Study on Predictive Fuzzy Control of Great Inertia System Based on Grey Model

Based on the predictive fuzzy control design of grey model, this paper analyses the dynamic output response of great inertia system, and proposes a hybrid contorl method, which is combined with the adaptive regulator of grey model and fuzzy variable step method. The method overcomes the deficiency of traditional predictive PID and grey prediction control, and obtains a rapid system response index without overshoot. The simulation results shows a remarkable effect and good optimal control function to great inertia system.

[1]  I Kaya,et al.  Improving performance using cascade control and a Smith predictor. , 2001, ISA transactions.

[2]  Yang Ru-qing Novel self-adjustable grey prediction controller , 2004 .

[3]  D Vrecko,et al.  A new modified Smith predictor: the concept, design and tuning. , 2001, ISA transactions.

[4]  Hongquan Qu,et al.  Application of fuzzy control theory to direct-heating furnace control system , 2002, Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527).

[5]  Shiuh-Jer Huang,et al.  Control of an inverted pendulum using grey prediction model , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[6]  Yao Wan-ye Adaptive grey prediction PID control for time-variable large delay system , 2004 .

[7]  Jyh-Horng Chou,et al.  Application of the Taguchi-genetic method to design an optimal grey-fuzzy controller of a constant turning force system , 2000 .

[8]  Ching-Chang Wong,et al.  Design of fuzzy control systems with a switching grey prediction , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[9]  Gao Shang Improvement of GM (1, 1) model , 2007, 2007 IEEE International Conference on Grey Systems and Intelligent Services.

[10]  Youguo Pi,et al.  PID neural networks for time-delay systems , 2000 .