A Comparative Study Between Sliding Mode and Fuzzy Sliding Mode Control for Pendubot

Abstract

The pendubot is a classical highly non-linear system that has been widely used in many laboratories to demonstrate the responses of the system when applying control algorithms, to analyse dynamical equations, and to study the parameter identification algorithms. The objective of this paper is to design the controller to stabilize the pendubot at equilibrium points (TOP and MID) and to track the defined trajectory. Firstly, mathematical equations of the pendubot are derived by the Euler‒Lagrange method. Thence, a genetic algorithm (GA) is employed to identify the parameters of the system based on the collected data of the output states of the system when applying impulse inputs. After that, sliding mode control (SMC) is designed to balance the system at the equilibrium points and track the defined trajectory. The chattering caused by SMC is reduced by fuzzy-sliding mode control (FSMC). The proposed FSMC method solves the problem induced by SMC by applying fuzzy logic. Additionally, the partial feedback linearisation (PFL) method is introduced to design the swing-up system. Finally, both simulation and experimental results are provided to show the effectiveness and robustness of the proposed methods.