模型预测控制的一个主要优点是能显式并优化处理控制量和状态量的约束。为此，主要围绕非线性预测控制的算法、稳定性和鲁棒性、对偶问题和滚动时域估计的最新研究成果进行综述，并阐述了理论与应用方面有待进一步研究的几个主要问题。

We present in this paper a novel nonlinear model predictive control scheme that guarantees asymptotic closedloop stability. The scheme can be applied to both stable and unstable systems with input constraints. The objective functional to be minimized consists of an integral square error (ISE) part over a finite time horizon plus a quadratic terminal cost. The terminal state penalty matrix of the terminal cost term has to be chosen as the solution of an appropriate Lyapunov equation. Furthermore, the setup includes a terminal inequality constraint that forces the states at the end of the finite prediction horizon to lie within a prescribed terminal region. If the Jacobian linearization of the nonlinear system to be controlled is stabilizable, we prove that feasibility of the open-loop optimal control problem at time t=0 implies asymptotic stability of the closed-loop system. The size of the region of attraction is only restricted by the requirement for feasibility of the optimization problem due to the input and terminal inequality constraints and is thus maximal in some sense.

This paper suggests a constrained H∞ control scheme for active suspensions with output and control constraints. The H∞ performance is used to measure ride comfort so that more general road disturbances can be considered. Time-domain constraints, representing requirements for: 1) good road holding which may have an impact on safety; 2) suspension stroke limitation; and 3) avoidance of actuator saturation, are captured using the concept of reachable sets and state-space ellipsoids. The proposed approach can potentially achieve the best possible ride comfort by allowing constrained variables free as long as they remain within given bounds. A state feedback solution to the constrained H∞ active suspension control problem is derived in the framework of linear matrix inequality (LMI) optimization and multiobjective control. Analysis and simulation results for a two-degree-of-freedom (2-DOF) quarter-car model show possible improvements on ride comfort, while respecting time-domain hard constraints.

将准无限时域非线性预测控制方法推广到更一般的情况，并给出了闭环约束系统的稳定性条件及最优解的存在条件。基于反馈线性化技术讨论了广义准无限时域非线性预测控制的实现及较大终端域的获取。该方法能显著减少在线优化所需的时间。