Intelligent PID Temperature Control Using Output Recurrent Fuzzy Broad Learning System for Nonlinear Time-Delay Dynamic Systems
Ali Rospawan, Ching‐Chih Tsai, Feng‐Chun Tai · 2022
This paper presents a novel adaptive predictive proportional-integral-derivative (PID) control using a new output recurrent fuzzy broad learning system (ORFBLS) for setpoint control of a class of nonlinear discrete-time dynamic systems with time delay. The proposed controller, abbreviated as ORFBLS-APPID, is composed of an ORFBLS identifier for online parameter tuning and estimation, and an adaptive predictive ORFBLS-PID control for accurate setpoint tracking and disturbance rejection. The three-term gains of the PID controller are automatically tuned by an ORFBLS. The set-point tracking of the proposed ORFBLS-APPID control method is well exemplified by conducting simulations for two well-known nonlinear discrete-time dynamic systems with time delay, thus showing its effectiveness and superiority.