Gain Scheduling

In an industrial gas-phase polyethylene reactor, the safe operating range of temperature is rather narrow. Even within this temperature range, temperature excursions must be avoided because they can result in low catalyst productivity and significant changes in product properties. In previous work, using a first-principles model, including the recycle stream and the heat exchange system, a PID temperature controller with robust performance was designed via optimization in the frequency domain for different operating points. For the reactor total pressure, ethylene partial pressure, H2/C2 and C4/C2 molar ratios, PI controllers were designed. In the PID temperature controller, if the manipulated variable (cooling water valve opening) saturates then the reactor operates without a feedback temperature controller, leading to oscillatory behaviour and limit cycles. It has been demonstrated that the manipulated variable saturation and the nonlinear dynamic behaviour are removed when auxiliary manipulated variables, obtained by bifurcation analysis, are used in a multivariable control strategy for the reactor temperature control. In this work, two control structures are compared to define the most suitable proposal for implementation in an industrial reactor and the impact of these control structures in the reactor production and in the polymer melt index are analyzed. The first control structure considers the control problem using the designed PID controller for the reactor temperature and includes a switching strategy with a PI controller for the auxiliary manipulated variables. The second control structure considers the control problem also using the designed PID controller for the reactor temperature, however including a MPC controller for the auxiliary manipulated variables.

This paper describes the design and implementation of digital controllers for a flywheel energy storage device that incorporates a radial flux hybrid permanent magnetic bearing. Although the uncontrolled device is asymptotically stable, active control is required to: (i) ensure that a finite radial air gap is maintained at all times, and (ii) attenuate the oscillations of the flywheel which reduce the efficiency of the motor generator. The paper presents the design of gain scheduled discrete time linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers for this rotordynamic system. Real time experiments are conducted to investigate the performance of the controllers. The result indicates that the LQR controller with approximate system velocities is easier to implement than the LQG controller, and also provides superior performance. r

The quality of generated electricity in power systems is dependent on the system output, which has to be of constant frequency and must maintain the scheduled power and voltage. Therefore, load frequency control, LFC, is very important for power systems. However, the LFC problem in hydroelectrical power systems has received little attention by researchers so far. In this study, a conventional proportional integral (PI) controller and a fuzzy gain scheduled proportional integral (FGPI) controller have been compared for applying to a single area and a two area hydroelectric power plant, considering that Turkey has several hydro power sources. The comparison study indicated that the proposed FGPI controller has better performance than the conventional PI controller. The study results were compared by simulation.

Adaptive techniques such as gain scheduling, automatic tuning and continuous adaptation have been used in industrial single-loop controllers for about ten years. This paper gives a survey of the different adaptive techniques, the underlying process models and control designs. An overview of industrial products is also presented, which includes a fairly detailed investigation of four different adaptive single-loop controllers.

This paper is concerned with the synthesis of a robust gain-scheduled H∞ MIMO VDSC (Vehicle Dynamic Stability Controller), involving the steering and braking actuators. This VDSC aims at improving automotive vehicle yaw stability and lateral performances. The contribution of this work is to provide a methodology to synthesize such a controller while taking into account the braking actuator limitations (i.e. the actuator can only brake the rear wheels) and use the steering actuator only if it is necessary (e.g. if the braking system is not efficient enough to ensure vehicle stability, or in case of braking system failure). These objectives are treated in an original way by the synthesis of a parameter dependent controller built in the LPV framework and by the solution of an LMI problem. The proposed solution is coupled with a local ABS strategy to guarantee slip stability and make the solution complete for implementation issues. Nonlinear time and frequency domain simulations on a complex full vehicle model ( which has been validated on a real car), subject to critical driving situations, shows the efficiency and robustness of the proposed solution.

Functional electrical stimulation (FES) is the most commonly used technology for improving motor function in individuals who have spinal cord injury. Despite the wide range of FES applications reported in the literature, few electrical stimulation systems that can generate meaningful functional outcomes are currently available for use outside research laboratories. We tested proportional-integral-derivative, gain scheduling, and sliding mode control closed-loop control algorithms in a simulation of electrically induced knee extension against gravity to uncover some of the reasons why closed-loop control is not being more widely used in real-world FES systems. We also subjected the simulated FES system to muscle fatigue, muscle spasms, and the effects of muscle retraining. All of the controllers exhibited significantly degraded performance when these real-world nonlinear effects were included in the simulation. Moreover, all of the controllers were sensitive to variation in the parameters of the muscle recruitment function, which are subject to change during real-world FES use. We suggest several ways to improve the performance of closed-loop control algorithms for use in FES applications. We believe that closed-loop controllers have an important place in future FES applications, but the performance of these algorithms must be greatly improved before they can be implemented in real-world systems.

A simple well-performing adaptive control technique for pH control in fermentations of recombinant protein production processes is described and its design procedure is explained. First, the entire control algorithm was simulated and parameterized. Afterwards it was tested in real cultivation processes. The results show that this simple technique leads to significant reductions in the fluctuations of the pH values in microbial cultures at a minimum of expenditures. The signal-to-noise ratio and thus the information captured by the pH signal were increased by about an order of magnitude. This leads to a substantial improvement in the noise of many other process signals that are used to monitor and control the process. For instance, respiratory off-gas data of CO 2 and its derived carbon dioxide production rate signals from the cultures carry much less noise as compared to those values obtained with conventional pH control. Detailed process analysis revealed that even very small pH jumps of 0.03 values during the fermentation were shown to result in pronounced deflections in CO 2 -volume fraction of 8% (peak to peak). The proposed controller, maintaining the pH within the interval of 0.01 around the setpoint, reduces the noise considerably.

Adaptive techniques such as gain scheduling, automatic tuning and continuous adaptation have been used in industrial single-loop controllers for about ten years. This paper gives a survey of the different adaptive techniques, the underlying process models and control designs. An overview of industrial products is also presented, which includes a fairly detailed investigation of four different adaptive single-loop controllers.

In this paper a coordinated master control for a solid fuel power plant has been developed and the performance evaluated in terms of tracking capability, stability and robustness. The control strategy has been model-based predictive control (MPC) and it was evaluated on a nonlinear process model of the Vattenfall power plant Idbäcken in Nyköping, Sweden. The developed master MPC with gain scheduling has better performance compared to the existing PID controller which has been thoroughly studied and tuned in a previous project. The robustness of the proposed master MPC controller against common disturbances and parameter variation has been investigated and it shows that the proposed controller is more robust than the existing PID controller.

Abstrak-Quadcopter diharapkan dapat bergerak secara lincah dan efektif menyusuri lintasan horisontal. Berdasar hukum fisisnya, gerak lateral dapat terjadi karena adanya daya angkat dan terjadinya perubahan sudut dari quadcopter tersebut. Mengacu pada hal tersebut, sudut-sudut gerak pada quadcopterakan menjadi parameter untuk gerak maju atau menyamping yang secara langsung juga berpengaruh pada gerak vertikal.

This paper deals with the design of a control scheme that integrates braking and front steering to enhance the vehicle yaw stability and the lateral vehicle dynamics. The proposed VDSC (Vehicle Dynamic Stability Controller) allows control of the yaw rate and obtains good response for the sideslip angle. Besides, this controller takes into account the braking actuator limitations (i.e braking only the rear wheels) and limits the use of the steering actuator only in the linear vehicle handling region (stability region). To reach these objectives, an original parameter dependent LPV controller structure with consistent performances weights is designed. The solution of the problem is obtained within the LMI framework, while warranting H∞ performances. To prevent tires longitudinal slip due to brake forces generated by the controller, an ABS strategy is included in the control scheme. Computer simulations, carried out on a complex full vehicle model subject to critical driving situations, confirm the effectiveness of the proposed control system and the overall improvements in vehicle handling and stability.

This paper presents a novel algorithm for the induction motor torque control in field weakening region. Proposed method insures maximum DC bus utilization and offers DTC performance through the stator voltage angle control. The algorithm is simple, without the outer flux loop nor the inner current loop. Dynamic response is preserved over wide speed range by means of gain-scheduling. The paper comprises the implementation details and experimental results.

We consider the application of a conditional integrator based sliding mode control design for robust regulation of minimum-phase nonlinear systems to the control of the longitudinal flight dynamics of an F-16 aircraft. The design exploits the modal decomposition of the linearized dynamics into its short-period and phugoid approximations. The control design is based on linearization, but is implemented on the nonlinear multiple-input multiple-output longitudinal model of the F-16 aircraft. We consider model following for the angle-of- attack, with the regulation of the aircraft velocity (or the Mach- hold autopilot) as a secondary objective. It is shown through extensive simulations that the inherent robustness of the SMC design provides a convenient way to design controllers without gain scheduling, with transient performance that is far superior to that of a conventional gain-scheduled approach with integral control.

In this paper, a road adaptive modified skyhook control for the semi-active Macpherson strut suspension system of hydraulic type is investigated. A new control-oriented model, which incorporates the rotational motion of the unsprung mass, is introduced. The control law extends the conventional skyhook-groundhook control scheme and schedules its gains for various road conditions. Using the vertical acceleration data measured, the road conditions are estimated by using the linearized new model developed. Two filters for estimating the absolute velocity of the sprung mass and the relative velocity in the rattle space are also designed. The hydraulic semi-active actuator dynamics are incorporated in the hardware-in-the-loop tuning stage of the control algorithm developed. The optimal gains for the ISO road classes are discussed. Experimental results are included.

In this paper, a scheduled-gain SG-PID controller using LabVIEW-based scheduling technique, which consists of a set of virtual instruments, has been designed and experimentally tested for heating process. Gain scheduling is realized by automatic setting of the controller parameters using three sets of programmed parameters, depending on the relative error between actual process temperature and setpoint (desired temperature). Experimental results show that the proposed controller, compared with conventional C-PID controller, responds faster to the changes in the setpoint temperature, reduces the overshoots in temperature during transient period and makes the system more stable. It was noticed that the dynamic and steady-state errors in the system have been reduced.

In this work software-based PID controller with gain scheduling is implemented to drive a DC motor. LabVIEW PID controller tool with its associated gain scheduling VI was used. Motor start up interval was experimentally analyzed and divided into three regions with three related PID gains sets. Gain scheduling selection criterion was based on the dynamic error absolute value, and it was realized by using case structures. Experiments show that speed overshoot was eliminated and drive system response became faster. Generally it is possible to auto tune the PID controller to achieve a response with the required static or dynamic specifications.

We consider the application of a conditional integrator based sliding mode control design for robust regulation of minimum-phase nonlinear systems to the control of the longitudinal flight dynamics of an F-16 aircraft. The design exploits the modal decomposition of the linearized dynamics into its short-period and phugoid approximations. The control design is based on linearization, but is implemented on the nonlinear multiple-input multiple-output longitudinal model of the F-16 aircraft. We consider model following for the angle-ofattack, with the regulation of the aircraft velocity (or the Machhold autopilot) as a secondary objective. It is shown through extensive simulations that the inherent robustness of the SMC design provides a convenient way to design controllers without gain scheduling, with transient performance that is far superior to that of a conventional gain-scheduled approach with integral control.

The design of inexpensive multi-sensor attitude determination systems is discussed. The systems discussed fuse information from a triad of solid state rate gyros with an aiding system mechanized using GPS or magnetometers and accelerometers. Euler angle and quaternion-based sensor fusion algorithms are developed. Methods for gain scheduling and estimator pole placement are presented. Using simulation and flight test results, it is shown that quaternion-based algorithms simplify gain scheduling and improve transient response.

Narrow Tilting Vehicles (NTVs) are the convergence of a car and a motorcycle. They are expected to be the new generation of city cars considering their practical dimensions and lower energy consumption. However, due to their height to breadth ratio, in order to maintain lateral stability, NTVs should tilt when cornering. Unlike the motorcycle, where the driver tilts the vehicle himself, the tilting of an NTV should be automatic. Two tilting systems are available; Direct and Steering Tilt Control, the combined action of these two systems being certainly the key to improve considerably NTV dynamic performances. In this paper, multivariable control tools (H 2 methodology) are used to design, in a systematic way, lateral assistance controllers driving DTC, STC or both DTC/STC systems. A three degrees of freedom model of the vehicle is used, as well as a model of the steering signal, leading to a two degrees of freedom low order controller with an efficient feedforward anticipative part. Taking advantage of all the available measurements on NTVs, the lateral acceleration is directly regulated. Finally, a gain-scheduling solution is provided to make the DTC, STC, and DTC/STC controllers robust to longitudinal speed variations.

En el artículo se aborda la automatización de una autoclave utilizada en el proceso de esterilización. Se diseñaron algoritmos de control para la temperatura, la presión y el nivel del agua. Para realizar el control de la misma se trabajó inicialmente con un controlador PI diseñado con el método Ciancone-Marlin y luego se planteó una solución basada en la implementación de un controlador PI con ganancia programable sintonizado con la misma técnica y utilizando ecuaciones de regresión para el cálculo de sus parámetros. El método de ganancia programable se puede considerar un control adaptativo no lineal, en el sentido que se realiza con un controlador lineal cuyos parámetros cambian en función de las condiciones de operación según una ecuación o una tabla precalculada. Los algoritmos de control fueron programados en plataforma Labview

In this paper, an intelligent automated lane-keeping system is proposed and implemented on our vehicle platform, i.e., TAIWAN iTS-1. This system challenges the online integrating heterogeneous systems such as a real-time vision system, a lateral controller, in-vehicle sensors, and a steering wheel actuating motor. The implemented vision system detects the lane markings ahead of the vehicle, regardless of the varieties in road appearance, and determines the desired trajectory based on the relative positions of the vehicle with respect to the center of the road. To achieve more humanlike driving behavior such as smooth turning, particularly at high levels of speed, a fuzzy gain scheduling (FGS) strategy is introduced to compensate for the feedback controller for appropriately adapting to the SW command. Instead of manual tuning by trial and error, the methodology of FGS is designed to ensure that the closed-loop system can satisfy the crossover model principle. The proposed integrated system is examined on the standard testing road at the Automotive Research and Testing Center (ARTC) 1 and extraurban highways.

In this paper we present the integration of a Linear-Time-Varying Model-Predictive-Control (LTV-MPC), designed to stabilize a vehicle during sudden lane change or excessive speed-entry in curve, with a slip controller that converts the desired longitudinal tire force variation in pressure variation in the brake system. The lateral controller is designed using a three-degrees-of-freedom vehicle model taking into account both yaw rate and side slip angle of vehicle while the slip controller is a nonlinear gain scheduling P with feedforward action. The performances are validated with SIL technique, in particular, the authors use a proprietary simulator calibrated on an oversteering sport commercial car. Simulation results show the benefits of the control methodology used.

This paper addresses the path-following problem of steering an autonomous airplane along a predefined 3-D path, while performing a coordinated turn maneuver. The presented solution relies on the definition of a path-dependent error space to express the dynamic model of the vehicle, and of an output tracking error that guarantees both path-following and coordinated turn compliance. For controller design purposes, the error dynamics are approximated by a polytopic Linear Parameter Varying (LPV) system representation with piecewise affine dependency on the parameters. The synthesis problem is stated as an H2 minimization problem with pole placement contraints, and solved using Linear Matrix Inequalities (LMIs). The nonlinear controller is implemented within the scope of gainscheduling control theory, using the D-methodology. The performance of the designed controller is assessed in simulation, using the full nonlinear model of a small scale airplane.

Abstruct-A new adaptive control system for dc motor drive with field weakening is proposed. The adaptation mechanism is based on the gain scheduling. A deep knowledge of the phenomena in the drive was necessary to define the scheduled variables that capture the essential nonlinearities of the process considered. However, in practice, to realize the proposed adaptive control system, the only a priori knowledge required is the experimentally determined magnetization curve. Simulation and experimental results indicating high performances of the control system proposed, are presented.

Abstract: A rotorcraft-based unmanned aerial vehicle exhibits more complex properties compared to its full-size counterparts due to its increased sensitivity to control inputs and disturbances and higher bandwidth of its dynamics. As an aerial vehicle with vertical take-off and landing capability, the helicopter specifically poses a difficult problem of transition between forward flight and unstable hover and vice versa. The LPV control technique explicitly takes into account the change in performance due to the real-time parameter ...

Bu makalede akış kontrolü problemlerinin modellemesi için
yeni bir yöntem geliştirilmiştir. Bu yöntemde akışın
hesaplamalı akışkanlar dinamiği (HAD) benzetimleri ile elde
edilen anlık görüntülerden bir uygun dikgen ayrışımı (UDA)
elde edilir ve bu ayrışımın zaman katsayılarına sistem tanılama
yöntemleri uygulanarak bir doğrusal durum uzayı sistemi
oluşturulur. Bu işlem, kesme noktası tabir edilen birkaç
çalışma noktası için tekrarlanır ve kesme noktalarında elde
edilen dinamik modeller, bir çıkış harmanlama tekniği ile
birleştirilir. Oluşturulan modeller birkaç doğrusal zamanla
değişmeyen (DZD) sistemin bileşiminden oluşması
bakımından basit bir yapıya sahip olmakla birlikte, verilen bir
akış zarfı içindeki çok farklı akış koşullarını temsil edebilecek
güce sahiptir. Makalenin sonunda önerilen modelleme
yöntemi, Navier-Stokes denklemleri ile yönetilen ve kinematik
akmazlık değerinin değişkenlik gösterdiği bir akış probleminin
kontrolü üzerinde örneklendirilmiş ve başarılı sonuçlar elde
edildiği görülmüştür.

The area of the analysis and control of linear parameter-varying (LPV) systems has received much recent attention because of its importance in developing systematic techniques for gain-scheduling. An LPV system resembles a linear system that nonlinearly depends on time-varying parameters. Typical approaches for the analysis and control of LPV systems are the scaled small-gain and the dissipative systems approach using smooth parameter-dependent Lyapunov functions (PDLFs). The dissipative systems approach is the more desirable of the two techniques because it can directly treat time-varying parameters. and yield a general LPV-type controller. Furthermore, this approach attractively formulates analysis and synthesis problems as convex optimization problems involving linear matrix inequalities (LMIs) which are now very efficiently solved by computer. However, this approach has two major potential difficulties in selecting an optimal PDLF in order to reduce conservatism of the analysis and synthesis, and solving exactly convex optimization problems involving an infinite number of LMIs. The thesis presents new analysis and control design techniques to avoid these potential drawbacks of the smooth dissipative systems approach. The thesis focuses on a piecewise-affine parameter-dependent linear parameter-varying system and a nonsmooth piecewise-affine parameter-dependent Lyapunov function. To address the non-differential nature of both the LPV system and PDLF, the thesis develops a nonsmooth dissipative systems framework. Then the thesis fully characterizes several important analysis and synthesis problems of LPV systems with this nonsmooth framework. The new approach is shown to yield a less conservative, guaranteed result than previously published LPV approaches. The improvement is direct results of using a more accurate model in the analysis and control, and using a very general class of PDLFs. The derived analysis and synthesis formulations are finite-dimensional convex optimization problems. The new approach also provides a trade-off between conservatism and computational effort of the design technique. Several benchmark problems are used to demonstrate the usefulness, reliability, and feasibility of the proposed new approaches.

A new set of tools, including controller scaling, controller parameterization and practical optimization, is presented to standardize controller tuning. Controller scaling is used to frequency-scale an existing controller for a large class of plants, eliminating the repetitive controller tuning process for plants that differ mainly in gain and bandwidth. Controller parameterization makes the controller parameters a function of a single variable, the loop-gain bandwidth, and greatly simplifies the tuning process. Practical optimization is defined by maximizing the bandwidth subject to the physical constraints, which determine the limiting factors in performance. Collectively, these new tools move controller tuning in the direction of science.

We consider the application of a conditional integrator based sliding mode control design for robust regulation of minimum-phase nonlinear systems to the control of the longitudinal flight dynamics of an F-16 aircraft. The design exploits the modal decomposition of the linearized dynamics into its short-period and phugoid approximations. The control design is based on linearization, but is implemented on the nonlinear multiple-input multiple-output longitudinal model of the F-16 aircraft. We consider model following for the angle-ofattack, with the regulation of the aircraft velocity (or the Machhold autopilot) as a secondary objective. It is shown through extensive simulations that the inherent robustness of the SMC design provides a convenient way to design controllers without gain scheduling, with transient performance that is far superior to that of a conventional gain-scheduled approach with integral control.

The design problem of mixed L 2 , H 2 gain scheduling nonlinear state feedback controller for Linear Parameter Varying (LPV) systems subjected to actuator saturations and L 2 bounded disturbances is considered. First, a new formulation of H 2 controllers has been presented based on the Homogeneous Polynomial Parameter Dependent (HPPD) representation. Then a systematic procedure to generate a sequence of LMI conditions of increasing precision for obtaining a sub-optimal L 2 , H 2 state-feedback controller for LPV systems subject to actuator saturations and L 2 -bounded disturbances, has been presented. The presented method utilizes the modified sector condition for actuator saturation formalization and HPPD representation of LPV systems.

A microgrid is an integration of distributed energy sources, loads and energy storage systems. Indeed, energy storage systems are required in order to ensure reliability and power quality because of the intermittent nature of renewable energy sources and changes of load demand. Apart from that, the use of distributed energy storage units provides redundancy to the system and support possible increments in load consumption. In consequence, the control strategy used in the microgrid must take into account the stored energy balance between distributed energy storage units in order to avoid over-charge or deepdischarge in one of the energy storage units. Primary control in a microgrid is responsible for power sharing among units; and droop control is typically used in this stage. This paper proposes a modular and decentralized gain-scheduling control strategy based on fuzzy logic that ensures balanced stored energy among distributed energy storage units, as well as low voltage deviation in a DC microgrid. Hardware in the loop simulations show the performance of the proposed control strategy.

In web transport systems, the main problem is to control the web velocity and tensions independently, to prevent web breaks, folding, or damage. Interesting results have been obtained using multi-variable control strategies. Unfortunately, most of the existing methodologies are either not systematic or deal with the tracking and disturbance rejection problems as a whole, and not separately. This paper presents a complete methodology in order to design two-degrees-of-freedom (2DOF) controller. The feedforward part is based on a reference model allowing operators to obtain the desired tracking performances (in particular, web tensions and velocity decoupling). The feedback part ensures robustness and disturbance rejection and is designed using two high-level tuning parameters only, thanks to the Standard State Control (SSC) methodology. However, the system dynamics change greatly during the winding/unwinding process due to the winder/unwinder radius and inertia variations. Therefore, a gain-scheduling controller is derived from the interpolation of consistent realizations of the H 2 controllers obtained at different points of the operating domain. The resulting controller is tested on a realistic simulator first, and after discretization, on a 3-motor web-handling experimental platform. r

In this chapter a gain scheduled optimal controller is designed to solve the path-tracking problem of an airship. The control law is obtained from a coupled linear model of the airship that allows to control the longitudinal and lateral motions simultaneously. Due to the importance of taking into account wind effects, which are rather important due to the airship large volume, the wind is included in the kinematics, and the dynamics is expressed as function of the air velocity. Two examples are presented with the inclusion of wind, one considering a constant wind input and the other considering in addition a 3D turbulent gust, demonstrating the effectiveness of this single controller tracking a reference path over the entire flight envelope.

In this paper, an adaptive fuzzy controller gain scheduling scheme for power system load-frequency control is designed tu damp the frequency oscillations and to track its error to zero at steady state, A Sugeno type inference system is used in the proposed controller to adapt the scaling gains of a single fuzzy controller through a classical on-line monitoring of the most sensitive parameters of the system. The proposed controller avoids excessive patterns and training time compared to neural network based adaptive schemes. A typical single-area nonreheat power system is considered. Simulation results indicate that the proposed controller is insensitive to parameter changes in a wide range of operating condition, and to the generation rate constraints. Furthermore, it is simple io implement.

Thermostatic Radiator Valves (TRV) have proved their significant contribution in energy savings for several years. However, at low heat demands, an unstable oscillatory behavior is usually observed and well known for these devices. This instability is due to the nonlinear dynamics of the radiator itself which result in a large time constant and high gain for radiator at low flows. A remedy to this problem is to make the controller of TRVs adaptable with the operating point instead of widely used fixed PI controllers. To this end, we have derived a linear parameter varying model of radiator, formulated based on the operating flow rate, room temperature and the radiator specifications. In order to derive such formulation, the partial differential equation of the radiator heat transfer dynamics is solved analytically. Using the model, a gain schedule controller among various possible control strategies is designed for the TRV. It is shown via simulations that the designed controller based on the proposed LPV model performs excellent and stable in the whole operating conditions.

engines have the benefit of high efficiency with low emissions of NO and particulates. These benefits are due to the autoignition process of the dilute mixture of fuel and air during compression. However, because there is no direct-ignition trigger, control of ignition is inherently more difficult than in standard internal combustion engines. This difficulty necessitates that a feedback controller be used to keep the engine at a desired (efficient) setpoint in the face of disturbances. Because of the nonlinear autoignition process, the sensitivity of ignition changes with the operating point. Thus, gain scheduling is required to cover the entire operating range of the engine. Controller tuning can therefore be a time-intensive process. With the goal of reducing the time to tune the controller, we use extremum seeking (ES) to tune the parameters of various forms of combustion-timing controllers. In addition, in this paper, we demonstrate how ES can be used for the determination of an optimal combustion-timing setpoint on an experimental HCCI engine. The use of ES has the benefit of achieving both optimal setpoint (for maximizing the engine efficiency) and controller-parameter tuning tasks quickly.

This paper presents a technique to identify an affine parameter-dependent model based on a set of Linear-Time-Invariant (LTI) models that are identified in local operating points of the varying system. The systems under investigation are mechatronic systems in which the dynamic behaviour is depending on a single varying parameter. By fitting specific pole and zero loci on the poles and zeros of the local LTI models, an affine state-space model can be constructed. Since the resulting affine model is well conditioned and has a low complexity, it is suitable to be used for Linear-Parameter-Varying (LPV) control. The applicability of the presented technique is shown on an industrial pick-and-place machine with position-dependent dynamics.

We propose a method of interpolating linear time-invariant controllers with observer state feedback structure in order to generate a continuously-varying family of controllers that stabilizes a family of linear plants. Gain scheduling is a motivation for this work, and the interpolation method yields guidelines for the design of gain scheduled controllers. The scheduling method is illustrated with the design of

This paper addresses the path-following problem of steering an autonomous air vehicle along a predefined 3-D path, while tracking a desired velocity profile. The presented solution relies on the definition of a path-dependent error space to express the dynamic model of the vehicle, which exhibits a high degree of directional accuracy. The proposed methodology adopts a polytopic Linear Parameter Varying (LPV) representation with piecewise affine dependence on the parameters to accurately model the error dynamics over a wide flight-envelope. The synthesis problem is stated as a discrete-time H 2 control problem for LPV systems and solved using Linear Matrix Inequalities (LMIs). To achieve better path-following performance, a preview control technique is adopted, which amounts to introducing a feedforward term driven by future path disturbances. Implementation of the nonlinear controller is addressed within the framework of gain-scheduling control theory using the D-methodology. The effectiveness of the proposed controller is assessed in simulation using the full nonlinear model of a small-scale helicopter.

An industrial weigh belt feeder is used to transport solid materials into a manufacturing process at a constant feedrate. It exhibits nonlinear behavior because of motor friction, saturation, and quantization noise in the sensors, which makes standard autotuning methods difficult to implement. This paper proposes and experimentally demonstrates two types of fuzzy logic controllers for an industrial weigh belt feeder. The first type is a PI-like fuzzy logic controller (FLC). A gain scheduled PI-like FLC and a self-tuning PI-like FLC are presented. For the gain scheduled PI-like FLC the output scaling factor of the controller is gain scheduled with the change of setpoint. For the self-tuning PI-like FLC, the output scaling factor of the controller is modified online by an updating factor whose value is determined by a rule base with the error and change of error of the controlled variable as the inputs. A fuzzy PI controller is also presented, where the proportional and integral gains are tuned online based on fuzzy inference rules. Experimental results show the effectiveness of the proposed fuzzy logic controllers. A performance comparison of the three controllers is also given.