Uncertain nonlinear system control using hybrid fuzzy LQR-sliding mode technique optimized with evolutionary algorithm

Abstract

Purpose

This paper aims to propose an advanced tracking control of the uncertain nonlinear dynamic system using a novel hybrid fuzzy linear quadratic regulator (LQR)-proportional-integral-derivative (PID) sliding mode control (SMC) optimized by differential evolution (DE) algorithm.

Design/methodology/approach

First, a swing-up and balancing control is presented for an experimental uncertain nonlinear Pendubot system perturbed with friction. The DE-based optimal SMC scheme is used to optimally swing up the Pendubot system to the top equilibrium position. Then the novel hybrid fuzzy-based on LQR fusion function and PID controller optimized by DE algorithm is innovatively applied for balancing and control the position of the first link of the Pendubot in the down-right position with tracking sinusoidal signal reference.

Findings

Experimental results demonstrate the robustness and effectiveness of the proposed approach in balancing control for an uncertain nonlinear Pendubot system perturbed with internal friction.

Originality/value

This manuscript is an original research paper and has never been submitted to any other journal.

Citation

Son, N.N., Kien, C.V. and Anh, H.P.H. (2019), "Uncertain nonlinear system control using hybrid fuzzy LQR-sliding mode technique optimized with evolutionary algorithm", Engineering Computations, Vol. 36 No. 6, pp. 1893-1912. https://doi.org/10.1108/EC-08-2018-0356