Timing Optimization

Ahatract-We investigate the existence and uniqueness of robust time-optimal control solutions of flexible structures for rest-torest motion. We show that several robust time-optimal control designs for flexible systems are equivalent to traditional nonrobust time-optimal controls for difirent systems. This equivalence implies that the robust time-optimal controllers must then have all the properties that are known about traditional timeoptimal controllers. Further, many of the numerical methods developed for generating time-optimal commands are directly applicable to designing robust time-optimal commands. 0

The Western Research Laboratory (WRL) is a computer systems research group that was founded by Digital Equipment Corporation in 1982. Our focus is computer science research relevant to the design and application of high performance scientific computers. We test our ideas by designing, building, and using real systems. The systems we build are research prototypes; they are not intended to become products.

An improved proximate time-optimal (PTO) positioning control approach with discrete-time sliding-mode control theory for a Hard Disk Drive (HDD) servo is presented. A third order velocity reference profile is introduced to improve the second order ones in the conventional proximate time-optimal servomechanism (PTOS). The proposed approach eliminates the mode-switching mechanism and dramatically reduces the seek time by 5-50%. Moreover, it is robust to unmodelled dynamics and parameter variations. Its effectiveness is verified in a simulation.

ence on Roborics and A U~O I W K 2. S h i l l e r S. 3ubowsky l a s e a r c h Assisunc Pro terror The mtioa of c u r r e n t i n d u s t r i a l n r n f p u l a t o r s is t y p i c a l l y c o n t r o l l e d so L ! C tasks are not done io 8 rfninum t i m e o p t i m~l manner. The r e s u l t is s u b s u n t f a l l y lower p r o d u c t i v i t y Chm Chat poteatial Ly possib le. JOCentLy a ColpUU C i O M l Ly e f f i c i e n t algorithm !ma been dereloped LO f i n d the t r u e iinimum tine optimal aocioa f o r a M n i p U b t O t novily along a s p e c i f i e d path in space rht uses bo-L!a f u l l aonlfnear dynamic c . k r a C t e t Of the a n i p u l a t r and the c o n s t r a i n t s Imposed by Lts i m p l o r e n u t f o n of c. 90 algorithm c a l l e d 0PYAR.Y is described which u n meat p r a c t i c a l l y gmeral six dogroe-of-freedom a u a i p u l a t o r s . Exraples a r e presented which show 3PTAR.Y eo ba a u s e f u l design tool f o r manipulators. their u r k s and work places. The algorftSm is extended L a O P T A X l LO i n c l u d e &e eoastraints fmposed by s a n i p u l a t o r payloads and end-effectors. A Computer Aided 3esi;o (CAD) C . fn troduc ti on The p r o d u c t i v i t y of p.ny i n d u s t r i a l robotic m n f p u l a c o c u s k s can 5. faproved by !mViBg n a n i p u l a t o r s aov. more quickLy. 3uc several f a c t o r s L h i t r u n i ? u l a t o r speeds. such as the f i i i t e c a p a b f l l t e s o f 3 s y s t e m ' s a c t u a t o r s and the level of jynamic forces a h i c h cSe object baing manipulated u a t o l e r a t e r i c h o u t lamage or b e i n s pulled out of che g r i p p e r . Ivan sore import.nc, the desisur o € currant a a n i p u l a t o r c o n t r o l l e t s do a o t p e r m i t i n d u s t r i a l n a n i p u l a t o r s to move as q u i c k l y as they 3f;hC. because t h y do not use e f f e c t i v e l y L.0 f u l l u p a b i l i t i e s of choir actuators, nor o p e r a t e a t o r aear che Units Lmposed by their payloads o r end-effectors. Yanipulator d p m f e s are h i z h l y i o n l i n e a r and complex. met? a c t u a f o r s a r e r r q u i r e d to produce complex, tine varying torques or f o r c e r in order f o r the a a n i p u l a t o r t o follow e v m r e l a t f v o l y simple paths: tSe dynamic f o r c e s a t the payload a r e e q u a l l y eo=?Lex. Today's commercfal manipulators are proqramed EO move along cheit p a t h s a t t h eonsunt a c c e i e r a t t o n s 3nd v e l o c i t i e s .

A microprocessor implementing IBM S/390 architecture operates in a 10 + 2 way system at frequencies up to 411 MHz (2.43 ns). The chip is fabricated in a 0.2-m L e CMOS technology with five layers of metal and tungsten local interconnect. The chip size is 17.35 mm 2 17.30 mm with about 7.8 million transistors. The power supply is 2.5 V and measured power dissipation at 300 MHz is 37 W. The microprocessor features two instruction units (IU's), two fixed point units (FXU's), two floating point units (FPU's), a buffer control element (BCE) with a unified 64-KB L1 cache, and a register unit (RU). The microprocessor dispatches one instruction per cycle. The dual-instruction, fixed, and floating point units are used to check each other to increase reliability and not for improved performance. A phase-locked-loop (PLL) provides a processor clock that runs at 22 the system bus frequency. High-frequency operation was achieved through careful static circuit design and timing optimization, along with limited use of dynamic circuits for highly critical functions, and several different clocking/latching strategies for cycle time reduction. Timing-driven synthesis and placement of the control logic provided the maximum flexibility with minimum turnaround time. Extensive use of self-resetting CMOS (SRCMOS) circuits in the on-chip L1 cache provides a 2.0-ns access time and up to 500 MHz operation.

A method is presented to obtain the time-optimal motions for robotic manipulators. It considers the full nonlinear dynamics of the manipulator, its actuator saturation limits, and gripper and payload constraints. It also accounts for both the presence of obstacles in the work space and restrictions on the motion of the manipulator's joints. The method is computationally practical and has been implemented for the optimal trajectory planning of general six degree-of-freedom manipulators. Examples are presented that demonstrate the substantial improvement in manipulator performance that can be achieved using this method.

In this paper, we consider a multicommodity flow problem where for each pair of vertices, (u,v), we are required to sendf half-units of commodity (uv) from u to v and f half-units of commodity (vu) from v to u without violating capacity constraints. Our main result is an algorithm for performing th9 task provided that the capacity of each cut exceeds the demand across the cut by a b(log n) factor. The condition on cuts is required in the worst case, and is trivially within a i(log n) factor of optimal for any flow problem.

On today's commodity clusters, achieving nearoptimal speedup is very hard. We have previously shown that parallel applications using synchronous sequential MPI calls can be optimized by runtime replacement with corresponding asynchronous MPI operations. This may be achieved by protecting memory used by the MPI call from application writes until the operation is complete. However, changing the protection bits of memory pages, which alters the page table and flushes the CPU caches, may introduce a significant overhead. In the case of overlapping requests, which are common for applications with domain decompositions using border exchanges of ghost cells, this would have to be done multiple times for each communications phase.

This paper focuses on time-optimal and time-energy optimal path tracking, which are subproblems in optimal motion planning of robot systems. Through a nonlinear change of variables, the time-energy optimal path tracking problem is transformed here into a convex optimal control problem with a single state variable. A direct transcription method is presented that reduces finding the globally optimal trajectory to solving a second-order cone program using robust numerical algorithms that are freely available. Application to a six-DOF KUKA 361 industrial robot carrying out a writing task illustrates the practicality of the new method.

This paper presents a Matlab based Scheduling toolbox TORSCHE (Time Optimization of Resources, SCHEduling). The toolbox offers a collection of data structures that allow the user to formalize various off-line and online scheduling problems. Algorithms are simply implemented as Matlab functions with fixed structure allowing users to implement new algorithms. A more complex problem can be formulated as an Integer Linear Programming problem or satisfiability of boolean expression problem. The toolbox is intended mainly as a research tool to handle control and scheduling co-design problems. Therefore, we provide an interfaces to a real-time Matlab/Simulik based simulator TrueTime and a code generator allowing to generate parallel code for FPGA.

Collision-free, time-optimal navigation of a real wheeled robot in the presence of some static obstacles is undertaken in the present study. Two soft computing-based approaches, namely genetic-fuzzy system and genetic-neural system and a conventional potential field approach have been developed for this purpose. Training is given to the soft computing-based navigation schemes off-line and the performance of the optimal motion planner is tested on a real robot. A CCD camera is used to collect information of the environment. After processing the collected data, the communication between the robot and the host computer is obtained with the help of a radio-frequency module. Both the soft computing-based approaches are found to perform better than the potential field method in terms of the traveling time taken by the robot. Moreover, the performance of fuzzy logic-based motion planner is found to be comparable with that of neural network-based motion planner, although the training of the former is seen to be computationally less expensive than the latter. Sometimes the potential field method is unable to yield any feasible solution, specifically when the obstacle is found to be just ahead of the robot, whereas soft computing-based approaches have tackled such a situation well.

In this paper, we consider sorting problem with n elements distributed over a number of processing entities in a distributed system. We have derived an alternative, efficient algorithm with the worst case lower bound of (n − 1) rounds for distributed sorting on a line network, where n is the number of processors. The proposed distributed sorting algorithm improves the performance of each processor without creating copies of (n − 2) elements at intermediate processors and reduces the execution time of Sasaki's time−optimal algorithm [A.Sasaki, A time-optimal distributed sorting algorithm on a line network, Inform. Process. Lett., 83(2002) pp. 21-26]. Also all processors do not necessarily perform the disjoint comparison-exchange operations and simulation results show that the proposed algorithm results in better execution time with the identity of processors. This algorithm could also be extended for sorting the distributed elements on the linear embedding obtained from a general network.

Real time control of five-axis machine tools requires smooth generation of feed, acceleration and jerk in CNC systems without violating the physical limits of the drives. This paper presents a feed scheduling algorithm for CNC systems to minimize the machining time for five-axis contour machining of sculptured surfaces. The variation of the feed along the five-axis tool-path is expressed in a cubic B-spline form. The velocity, acceleration and jerk limits of the five axes are considered in finding the most optimal feed along the toolpath in order to ensure smooth and linear operation of the servo drives with minimal tracking error. The time optimal feed motion is obtained by iteratively modulating the feed control points of the B-spline to maximize the feed along the tool-path without violating the programmed feed and the drives' physical limits. Long tool-paths are handled efficiently by applying a moving window technique. The improvement in the productivity and linear operation of the five drives is demonstrated with five-axis simulations and experiments on a CNC machine tool. r

Doped and undoped SACVD recipes were investigated with respect to their clean performance with a new calorimetric probe sensor. Endpoint curves were collected with a standalone software utility, and results were analyzed post-acquisition offline. The impact of preventive maintenance (PM) activities and different single/multiple cleans towards clean performance were investigated. A numerical model for the clean behavior after annual chamber PM´s was developed. Clean time optimization was carried out for different recipes.

The editors of this volume, Nadia Nedjah, Ajith Abraham and Luiza de Macedo Mourelle, have done a superb job of assembling some of the most innovative and intriguing applications and additions to the methodology and theory of genetic programming -an automatic programming technique that starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem.

In this paper, we propose two algorithms for generating a complete n-bit binary reflected gray code sequence. The first one is called Backtracking. It generates a complete n-bit binary reflected gray code sequence by generating only a sub-tree instead of the complete tree. In this approach, both the sequence and its reflection for n-bit is generated by concatenating a ldquo0rdquo and a ldquo1rdquo to the most significant bit position of the n-1 bit result generated at each leaf node of the sub-tree. The second one is called MOptimal. It is the modification of a space and time optimal approach [8] by considering the minimization of the total number of outer and inner loop execution for this purpose. In this method, both a sequence and its reflection for n-bit is also generated during each inner loop execution instead of generating only one sequence by adding ldquo0rdquo and ldquo2n-1rdquo to the previous n-1 bit sequence. Finally, we evaluate the performance of the proposed and existing algorithms by measuring the execution time with respect to number of bits and compare the results with each other. Simulation results demonstrate that Backtracking takes small execution time up to 10 bits with maximum improvement of 17.02%. The evaluation also demonstrates that MOptimal also takes small execution time for more than 15 bits showing an improvement of 2.10% for 23 bits.

GPGPUs have recently emerged as powerful vehicles for generalpurpose high-performance computing. Although a new Compute Unified Device Architecture (CUDA) programming model from NVIDIA offers improved programmability for general computing, programming GPGPUs is still complex and error-prone. This paper presents a compiler framework for automatic source-to-source translation of standard OpenMP applications into CUDA-based GPGPU applications. The goal of this translation is to further improve programmability and make existing OpenMP applications amenable to execution on GPGPUs. In this paper, we have identified several key transformation techniques, which enable efficient GPU global memory access, to achieve high performance. Experimental results from two important kernels (JACOBI and SPMUL) and two NAS OpenMP Parallel Benchmarks (EP and CG) show that the described translator and compile-time optimizations work well on both regular and irregular applications, leading to performance improvements of up to 50X over the unoptimized translation (up to 328X over serial on a CPU).

A newly developed ball burnishing tool was designed and tested for surface finishing of large flat surfaces in a shortest possible time. Optimization and analysis of the burnishing process were carried on AISI 1010 steel hot-rolled plates using the Taguchi technique and response surface methodology (RSM) to identify the effect of burnishing parameters (i.e., burnishing speed, burnishing force, and feed rate) on surface roughness, surface hardness, and microstructure of burnished surfaces. The optimal burnishing parameters were found after conducting the TaguchiÕs L 25 matrix experiments and obtaining the response models for the surface roughness and the hardness. It was found that the burnishing force has the most influential effect on the surface roughness and hardness, followed by the burnishing speed, and least influence by the feed rate. In addition, microstructural examinations of the burnished surface indicate that burnishing force more than 400 N causes flaking of the burnished surfaces. The optimal burnishing parameters for the steel plates were a combination of a burnishing speed of 235 rpm, a burnishing force of 400 N, and a feed rate of 0.18 mm/rev. Using these parameters, the mean surface roughness has been improved from Ra = 2.48 to 1.75 lm, while the hardness increases from 59 to 65.5 HRB.

Telecommunication has seen extensive evolution in last couple of decades and MW links have been devised to ensure transmission links of high data rates and to ensure Quality of Service (QoS). MW antenna used in communication systems is regularly affected by environmental factor and generally by wear and tear of mounts. These factors cause the optimally directed antennas to be perturbed from respective main lobes. An automated antenna alignment that works without human intervention can decrease the down time and ensure a reliable communication between the near and far end terminals of the Base Transceiver Station (BTS). Results are presented to indicate antenna alignment in time optimal manner.

There is a strong need for advanced control methods in battery management systems, especially in the plug-in hybrid and electric vehicles sector, due to cost and safety issues of new high-power battery packs and high-energy cell design. Limitations in computational speed and available memory require the use of very simple battery models and basic control algorithms, which in turn result in suboptimal utilization of the battery. This work investigates the possible use of optimal control strategies for charging. We focus on the minimumtime charging problem, where different constraints on internal battery states are considered. Based on features of the openloop optimal charging solution, we propose a simple one-step predictive controller, which is shown to recover the time-optimal solution, while being feasible for real-time computations. We present simulation results suggesting a decrease in charging time by 50% compared to the conventional constant-current / constant-voltage method for lithium-ion batteries. †

This article presents a method for determining smooth and time-optimal path constrained trajectories for robotic manipulators and investigates the performance of these trajectories both through simulations and experiments. The desired smoothness of the trajectory is imposed through limits on the torque rates. The third derivative of the path parameter with respect to time, the pseudo-jerk, is the controlled input. The limits on the actuator torques translate into state-dependent limits on the pseudoacceleration. The time-optimal control objective is cast as an optimization problem by using cubic splines to parametrize the state space trajectory. The optimization problem is solved using the flexible tolerance method. The experimental results presented show that the planned smooth trajectories provide superior feasible time-optimal motion.

In this paper the design and the experimental verification of a Constrained Finite Time Optimal (CFTO) control scheme for the attitude control of an Unmanned Quadrotor Helicopter (UqH) subject to wind gusts is being presented. In the proposed design the UqH has been modeled by a set of Piecewise Affine (PWA) linear equations while the wind gusts effects are embedded in the system model description as the affine terms. In this approach the switching among the PWA model descriptions are ruled by the rate of the rotation angles. In the design of the stabilizing CFTO-controller both the magnitude of external disturbances (worst case applied wind gust), and the mechanical constraints of the UqH such as maximum thrust in the rotors and UqH's angles rate are taken under consideration in order to design an off-line controller that could rapidly be applied to a UqH in a form of a look-up table. The proposed control scheme is applied in experimental studies and multiple test-cases are presented that prove the efficiency of the proposed scheme.

A nonlinear model describing the relationship between the biosurfactant concentration as a process output and the critical medium components as the independent variables was developed by artificial neural network modeling. The model was optimized for the maximum biosurfactant production by using genetic algorithm. Based on a single-factor-at-a-time optimization strategy, the critical medium components were found to be glucose, urea, SrCl 2 and MgSO 4 . The experimental results obtained from a statistical experimental design were used for the modeling and optimization by linking an artificial neural network (ANN) model with genetic algorithm (GA) in MATLAB. Using the optimized concentration of critical elements, the biosurfactant yield showed close agreement with the model prediction. An enhancement in biosurfactant production by approximately 70% was achieved by this optimization procedure. j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / b i o r t e c h based densitometric method and also corroborated by dry weight method .

An experimental study aimed at examining the effects of hydrogen addition on cycle-bycycle variation (CCV) in an SI engine was conducted on a 6-cylinder throttle body injection natural gas (NG) engine. Two types of fuels, CNG and 80/20 (in volume) CNG/hydrogen mixtures, were used for comparison purposes. The results showed that coefficient of variation (CoV) in both maximum pressure ðP max Þ and indicated mean effective pressure (IMEP) could be reduced by hydrogen addition and that positive effect would be more obvious as the engine was further leaned out. The duration of flame development and propagation as well as the CCVs in flame propagation duration could be simultaneously reduced by hydrogen addition, all of which are beneficial to improve combustion stability and thought to be reasons for the reduction in CoV imep . Stability of combustion phasing that is crucial to the effectiveness of ignition timing optimization was also improved by hydrogen. Hydrogen addition was also proved to be good to the control of emission of NO x and unburned HC. Hence it is concluded that hydrogen addition is an effective and applicable approach to keep down CCVs in lean burn spark-ignition engines.

In this work TiO 2 layers have been deposited by screen-printing in common glazed ceramic tiles. These TiO 2 layers were evaluated for the photocatalytic degradation of Orange II in aqueous solutions, in a batch photoreactor under visible light, and compared with TiO 2 (anatase) suspensions. The photocatalytic behaviour of the TiO 2 was evaluated by taking into account experimental variables which include (i) firing temperature of the TiO 2 printed layer; (ii) layer thickness; (iii) operation time. Optimal processed layers showed an interesting decolourisation performance (over 90% efficiency after 7-8 h). The maximum decolourisation rate, assuming an apparent first order reaction, is over 0.050 min −1 and is close to values reported in the literature for supported TiO 2 photocatalysis under UV irradiation. We anticipate that these new ceramic materials might be developed as an interesting alternative to TiO 2 suspensions, for example in photocatalytic applications excusing the removal of the particles at the end of the process.

We address the problem of crosstalk computation and reduction using circuit and layout techniques in this paper. We provide easily computable expressions for crosstalk amplitude and pulse width in resistive, capacitively coupled lines. The expressions hold for nets with arbitrary number of pins and of arbitrary topology under any specified input excitation. Experimental results show that the average error is about 10% and the maximum error is less than 20%. The expressions are used to motivate circuit techniques, such as transistor sizing, and layout techniques, such as wire ordering and wire width optimization to reduce crosstalk.

In this paper, a "real-time" traffic signal control strategy is provided using genetic algorithms to provide nearoptimal traffic performance for intersections. Real-time traffic signal control is an integral part of the urban traffic control system and providing effective real-time traffic signal control for a large complex traffic network is an extremely challenging distributed control problem. The developed "intelligent" system makes "real-time" decisions as to whether to extend green time for a set of signals. The model is developed using genetic algorithm implemented in MATLAB. A traffic emulator is developed in JAVA to represent dynamic traffic conditions. The emulator conducts surveillance after fixed interval of time and sends the data to genetic algorithm, which then provides optimum green time extensions and optimizes signal timings in real time. The optimization parameters are -total number of vehicles in a road and importance of the road in the intersection. In the end, by comparing the experimental result obtained by the fixed time and real time based traffic systems which improves significant performance for intersections, we confirmed the efficiency of our intelligent real time based control system.

The dynamic behavior of a planar gantry crane with hoisting of the load is investigated. The command generation method of input shaping is proposed for reduction of the residual vibration. Several versions of input shaping are evaluated and compared with time-optimal rigid-body commands over a wide range of parameters. Input shaping provides signi"cant reduction in both the residual and transient oscillations, even when the hoisting distance is a large percentage of the cable length. Experimental results from a 15-ton gantry crane at the Savannah River Technology Center are used to support the numerical results.

An undergraduate level laboratory course on digital signal processors and their use in real-time digital signal processing (DSP) systems is described. Special emphasis is put on some practical issues such as execution time optimization, finite wordlength effects and a pipelined strategy as a suitable way to improve the performance of a real-time DSP system. The primary purpose of the laboratory is a better understanding of the theoretical concepts and a more active participation of the students in the course. We think that this paper will be of interest to those teaching related courses such as Introduction to DSP, Digital Signal Processing, Real-time DSP, Microprocessors and Hardware/Software Interaction. The well-known Texas Instruments' TMS320C2x and TMS320C5x fixed-point processors are used as the fundamental tool in the lab experiments and the TMS320C3x is suggested as a low-cost floating-point alternative. Enough detail is provided in the paper to duplicate certain parts of the experiments.

In this paper we propose to analyze the impact of the facets, constituting a railway dynamical environment, on the electromagnetic wave propagation mechanisms. This study allows reducing the computation times of a radio wave propagation simulator based on ray tracing. The obtained results drive to gain in computation time higher than five.

The aim of this study was to assess the effect of the recovery duration in intermittent training drills on metabolism and coordination in sport games. Ten nationally ranked male tennis players (age 25.3+/-3.7 years, height 1.83+/-0.8 m, body mass 77.8+/-7.7 kg; mean +/- sx) participated in a passing-shot drill (baseline sprint with subsequent passing shot) that aimed to improve both starting speed and stroke quality (speed and precision). Time pressure for stroke preparation was individually adjusted by a ball-machine and corresponded to 80% of maximum running speed. In two trials (T10, T15) separated by 2 weeks, the players completed 30 strokes and sprints subdivided into 6 x 5 repetitions with a 1 min rest between series. The rest between each stroke-and-sprint lasted either 10 s (T10) or 15 s (T15). The sequence of both conditions was randomized between participants. Post-exercise blood lactate concentration was significantly elevated in T10 (9.04+/-3.06 vs 5.01+/-1.35 mmol x l(-...

We present an outdoor terrain planner that finds near optimal trajectories under dynamic and kinematic constraints. The planner can find solutions in close to real time by relaxing some of the assumptions associated with costly rigid body simulation and complex terrain surface interactions. Our system is based on control-driven Probabilistic Roadmaps and can efficiently find and optimize a near time-minimum trajectory. We present simulated results with artificial environments, as well as a real robot experiment using Segway Robotic Mobile Platform.

This paper addresses the compile-time optimization of a class of nested-loop computations that arise in some computational physics applications. The computations involve summations over products of array terms in order to compute multi-dimensional surface and volume integrals. Reordering additions and multiplications and applying the distributive law can significantly reduce the number of operations required in evaluating these summations. In a multiprocessor environment, proper distribution of the arrays among processors will reduce the inter-processor communication time. We present a formal description of the operation minimization problem, a proof of its NPcompleteness, and a pruning strategy for finding the optimal solution in small cases. We also give an algorithm for determining the optimal distribution of the arrays among processors in a multiprocessor environment.

Current fMRI retinotopic mapping procedures often use checkerboard stimuli consisting of expanding rings and rotating wedges to measure the topography within human visual areas. Efficient procedures are well described in the literature. For many experimental paradigms, e.g., visuo-spatial attention paradigms, the identification of taskrelevant positions is the only mandatory prerequisite. To define these specific ''regions-of-interest'' (ROIs), spatially defined localizers are used. A precise evaluation of localizer techniques in regard to efficient scanning time, optimal BOLD (blood oxygenic level dependent) response, as well as quantification of the resulting ROIs within each visual area (size, overlap, surround effects) has not been studied to date. Here, we suggest a mapping procedure designed to quantify spatial and functional properties of single positions at close proximity in multiple human visual areas. During a passive viewing task, various stimuli (e.g., checkerboards or colored objects) subtending 1.4-of visual angle were presented at one out of four positions in a randomized block design. We measured the degree of overlap between positions at different hierarchical levels of the visual system (V1 -V4v) and quantified modulatory effects on a specific position by stimulation at neighboring (1.7-spacing) or distant positions (5.1-or 8.5-spacing). Within each visual area, ''mexican-hat'' distributions of local signal intensity changes, which describe a particular combination of facilitatory and suppressive effects, were found. Cubic fitting revealed the most localized tuning effect in V1, which gradually decreased throughout the higher visual areas. Colored objects were most efficient in localizing circumscribed retinotopic positions in both early and higher areas. D

This paper presents an adaptive filtering system for separation of two bio-impedance signal components: cardiac and respiratory signals. The proposed filtering system is adaptive to the parameters of the input signal's cardiac component (the reference signal), which is corrupted by the respiratory component and also by additive stochastic disturbances. The adaptation is achieved applying estimation and continuous tracking of the heart rate using a time-optimal Adaptive Phase-Locked Loop (APLL). Technical solutions of the filtering system are oriented on applications in portable and implantable medical devices.

This paper explores a novel way to incorporate hardware-programmable resources into a processor microarchitecture to improve the performance of general-purpose applications. Through a coupling of compile-time analysis routines and hardware synthesis tools, we automatically configure a given set of the hardware-programmable functional units (PFUs) and thus augment the base instruction set architecture so that it better meets the instruction set needs of each application. We refer to this new class of general-purpose computers as PRogrammable Instruction Set Computers (PRISC). Although similar in concept, the PRISC approach differs from dynamically programmable microcode because in PRISC we define entirely-new primitive datapath operations. In this paper, we concentrate on the microarchitectural design of the simplest form of PRISC-a RISC microprocessor with a single PFU that only evaluates combinational functions. We briefly discuss the operating system and the programming language compilation techniques that are needed to successfully build PRISC and, we present performance results from a proof-of-concept study. With the inclusion of a single 32-bit-wide PFU whose hardware cost is less than that of a 1 kilobyte SRAM, our study shows a 22% improvement in processor performance on the SPECint92 benchmarks.

This study is aimed at investigating the effect of injection system parameters such as injection pressure, injection timing and nozzle tip protrusion on the performance and emission characteristics of a twin cylinder water cooled naturally aspirated CIDI engine. Biodiesel, derived from pongamia seeds through transesterification process, blended with diesel was used as fuel in this work. The experiments were designed using a statistical tool known as Design of Experiments (DoE) based on response surface methodology (RSM). The resultant models of the response surface methodology were helpful to predict the response parameters such as Brake Specific Energy Consumption (BSEC), Brake Thermal Efficiency (BTE), Carbon monoxide (CO), Hydrocarbon (HC), smoke opacity and Nitrogen Oxides (NO x) and further to identify the significant interactions between the input factors on the responses. The results depicted that the BSEC, CO, HC and smoke opacity were lesser, and BTE and NO x were higher at 2.5 mm nozzle tip protrusion, 225 bar of injection pressure and at 30°BTDC of injection timing. Optimization of injection system parameters was performed using the desirability approach of the response surface methodology for better performance and lower NO x emission. An injection pressure of 225 bar, injection timing of 21°BTDC and 2.5 mm nozzle tip protrusion were found to be optimal values for the pongamia biodiesel blended diesel fuel operation in the test engine of 7.5 kW at 1500 rpm.

In a typical disk drive servo system, two or more types of controllers are used for track seeking, track following, and track settling modes. This leads to the problem of mode switching among these controllers. We present in this paper a unified control scheme, the discrete-time composite nonlinear feedback control, which can perform all the above functions in hard disk drive (HDD) servo systems with actuator saturation. The proposed scheme is composed by combining a linear feedback law and a nonlinear feedback law. The linear feedback law is designed to yield a fast response, while the nonlinear feedback law is used to increase the damping ratio of the closed-loop system as the system output approaches the command input. In the face of actuator saturation, this control law not only increases the speed of closed-loop response, but also improves the settling performance. Implementation results show that the proposed method outperforms the conventional proximate time-optimal servomechanism by about 30% in settling time.

This study is aimed at investigating the effect of injection system parameters such as injection pressure, injection timing and nozzle tip protrusion on the performance and emission characteristics of a twin cylinder water cooled naturally aspirated CIDI engine. Biodiesel, derived from pongamia seeds through transesterification process, blended with diesel was used as fuel in this work. The experiments were designed using a statistical tool known as Design of Experiments (DoE) based on response surface methodology (RSM). The resultant models of the response surface methodology were helpful to predict the response parameters such as Brake Specific Energy Consumption (BSEC), Brake Thermal Efficiency (BTE), Carbon monoxide (CO), Hydrocarbon (HC), smoke opacity and Nitrogen Oxides (NO x ) and further to identify the significant interactions between the input factors on the responses. The results depicted that the BSEC, CO, HC and smoke opacity were lesser, and BTE and NO x were higher at 2.5 mm nozzle tip protrusion, 225 bar of injection pressure and at 30°BTDC of injection timing. Optimization of injection system parameters was performed using the desirability approach of the response surface methodology for better performance and lower NO x emission. An injection pressure of 225 bar, injection timing of 21°BTDC and 2.5 mm nozzle tip protrusion were found to be optimal values for the pongamia biodiesel blended diesel fuel operation in the test engine of 7.5 kW at 1500 rpm.

It is not easy to apply the algorithms for time-optimal trajectory planning in practice because they rely on the exact dynamic models of the system. In this paper we propose a simplification of the timeoptimal path-tracking control algorithms. The proposed algorithms are based only on the kinematic constraints. Such simplifications can be justified in cases when the actuators are never pushed to their torque limits and when the task gives the constraints for the optimal trajectory. One of the practical applications of these simplified algorithms are palletizing robots. For these robots the gripping force is one of the key factors. If the dynamic forces are to high the gripper may loose the load. Assuming that the payload is constant during the motion the dynamic properties in the task space are not changing, and the maximal allowable accelerations can be determined from maximal gripping force. The acceleration and velocity bounds are then used in the trajectory planning algorithm. Although the the simplifications reduce the computational complexity the trajectory has still to be precalculated off-line. The proposed algorithm has been implemented in our PC-based robot controller which is used to control the palletizing robot. Experimental results confirm that the proposed algorithms assure the end-effector motion in the prescribed bounds.

Virginia P. Sisiopiku, Ph.D. Associate Professor The University of Alabama at Birmingham 1530 3rd Ave S, Hoehn 311 Birmingham, AL 35205-4440 E-mail: [email protected] ... Abhishek Acharya, MSCE Transportation Engineer 16912 Yukon Avenue #B, Torrance CA 90504 E-...

Sensors are typically deployed to gather data about the physical world and its artifacts for a variety of purposes that range from environment monitoring, control, to data analysis. Since sensors are resource constrained, often sensor data is collected into a sensor database that resides at (more powerful) servers. A natural tradeoff exists between the sensor resources (bandwidth, energy) consumed and the quality of data collected at the server. Blindly transmitting sensor updates at a fixed periodicity to the server results in a suboptimal solution due to the differences in stability of sensor values and due to the varying application needs that impose different quality requirements across sensors. This paper proposes adaptive data collection mechanisms for sensor environments that adjusts to these variations while at the same time optimizing the energy consumption of sensors. Our experimental results show significant energy savings compared to the naive approach to data collection.