Interactive and Worst-Case Optimized Robust Control for Potential Application to Guaranteeing Roll Stability for Intelligent Heavy Vehicle.

Roll stability loss of heavy vehicle is a severe road safety problem and modern intelligent heavy vehicle (IHV) raises new requirement for advanced roll stability control technology. Two novel roll stability control frameworks, namely active steering-active anti-roll (AS-AAR) interactive control and worst-case optimized robust control, which have potential application to guaranteeing roll stability of IHV are proposed and investigated in this paper. The first control framework is implemented based on Nash dynamic game theory in which AS-AAR shared control is investigated as a dynamic difference game so that its two players, namely AS and AAR system, can interact with each other to provide satisfactory control performance. This interactive control scheme can be applied to vehicle automated driving scenario to improve vehicle tracking performance and roll stability. Based on zero-sum game theory, the second worst-case optimized robust control scheme is also developed to guarantee vehicle roll stability. This control method provides a suitable design framework to guarantee roll stability in scenario of vehicle-to-driver handover for IHV in which the steering input from human driver is regarded as uncertain disturbance. Simulation results show that both control frameworks can effectively improve roll stability as well as lateral stability while ensuing satisfied tracking performance. [ABSTRACT FROM AUTHOR]