Optimal fuzzy adaptive robust PID control for an active suspension system

ABSTRACT

This work proposes an optimal fuzzy adaptive robust proportional-integral-derivative (PID) controller for a quarter-car model with an active suspension system. To this end, at first, the errors of the relative displacement and acceleration of the chassis and their integrals and derivatives are implemented to design a PID controller. Integral sliding surfaces defined based on the errors and their integrals are utilised to design the adaptation rules via the gradient descent method and the chain derivative rule. Afterwards, a fuzzy system consisted of the singleton fuzzifier, centre average defuzzifier and the product inference engine is applied to regulate the control parameters. Finally, the particle swarm optimisation (PSO) algorithm is utilised to ascertain the optimum gains of the designed controller. The body acceleration and the relative displacement between tire and sprung mass are considered as two objective functions for minimisation by the algorithm. Results show the dominance of the proposed active suspension system over previous published research works.

KEYWORDS:

• Active suspension system
• quarter-car model
• fuzzy system
• adaptive mechanism
• robust control
• PID control
• particle swarm optimisation

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

M. J. Mahmoodabadi

M. J. Mahmoodabadi received his BS and MS degrees in Mechanical Engineering from Shahid Bahonar University of Kerman, Iran in 2005 and 2007, respectively. He received his Ph.D. degree in Mechanical Engineering from the University of Guilan, Rasht, Iran in 2012. He worked for 2 years in the Iranian textile industries. During his research, he was a scholar visitor with Robotics and Mechatronics Group, University of Twente, Enchede, the Netherlands for 6 months. Now, he is an Associate Professor of Mechanical Engineering at the Sirjan University of Technology, Sirjan, Iran. His research interests include optimization algorithms, nonlinear and robust control and computational methods.

N. Nejadkourki

N. Nejadkourki was born in Sirjan, Kerman, Iran in 1994. She received her BS degree in Robotic Engineering from Sirjan University of Technology, Sirjan, Iran in 2019. Her research interests include robotics and control theory.