基于多面体不变集的变终端约束集RMPC

针对一类状态和输入受约束的多胞不确定线性时变系统,提出了一种基于多面体不变集的变终端约束集鲁棒模型预测控制算法.首先采用基于状态反馈增益的多面体不变集计算方法,给出了一种新的控制不变集序列构造方法,然后以控制不变集序列的并集作为终端约束集,结合在线优化和增益切换,实施变终端约束集双模鲁棒预测控制.该算法不仅有效地扩大了...     

基于容许集的变终端约束MPC控制

针对一类输入和状态受约束的离散线性系统,提出一种基于Ⅳ步容许集的变终端约束集模型预测控制方法.首先给出多面体不变集序列作为终端约束集的离线模型预测控制算法,扩大了终端约束集.为进一步扩大初始状态可镇定区域,引入N步容许集,设计了基于容许集的变终端约束集模型预测控制方法.该算法采用离线设计、在线优化方法,实现了系统渐近稳定,不仅降低了在线运算量,而且扩大了初始状态可镇定区域.仿真结果表明了算法的有效性.     

基于终端不变集的 Markov 跳变系统约束预测控制

针对离散 Markov 跳变系统, 研究带输入输出约束的有限时域预测控制问题. 对于给定预测时域内的每条模态轨迹, 设计控制输入序列, 驱动系统状态到达相应的终端不变集内, 在预测时域外, 则寻求一个虚拟的状态反馈控制器以保证系统的随机稳定性, 在此基础上, 分别给出了以线性矩阵不等式 (LMI) 描述的带输入、输出约束预测控制器的设计方法.     

MPC控制器的性能监视

本文介绍了MPC控制器的一种性能指标。该指标以MPC控制器在滚动优化中预计达到的稳态目标作为评估基准,没有苛刻的假设条件,且易于现场实时获得。以Honey鄄well公司的RMPCT多变量控制器为例,就干扰、模型误差等对性能指标的影响进行了仿真实验。     

非线性预测控制终端约束集的优化

为保证预测控制的稳定性, 经典的策略是在预测控制的优化问题中加入终端约束集和终端惩罚函数, 并保证终端约束集是一个在终端控制律作用下的正不变集, 终端惩罚函数是受控系统的局部控制Lyapunov函数. 本文提供了一种求解非线性系统终端约束集、终端控制律和终端惩罚函数的新策略. 通过在优化问题中引入新的变量来降低求解终端约束条件的保守性, 并且可以从理论上保证求解得到的终端约束集更大. 通常情况下, 较大的终端约束集将允许选取的预测时域较小, 因而可以降低预测控制的在线计算负担. 从形式上看, 新的变量的引入使得终端约束集和终端惩罚项实现了某种程度的解耦, 即终端约束集不再是终端惩罚函数的水平截集. 最后通过仿真算例验证了所提策略的有效性.     

一种改进的鲁棒约束预测控制器的综合设计方法

针对多包描述的不确定系统,提出一种新的鲁棒约束预测控制器.高线设计多包系统worst-case情况下性能最优的不变集,在线求解多包系统无穷时域性能指标的rain-max优化问题.设计方法采用了时变的终端约束集,扩大了初始可行域,并能获得较优的控制性能.仿真结果验证了该方法的有效性.     

基于可达集的鲁棒模型预测控制

设计了一种基于可达集的鲁棒模型预测控制算法.首先确定了一个鲁棒不变集,并将此不变集用作模型预测控制的终端约束集;接着采用终端约束集对可达集的包含度作为优化指标;最后,采用预测时域逐渐减小的控制策略以保证在线优化存在可行解.从理论上证明了吸引域内的任意点在有限时域内都会被引导至终端约束集并始终停留在此集之内,并由仿真算例验证了本文所设计鲁棒模型预测控制算法的可行性.     

MPC8280集成的SDRAM存储控制器设计

介绍了NXP公司PowerQUICC II系列MPC8280处理器集成的SDRAM存储控制器的工作原理和工作模式,并在某国产化8280嵌入式系统开发板上,利用SDRAM存储控制器对4片SDRAM芯片进行读写操作。实际操作结果表明,该国产化8280处理器SDRAM存储控制器功能正常,可以访问SDRAM外设存储器。     

基于混合系统与终端不变集约束的混合整数规划优化控制

首先给出了混合系统的混合逻辑动态(Mixed logic dynamic, MLD)模型建模; 提出了基于终端不变集约束的混合整数规划优化控制, 通过建立Lyapunov函数证明了该方法的可行性; 利用混合整型二次规划(Mixed-integer quadratic programming, MIQP)的方法对终端不变集约束混合系统的优化控制进行求解; 最后通过一个实例进行建模、仿真, 证明了本方法的可行性与优越性.     

Exact determinations of the maximal output admissible set for a class of nonlinear systems

This paper is concerned with obtaining necessary and sufficient conditions for fulfilling specified state and control pointwise-in-time constraints against a certain class of nonlinear dynamics. The results are generalizations of the maximal output admissible set theory to the case of nonlinear systems. Main contribution of the present paper is to propose explicit algorithmic procedures to determine the maximal output admissible set. Another contribution is that we discuss on a finite determinability of the maximal output admissible set for nonlinear systems. Some relations between observability of nonlinear systems and finite characterizations of the maximal output admissible set are clarified.     

基于带缓冲网络控制系统的一种时延算法

网络控制系统中的随机时延降低系统性能。使用模型预测器可对固定时延进行补偿,但对随机时延系统稳定性降低。在执行器前加入缓冲区将随机时延转化为固定时延,最后提出一种计算缓冲区最佳等待时间的插值算法。     

Scanning and tracking with independent cameras—a biologically motivated approach based on model predictive control

This paper presents a framework for visual scanning and target tracking with a set of independent pan-tilt cameras. The approach is systematic and based on Model Predictive Control (MPC), and was inspired by our understanding of the chameleon visual system. We make use of the most advanced results in the MPC theory in order to design the scanning and tracking controllers. The scanning algorithm combines information about the environment and a model for the motion of the target to perform optimal scanning based on stochastic MPC. The target tracking controller is a switched control combining smooth pursuit and saccades. Min-Max and minimum-time MPC theory is used for the design of the tracking control laws. We make use of the observed chameleon’s behavior to guide the scanning and the tracking controller design procedures, the way they are combined together and their tuning. Finally, simulative and experimental validation of the approach on a robotic chameleon head composed of two independent Pan-Tilt cameras is presented.

Robust invariant sets for constrained storage systems

Several items are produced and stored into n buffers in order to supply an external demand without interruptions. We consider the classical problem of determining control laws and smallest buffer levels guaranteeing that an unknown bounded demand is always satisfied. A simple model with n decoupled integrators and n additive bounded disturbances is employed. The coupling arises from bounds on the total production capacity and on the total demand. Invariant set theory for linear and switched linear systems is exploited to compute robust positive invariant sets and controlled robust invariant sets for two commonly adopted scheduling policies. This paper provides the explicit expression of the invariant sets for any arbitrary n.     

Coverage and invariability by structural functions

Based on some of the results and definitions provided in the article System linkage: Structural functions and hierarchies (Lloret et al. “System linkage: structural functions and hierarchies”, Cybern. Syst. Int. J., 29, pp. 35–46, 1998) and adding new definitions that are in keeping with the spirit of the same article, new results have been obtained that explore the utility of the structural input–output function (also transferable to the other structural functions) and that expand on studies conducted to date on variables (cells).

Our approach is based principally on the application of graph theory to the study of relationships between variables (cells) using specific set theory concepts, introducing new definitions and adapting continuous function properties to our discrete environment. More specifically, we present two new concepts—coverage between sets and the invariant set—analysing their inter-relatedness from the perspective of structural functions, i.e. from the point of view of influences in the system. To date these concepts have been handled from a continuous point of view, and so the discrete approach described here will lay the foundations for new developments in this direction.

Although the development of the concepts may, a priori, appear to very theoretical, they are, in fact, much more practical than would appear to be the case. A result such as the fact that A covers B, for example, can be interpreted in terms of the latter set being formed of direct influences from elements in the former set in relation to one or more than one relationships. Analogously, the invariant set concept may be interpreted as the set maintaining its structure and status, remaining constant with respect to any possible relationships.     

On the computation of convex robust control invariant sets for nonlinear systems

In this paper we provide a method to compute robust control invariant sets for nonlinear discrete-time systems. A simple criterion to evaluate if a convex set in state space is a robust control invariant set for a nonlinear uncertain system is presented. The criterion is employed to design an algorithm for computing a polytopic robust control invariant set. The method is based on the properties of DC functions, i.e. functions which can be expressed as the difference of two convex functions. Since the elements of a wide class of nonlinear functions have DC representation or, at least, admit an arbitrarily close approximation, the method is quite general. The algorithm requires relatively low computational resources.     

Transient average constraints in economic model predictive control

In this paper, an economic model predictive control algorithm is proposed which ensures satisfaction of transient average constraints, i.e., constraints on input and state variables averaged over some finite time period. We believe that this stricter form of average constraints (compared to previously proposed asymptotic average constraints) is of independent interest in various applications such as the operation of a chemical reactor, where e.g. the amount of inflow or the heat flux during some fixed period of time must not exceed a certain value. Besides guaranteeing fulfillment of transient average constraints for the closed-loop system, we show that closed-loop average performance bounds and convergence results established in the setting of asymptotic average constraints also hold in case of transient average constraints. Furthermore, we illustrate our results with a chemical reactor example.     

Maximal controllability of input constrained unstable systems by the addition of implicit constraints

The null controllable set of a system is the largest set of states that can be controlled to the origin. Control systems that have a region of attraction equal to the null controllable set are said to be maximally controllable closed-loop systems. In the case of open-loop unstable plants with amplitude constrained control it is well known that the null controllable set does not cover the entire state-space. Further the combination of input constraints and unstable system dynamics results in a set of state constraints which we call implicit constraints. It is shown that the simple inclusion of implicit constraints in a controller formulation results in a controller that achieves maximal controllability for a class of open-loop unstable systems.