Aerospace Engineering Commons^™

Model-Assisted Online Optimization Of Gain-Scheduled Pid Control Using Nsga-Ii Iterative Genetic Algorithm, Shen Qu, Tianyi He, Guoming Zhu

Mechanical and Aerospace Engineering Faculty Publications

In the practical control of nonlinear valve systems, PID control, as a model-free method, continues to play a crucial role thanks to its simple structure and performance-oriented tuning process. To improve the control performance, advanced gain-scheduling methods are used to schedule the PID control gains based on the operating conditions and/or tracking error. However, determining the scheduled gain is a major challenge, as PID control gains need to be determined at each operating condition. In this paper, a model-assisted online optimization method is proposed based on the modified Non-Dominated Sorting Genetic Algorithms-II (NSGA-II) to obtain the optimal gain-scheduled PID controller. …