Whale-optimized fuzzy-fractional order controller-based automobile suspension model

Abstract

The functionality of the Active Suspension System (ASS) concerning stability and ride quality offers scope in modelling and simulation of automobile active suspension model. This work explores the design and simulation of a five degree of freedom ASS based driver integrated half car model (i.e.) Active Half Car Driver (AHCD) model. A novel design approach which assesses the Fuzzy-Fractional Order PID (FFOPID) controller parameters using bio inspired Whale Optimization Algorithm (WOA) is presented. The WOA is employed to manipulate the parameters of FFOPID controller and its efficacy is investigated using a comparative study against the performance of FOPID, FFOPID and Particle Swarm Optimization (PSO) technique tuned FFOPID (PSO-FFOPID) controllers over a single bump and a random road. The ACHD model is also analyzed under different speed levels which discloses performance adaptability of the proposed WOA-FFOPID controller. The Frequency Weighted Root Mean Square and Vibration dose value as per ISO 2631-1 standards are calculated and the results thus acquired are compared comprehensively and are analyzed which confirms that the WOA-FFOPID centered AHCD model provides the best ride comfort by reducing the driver body vibration in vertical motion.

KEYWORDS:

• Bio-inspired whale optimization algorithm
• active suspension system
• half-car driver model
• fuzzy-fractional order PID
• fractional order PID

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Council for Scientific and Industrial Research, India [grant number 09/468/0531/2019/EMR-I].