Hybrid Strategy for Parameter Estimation and PID Tuning

Ling Wang, Da-Zhong Zheng, De-Xian Huang
2004 IFAC Proceedings Volumes  
Parameter estimation and PID tuning are two crucial issues in control engineering. Classical methods either require some prior information or depend on some rules, especially they are short of generality and their performances are not satisfied in many engineering fields. Although genetic algorithm and simulated annealing approaches have gained much attention and applications during the past decades, it may cause the premature convergence of genetic algorithm and prohibitive timeconsumption
more » ... ired for simulated annealing if executing them alone. In this paper, reasonably combining the parallel structure of genetic algorithm with the controllable jumping property of simulated annealing, a class of effective and general hybrid optimization strategy is proposed for parameter estimation and PID tuning. The proposed strategy is easy to be understood and implemented, and only a little pre-needed information is required. Numerical simulation results demonstrate that the hybrid strategy is of effectiveness, robustness on initial states, and adaptability on models or plants, and comparisons show that the hybrid strategy can achieve performances greatly better than those of pure genetic algorithm and classical methods.
doi:10.1016/s1474-6670(17)38847-x fatcat:rhloloyqebepbogcecnrul7ree