PID Parameters Optimization Using Genetic Algorithm Technique for Electrohydraulic Servo Control System

Ayman A. Aly
DOI: 10.4236/ica.2011.22008                

Abstract

Electrohydraulic servosystem have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In order to increase the reliability, controllability and utilizing the superior speed of response achievable from electrohydraulic systems, further research is required to develop a control software has the ability of overcoming the problems of system nonlinearities. In This paper, a Proportional Integral Derivative (PID) controller is designed and attached to electrohydraulic servo actuator system to control its angular position. The PID parameters are optimized by the Genetic Algorithm (GA). The controller is verified on the state space model of servovalve attached to a rotary actuator by SIMULINK program. The appropriate specifications of the GA for the rotary position control of an actuator system are presented. It is found that the optimal values of the feedback gains can be obtained within 10 generations, which corresponds to about 200 experiments. A new fitness function was implemented to optimize the feedback gains and its efficiency was verified for control such nonlinear servosystem.

Keywords

Optimal Control, PID, GA, Electrohydraulic, Servosystem

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	H. E. Merrit, “Hydraulic Control Systems,” John Wiley & Sons Inc, New York, 1967.
[2]	J. Watton, “Fluid Power Systems,” Prentice Hall, New Jersey, 1989.
[3]	J. E. Bobrow and K. Lum, “Adaptive, High Bandwidth Control of a Hydraulic Actuator,” Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, Vol. 118, No. 4, 1996, pp. 714-720. doi:10.1115/1.2802347
[4]	T. L. Chern and Y. C. Wu, “Design of Integral Variable Structure Controller and Application to Electrohydraulic Velocity Servosystems,” IEEE Proceedings D, Vol. 138, No. 5, 1991, pp. 439-444.
[5]	R.-F. Fung and R.-T. Yang, “Application of Variable Structure Controller in Position Control of a Nonlinear Electrohydraulic Servo System,” Computers & Structures, Vol. 66, No. 4, 1998, pp. 365-372. doi:10.1016/S0045-7949(97)00084-9
[6]	G. Vossoughi and M. Donath, “Dynamic Feedback Linearization for Electrohydraulic Actuated Control Systems,” Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, Vol. 117, No. 3, 1995, pp. 468-477. doi:10.1115/1.2801102
[7]	A. A. Aly, “Modeling and Control of an Electro-Hydraulic Servo Motor Applying Velocity Feedback Control Strategy,” International Mechanical Engineering Conference, IMEC2004, Kuwait, 2004.
[8]	A. H. Jones and M. L. Tatnall, “Online Frequency Domain Identification for Genetic Tuning of PI Controllers,” Proceedings of ICSE, Coventry University, Coventry, 1994.
[9]	“Moog 761 Series Servovalves,” Moog Controls Inc., East Aurora.
[10]	W. Wang, J. T. Zhang and T. Y. A. Chai, “Survey of Advanced PID Parameter Tuning Methods,” Acta Automatica, Vol. 26, No. 3, 2000, pp. 347-355.
[11]	M. H. Moradi, “New Techniques for PID Controller Design,” IEEE Conference on Control Applications, Vol. 2, 2003, pp. 903-908.
[12]	A. A. Aly, “A Non Linear Optimal PID Control of a Hydraulic Crane,” Journal of Engineering Science, Vol. 33, No. 1, 2007, pp. 199-209.
[13]	K. K. Tan, S. N. Huang and T. H. Lee, “Development of a GPC-based PID Controller for Unstable Systems with Dead Time,” ISA Transactions, Vol. 39, 2000, pp. 57-70. doi:10.1016/S0019-0578(99)00036-1
[14]	P. Cominos and N. Munro, “PID Controllers: Recent Tuning Methods and Design to Specification,” IEE Proceedings Control Theory & Applications, Vol. 149, No. I, January 2002.
[15]	J. G. Ziegler and N. B. Nichols, “Optimum Settings for Automatic Controllers,” Transactions of the ASME, Vol. 64, 1942, pp. 759-768.
[16]	C. Coon, “Theoretical Consideration of Retarded Control,” Transactions of the ASME, Vol. 75, 1952, pp. 827-834.
[17]	L. Hao, C. L. Ma and F. Li, “Study of Adaptive PID Controller Based on Single Neuron and Genetic Optimization,” The 8th International Conference on Electronic Measurement and Instruments ICEMI, Vol. 1, 2007, pp. 240-243.
[18]	J. R. Koza, F. H. Bennett, A. David and K. Martin, “A Genetic Programming III: Darwinian Invention and Problem Solving,” Morgan Kaufmann, San Francisco, 1999.
[19]	J. R. Koza, M. A. Keane, M. J. Streeter, W. Mydlowec, J. Yu and G. Lanza, “Genetic Programming IV. Routine Human-Competitive Machine Intelligence,” Kluwer Academic Publishers, Dordrecht, 2003.
[20]	C. R. Reeves, “Using Genetic Algorithms with Small Populations,” Proceedings of the 5th International Conference on Genetic Algorithms, 1993.
[21]	D. E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine Learning,” Addison-Wesley, New York, 1989.