基于高阶观测器和干扰补偿控制的模型预测控制方法

针对状态不可测、外部干扰未知, 并且状态和输入受限的离散时间线性系统, 将高阶观测器、干扰补偿控制与标准模型预测控制(Model predictive control, MPC)相结合, 提出了一种新的MPC方法. 首先利用高阶观测器同步观测未知状态和干扰, 使得观测误差一致有界收敛;然后基于该干扰估计值设计新的干扰补偿控制方法, 并将该方法与基于状态估计的标准MPC相结合, 实现上述系统的优化控制. 所提出的MPC方法克服了利用现有MPC方法求解具有外部干扰和状态约束的优化控制问题时存在无可行解的局限, 能够保证系统状态在每一时刻都满足约束条件, 并且使系统的输出响应接近采用标准MPC方法控制线性标称系统时得到的输出响应. 最后, 将所提控制方法应用到船舶航向控制系统中, 仿真结果表明了所提方法的有效性和优越性.

Model Predict Control Method Based on Higher-order Observer and Disturbance Compensation Control

By combining a higher-order observer with disturbance compensation control and standard model predictive control (MPC), a novel MPC method is proposed for a discrete-time linear system with unmeasurable states, unknown external disturbances and constraints of states and inputs. Firstly, a higher-order observer is used to simultaneously observe unknown states and disturbances, such that the observation errors are uniformly bounded. Then a new disturbance compensation control method is designed based on the disturbance estimation, and the proposed method is obtained by combining the disturbance compensation control with the standard MPC based on the state estimation. The proposed method overcomes the limitation that there is no feasible solution when using the existing MPC methods to solve the optimization control problem with external disturbances and state constraints, which can also assure the system states satisfying their constraint conditions at each time instant, and make the output responses of the system close to those of the linear nominal system controlled by the standard MPC method. Finally, the proposed control method is applied to a ship heading control system, and the simulation results show its effectiveness and superiority.