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.

重型车辆的侧倾稳定性损失是严重的道路安全问题，现代智能重型车辆（IHV）对先进的侧倾稳定性控制技术提出了新的要求。本文提出并研究了两种新颖的侧倾稳定性控制框架，即主动转向-主动防侧倾（AS-AAR）交互控制和最坏情况优化鲁棒控制，它们在保证 IHV 侧倾稳定性方面具有潜在的应用价值。第一个控制框架是基于纳什动态博弈理论实现的，其中 AS-AAR 共享控制被研究为动态差异博弈，以便其两个参与者，即 AS 和 AAR 系统可以相互交互以提供令人满意的控制性能。这种交互控制方案可以应用于车辆自动驾驶场景，以提高车辆跟踪性能和侧倾稳定性。基于零和博弈理论，还开发了第二种最坏情况优化鲁棒控制方案，以保证车辆侧倾稳定性。该控制方法提供了一个合适的设计框架，以保证 IHV 车辆到驾驶员切换场景中的侧倾稳定性，其中人类驾驶员的转向输入被视为不确定干扰。仿真结果表明，两种控制框架都可以有效提高侧倾稳定性和横向稳定性，同时保证满意的跟踪性能。该控制方法提供了一个合适的设计框架，以保证 IHV 车辆到驾驶员切换场景中的侧倾稳定性，其中人类驾驶员的转向输入被视为不确定干扰。仿真结果表明，两种控制框架都可以有效提高侧倾稳定性和横向稳定性，同时保证满意的跟踪性能。该控制方法提供了一个合适的设计框架，以保证 IHV 车辆到驾驶员切换场景中的侧倾稳定性，其中人类驾驶员的转向输入被视为不确定干扰。仿真结果表明，两种控制框架都可以有效提高侧倾稳定性和横向稳定性，同时保证满意的跟踪性能。