Integration of PSO and GA for optimum design of fuzzy PID controllers in a pendubot system

Artificial Life and Robotics

Volumn 13, Issue 1, 2008, Pages 223-227

  Fu, Yu Yi ^a   Wu, Chia Ju ^a   Chien, Ting Li ^b   Ko, Chia Nan ^c  

^a NATIONAL YUNLIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b WUFENG INSTITUTE OF TECHNOLOGY   (Taiwan)

^c NAN KAI UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

Fuzzy PID controllers; Genetic algorithm; Particle swarm optimization; Pendubot system

Indexed keywords

ELECTRIC CONTROL EQUIPMENT; EVOLUTIONARY ALGORITHMS; FUZZY LOGIC; GENETIC ALGORITHMS; INTEGRATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; OPTIMIZATION; PROPORTIONAL CONTROL SYSTEMS; THREE TERM CONTROL SYSTEMS; TIME VARYING CONTROL SYSTEMS; TUNING; TWO TERM CONTROL SYSTEMS;

AND GENETIC ALGORITHMS; ASYMPTOTICAL STABILITIES; ASYMPTOTICAL STABILIZATIONS; AUTO-TUNING; ERROR SIGNALS; EVOLUTIONARY LEARNINGS; FUZZY PID CONTROLLERS; INPUT VARIABLES; OPTIMUM DESIGNS; OUTPUT VARIABLES; PARTICLE SWARM OPTIMIZATION; PENDUBOT SYSTEM; PID CONTROLLERS; PID GAINS; SIMULATION RESULTS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 58049191011     PISSN: 14335298     EISSN: 16147456     Source Type: Journal    
DOI: 10.1007/s10015-008-0512-x     Document Type: Article

References (13)

1. Keel LH, Rego JI, Bhattacharyya SP (2003) A new approach to digital PID controller design. IEEE Trans on Automatic Control 48(4):687-692
2. Cervantes I, Garrido R, Jose AR, et al (2004) Vision-based PID control of planar robots. IEEE Trans on Mechatronics 9(1): 132-136
3. Whidborne JF, Istepanian RSH (2001) Genetic algorithm approach to designing finite-precision controller structures. IEE Proc of Control Theory Applications 148(5):377-382
4. Lin L, Jan HY, Shieh NC (2003) GA-based multiobjective PID control for a linear brushless dc motor. IEEE Trans on Mechatronics 8(1):56-65
5. Tao CW, Taur JS (2005) Robust fuzzy control for a plant with fuzzy linear model. IEEE Trans on Fuzzy Syst 13(1):30-41
6. Wu CJ, Liu GY, Cheng MY, et al (2002) A neural-network-based method for fuzzy parameter tuning of PID controllers. J Chin Inst Eng 25(3):265-276
7. Gaing ZL (2004) A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans Energy Conversion 19(2):384-391
8. Habib SJ, Al-kazemi BS (2005) Comparative study between the internal behavior of GA and PSO through problem-specific distance functions. The 2005 IEEE Congress on Evolutionary Computation, pp 2190-2195
9. Wang LX (1997) A Course in Fuzzy Systems and Control. Prentice-Hall, New Jersey
10. Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp 1942-1948
11. Ratnaweera A, Halgamuge SK, Watson C (2004) Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Trans Evolutionary Comput 8(3):240-255
12. Haupt RL, Haupt SE (2004) Practical Genetic Algorithms, 2nd edn. John Wiley & Sons, New York
13. Spong MW, Vidyasagar M (1989) Robot dynamics and control. Wiley, New York