针对存在有界扰动的非线性无人驾驶车辆避障过程中最优路径规划跟踪问题,提出一种基于预测时域内系统输入输出收缩约束(PIOCC)的模型预测控制(MPC)方法.首先在构建目标函数时,为扩大可行性解的范围引入软约束思想,将最优规划路径的跟随问题转化为对模型预测控制优化问题的求解;其次为避免短预测时域造成闭环系统发散而导致在约束条件限定下出现无可行性解的情况,采用预测时域内系统输入输出收缩约束的方法,设计模型预测控制器;再次基于Lyapunov稳定性理论证明所设计的模型预测闭环控制系统是渐近稳定的;最后通过仿真实例验证了所提出基于PIOCC的控制策略在解决扩大可行解范围和避免闭环系统发散问题时的有效性,实现了无人驾驶车辆在路径跟踪时具有良好的快速性和稳定性.

Unmanned mine vehicle driving technology is a significant part of smart mining research. This paper proposes a model predictive control strategy for the planning path trajectory tracking problem of unmanned mine vehicles during mining and transportation. Firstly, we construct an optimized function with soft constraints. Secondly, the terminal equation constraint is introduced to design model predictive control optimization problem, thereby transforming the trajectory tracking problem of the unmanned mine vehicle into the solution of the optimization problem. Then the unmanned mine vehicle trajectory tracking model predictive controller is designed, and the stability of the closed loop system through the Lyapunov stability theory is proved. Finally, a simulation example is used to verify that the terminal equation constraint model predictive controller proposed in this paper has a good tracking effect in the process of unmanned mine vehicle trajectory tracking. The control strategy proposed in this paper has improved the effect of unmanned mine vehicle planning path tracking, and its the following speed and stability are enhanced.

This paper addresses the static output feedback predictive (SOFP) control problem with cyber-physical system (CPS) subject to Denial-of-Service (DoS) attacks. The effects of DoS attacks are reasonably assumed to the bounded consecutive packet dropouts by considering the energy constraints of an attacker. Then, a novel predictive control sequence, in which only the latest successfully received output is employed, is designed to compensate such packet dropouts caused by DoS attacks. Furthermore, the stability criterion and predictive control design are carefully derived by using the switching Lyapunov functional approach and linear matrix inequality. Compared with the previous works, the proposed predictive control strategy can compensate arbitrary packet dropouts under DoS attacks while only the latest successfully received output is available. At last, a simulation example illustrates the effectiveness of the SOFP control strategy.