Papers by Seyed Alireza Moezi
This research is presented to control a PUMA 560 robot which is well-known industrial robot with... more This research is presented to control a PUMA 560 robot which is well-known industrial robot with six degrees of freedom. It is a RRRRRR robot type which can do various tasks such as point welding in automotive industry and similar industries. The mathematical model is derived from dynamical equations by the means of Euler-Lagrange method. Stochastic feedback linearization with Kalman filter controller is implemented to control the PUMA 560 robot end effector.The regulation and
tracking results are represented. The controller is examined in normal situation and even in presence of disturbances. Finally, the results indicate good performance of the controller
The present study aims to implement an approach for trajectory control of a 3-RPR parallel manipu... more The present study aims to implement an approach for trajectory control of a 3-RPR parallel manipulator over a path with obstacles in the workspace. For this purpose, using the spline curves approach and based on the cuckoo optimization algorithm, a smooth reference trajectory with minimum length is generated in the workspace to avoid robot collision with obstacles. The performance and accuracy of the cuckoo optimization algorithm in converging to the optimal solution is then compared with the Genetic algorithm. In the next step, the robust sliding mode control technique is adopted for trajectory control of the robot in the presence of some uncertainties. These uncertainties usually include the lengths and mass of the robot’s links. The obtained results confirm the demanded level of performance and accuracy of the cuckoo optimization algorithm. It is also observed that the optimal trajectory with minimum length is generated using the spline curves approach. In addition, it is concluded that based on the sliding mode control technique, the robot can follow the desired trajectory very precisely in spite of the presence of the uncertainties in length and mass of the robot's links.
Crack in any structure changes its natural frequencies. Therefore it is possible to determine the... more Crack in any structure changes its natural frequencies. Therefore it is possible to determine the location and depth of crack by measuring its natural frequency changes. In this study, the application of MCOA numerical method for open edge-crack detection in an Euler–Bernoulli cantilever beam is proposed. The crack is modeled by a torsional spring, the coefficient of which is calculated using the crack dimensions. The objective function is the weighted squares difference of the measured and calculated natural frequencies. The results of the numerical simulations and experimental tests reveal high accuracy in detecting the location and depth of the crack.
In this paper, a connecting rod was modeled and analyzed by finite element method. By
using genet... more In this paper, a connecting rod was modeled and analyzed by finite element method. By
using genetic algorithm (GA) and modified cuckoo optimization algorithm (MCOA), the material
properties and some geometrical specifications were optimized. Cost function was a combination of
weight and stress. The connecting rod was under a load of 21.8 kN which obtained 360o crank angle
at 5700 rev/min. The reduction percentages of weight in 2-D analysis were 45.47% and 50.34%
based on GA and MCOA, respectively. The reduction percentages of stress were also 1.26% and
2.20% based on GA and MCOA, respectively. The values of reduction percentages in 3-D analysis
showed the same trends.
The results showed that applying each of the algorithms was efficient. Meanwhile, the results
of MCOA were better than GA, because of the smaller number of iterations and the initial
population, which resulted in increasing the rate of convergence (i.e. decreasing computational
time) and accuracy of answers. It can be mentioned that MCOA is an efficient and reliable
algorithm and can be used as a benchmark for future works.
The scope of this paper is to present a fuzzy logic control of a class of multi-input multioutput... more The scope of this paper is to present a fuzzy logic control of a class of multi-input multioutput (MIMO) nonlinear systems called “system of ball on a sphere,” such an inherently nonlinear, unstable, and underactuated system, considered truly to be two independent ball and wheel systems around its equilibrium point. In this work, Sugeno method is investigated as a fuzzy controller method, so it works in a good state with optimization and adaptive techniques, which makes it very attractive in control problems, particularly for such nonlinear dynamic systems. The system’s dynamic is described and the equations are illustrated. The outputs are shown in different figures so as to be compared. Finally, these simulation results show the exactness of the controller’s performance.
In this study, among different algorithms that have been introduced for obtaining optimal shapes ... more In this study, among different algorithms that have been introduced for obtaining optimal shapes and structures, an advanced optimization method for distinct shapes and also non-significant ones is illustrated. In order to investigate the efficiency of the method, a specific structural member (safety belt) is analyzed. The optimization process is to optimize the member via genetic algorithm, in order to have minimum weight; meanwhile having the ability to support the loading and also sustaining the generated tension stresses under the range of the allowable limit. The main goal of the present work is to focus on the existence of an optimal shape of the member optimized by genetic algorithm, having necessary conditions of optimality for a safety belt, and stability of optimal solutions under some prescribed perturbations.
This paper is the nonlinear adaptive feedback linearization control of a class of multi-input mul... more This paper is the nonlinear adaptive feedback linearization control of a class of multi-input multi-output (MIMO) nonlinear systems called “system of ball on a sphere”, which is designed to control and operate a ball on the top of a sphere. Nowadays, Control of nonlinear systems using the feedback linearization has attracted lots of attention in the nonlinear control theory. Since in the general case, there is uncertainty with respect of these nonlinear systems parameters, Adaptive feedback linearization is employed to obtain asymptotically accurate cancellation for this inherent uncertainty The system’s dynamic is described and the equations are illustrated. The results are simulated and compared in toe directions. The outputs are shown in different figures so as to be compared. These simulation results show the exactness of the controller’s performance.
ICMEAT2012
This paper is the nonlinear adaptive feedback linearization control of a class of multi-input mul... more This paper is the nonlinear adaptive feedback linearization control of a class of multi-input multi-output (MIMO) nonlinear systems called “system of ball on a sphere”, which is designed to control and operate a ball on the top of a sphere. Nowadays, Control of nonlinear systems using the feedback linearization has attracted lots of attention in the nonlinear control theory. Since in the general case, there is uncertainty with respect of these nonlinear systems parameters, Adaptive feedback linearization is employed to obtain asymptotically accurate cancellation for this inherent uncertaintyThe system’s dynamic is described and the equations are illustrated. The results are simulated and compared in toe directions. The outputs are shown in different figures so as to be compared. These simulation results show the exactness of the controller’s performance.
National Conference on Mechanical Engineering, Islamic Azad University, Shiraz Branch, Shiraz, Iran, Feb 23, 2012
This paper presents an adaptive neural network control of a 3-D overhead gantry crane system whic... more This paper presents an adaptive neural network control of a 3-D overhead gantry crane system which uses in industry to transport heavy loads. The dynamical equation used in this paper is based on close form equations of motion, made by lagrangian and Euler-lagrangian method. To control this system, a proper control law was designed and used. In order to have an experimental condition close to the real condition, the controller is designed in the consideration of load disturbance. The Simulation results substantiate the precision and the similarity between the desired values and the regulated ones.
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Papers by Seyed Alireza Moezi
tracking results are represented. The controller is examined in normal situation and even in presence of disturbances. Finally, the results indicate good performance of the controller
using genetic algorithm (GA) and modified cuckoo optimization algorithm (MCOA), the material
properties and some geometrical specifications were optimized. Cost function was a combination of
weight and stress. The connecting rod was under a load of 21.8 kN which obtained 360o crank angle
at 5700 rev/min. The reduction percentages of weight in 2-D analysis were 45.47% and 50.34%
based on GA and MCOA, respectively. The reduction percentages of stress were also 1.26% and
2.20% based on GA and MCOA, respectively. The values of reduction percentages in 3-D analysis
showed the same trends.
The results showed that applying each of the algorithms was efficient. Meanwhile, the results
of MCOA were better than GA, because of the smaller number of iterations and the initial
population, which resulted in increasing the rate of convergence (i.e. decreasing computational
time) and accuracy of answers. It can be mentioned that MCOA is an efficient and reliable
algorithm and can be used as a benchmark for future works.
tracking results are represented. The controller is examined in normal situation and even in presence of disturbances. Finally, the results indicate good performance of the controller
using genetic algorithm (GA) and modified cuckoo optimization algorithm (MCOA), the material
properties and some geometrical specifications were optimized. Cost function was a combination of
weight and stress. The connecting rod was under a load of 21.8 kN which obtained 360o crank angle
at 5700 rev/min. The reduction percentages of weight in 2-D analysis were 45.47% and 50.34%
based on GA and MCOA, respectively. The reduction percentages of stress were also 1.26% and
2.20% based on GA and MCOA, respectively. The values of reduction percentages in 3-D analysis
showed the same trends.
The results showed that applying each of the algorithms was efficient. Meanwhile, the results
of MCOA were better than GA, because of the smaller number of iterations and the initial
population, which resulted in increasing the rate of convergence (i.e. decreasing computational
time) and accuracy of answers. It can be mentioned that MCOA is an efficient and reliable
algorithm and can be used as a benchmark for future works.