Generalized fuzzy cascade predictive functional control design for different types of challenging dynamics systems

Abstract

This paper introduces a generalized form of cascade predictive functional control. The inner loop includes a state feedback controller, which aims to increase damping and stabilize the system. The outer loop utilizes an output feedback controller (OFC) to track reference and reject disturbance. The gains of the proposed controller structure are obtained optimally concerning to a specified prediction horizon through the predictive functional controller (PFC) method, which is improved by a fuzzy logic controller (FLC). The designed FLC plays a trade-off role between inner loop and outer loop gains values by tuning weighting factors in the PFC approach. In this paper, the proposed solution is formulated to convert the tracking problem into a regulation problem which results in complexity reduction and lower computational cost. Moreover, based on the proposed solution, a generalized form of OFC is obtained concerning to disturbance and reference characteristics. As a comparative study, the proposed controller is applied to the different types of challenging dynamics systems and compared to the discrete-time linear quadratic regulator (DLQR) control technique to reveal the benefits and reliable performance of the proposed control structure.

Off‐policy reinforcement learning algorithm for robust optimal control of uncertain nonlinear systems

“…Nevertheless, the factors $$$ Q(x) $$$ and $$$ R(x) $$$ in value function can be designed using various methods, like employing a fuzzy inference system, to attain a desirable performance for the closed‐loop system. Interested readers are referred to Reference 40.…”