Intelligent optimal control for the crawler vehicle with semi-active suspension using modified staged continuous tabu search algorithm

Abstract

This paper proposes a novel intelligent optimal control strategy for crawler vehicles with semi-active suspension. The proposed control strategy aims at improving vehicle ride comfort by addressing contradictory suspension properties requirements of ride comfort and handling stability simultaneously. After establishing seven degrees of freedom dynamic model of the crawler vehicle, a comprehensive evaluation index is developed to trade off among various vehicle performances, which include ride comfort, damper thermal reliability, elastic element fatigue and handling stability. Then, using modified staged continuous tabu search (MSCTS) algorithm, the optimal control efforts of semi-active suspension, damping ratios, are determined by minimizing the cost function defined by the comprehensive evaluation index. Demonstrated by simulations with triangle convex block and random ground roughness excitations, MSCTS control strategy can successfully improve ride comfort performance and achieve the optimal comprehensive performance as well.