An adaptive Fuzzy Cerebellar Model Articulation Controller via Particle Swarm Optimization

In the paper, a Fuzzy Cerebellar Model Arithmetic Controller (FCMAC) is proposed to solve the tracking problems of a class of nonlinear systems. First, the proposed FCMAC via parameters adaptation such that it is able to approximate an ideal controller, and then a robust controller is appended to assure the system stability in the present of approximated error. Third, the redesign of the proposed FCMAC promotes the performances of the closed-loop system. Moreover, to further optimize the redesigned FCMAC, the Particle Swarm Optimization (PSO) is utilized to optimize the parameters of the proposed FCMAC under the requirements of system stability and the defined performance index. From the computer simulation results we can find that the performances of the system are promoted under the proposed control scheme.

[1]  Stanislaw H. Zak,et al.  Uniformly ultimately bounded fuzzy adaptive tracking controllers for uncertain systems , 2004, IEEE Transactions on Fuzzy Systems.

[2]  T. Jayabarathi,et al.  Particle swarm optimization for various types of economic dispatch problems , 2006 .

[3]  Pitikhate Sooraksa,et al.  Dual-line PID controller based on PSO for speed control of DC motors , 2009, 2009 9th International Symposium on Communications and Information Technology.

[4]  Rong-Jong Wai,et al.  Robust CMAC neural network control for LLCC resonant driving linear piezoelectric ceramic motor , 2003 .

[5]  J.-Y. Chen,et al.  Adaptive design of a fuzzy cerebellar model arithmetic controller neural network , 2005 .

[6]  R. Eberhart,et al.  Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[7]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[8]  A. Visioli.  Tuning of PID controllers with fuzzy logic , 2001 .

[9]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[10]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[11]  Frank L. Lewis,et al.  Optimal design of CMAC neural-network controller for robot manipulators , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[12]  Russell C. Eberhart,et al.  Comparison between Genetic Algorithms and Particle Swarm Optimization , 1998, Evolutionary Programming.

[13]  Chih-Min Lin,et al.  Adaptive CMAC-based supervisory control for uncertain nonlinear systems , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Peter Kwong-Shun Tam,et al.  A fuzzy sliding controller for nonlinear systems , 2001, IEEE Trans. Ind. Electron..

[15]  Yoshikazu Fukuyama,et al.  Practical distribution state estimation using hybrid particle swarm optimization , 2001, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[16]  Peng-Yung Woo,et al.  Neural-fuzzy control system for robotic manipulators , 2002 .

[17]  Kao-Shing Hwang,et al.  Smooth trajectory tracking of three-link robot: a self-organizing CMAC approach , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[18]  P. J. Angeline,et al.  Using selection to improve particle swarm optimization , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[19]  Yuan Zheng,et al.  Particle swarm optimization used as a control algorithm for adaptive PMD compensation , 2005, IEEE Photonics Technology Letters.

[20]  Jen-Yang Chen.  A VSS-type FCMAC controller , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[21]  Lin Chun-Shin,et al.  CMAC with General Basis Functions. , 1996, Neural networks : the official journal of the International Neural Network Society.

[22]  James S. Albus,et al.  Data Storage in the Cerebellar Model Articulation Controller (CMAC) , 1975 .

[23]  Yoshikazu Fukuyama,et al.  A particle swarm optimization for reactive power and voltage control considering voltage security assessment , 2000 .

[24]  Bin Yao,et al.  Fuzzy adaptive robust control of a class of nonlinear systems , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[25]  Antonio Visioli,et al.  Fuzzy logic based set-point weight tuning of PID controllers , 1999, IEEE Trans. Syst. Man Cybern. Part A.

[26]  James Kennedy,et al.  Defining a Standard for Particle Swarm Optimization , 2007, 2007 IEEE Swarm Intelligence Symposium.

[27]  R. Garduno-Ramirez,et al.  Multiobjective control of power plants using particle swarm optimization techniques , 2006, IEEE Transactions on Energy Conversion.

[28]  Naim A. Kheir,et al.  Control system design , 2001, Autom..

[29]  Frank L. Lewis,et al.  Control of unknown nonlinear dynamical systems using CMAC neural networks: structure, stability, and passivity , 1995, Proceedings of Tenth International Symposium on Intelligent Control.