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基于混合逻辑动态的混杂系统研究及应用 总被引：3，自引：0，他引：3
综述了一种在工业领域中使用的混杂系统建模方法,即基于混合逻辑动态MLD（Mixed Logic Dynamic）的建模方法。分析了在该建模框架下系统的可观性、可控性、形式验证、稳定性、状态估计及故障检测、最优控制和预测控制,并且以水电厂为例讨论了该方法在实际工程中的应用。基于MLD的混杂系统研究目前仍处于起步阶段,在理论上混杂系统预测控制、最优控制、多目标控制及混合整数二次规划求解都有待研究,在应用上如何根据不同问题有效地建模混杂系统也有待研究。 相似文献
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This paper investigates stability analysis for piecewise affine (PWA) systems and specifically contributes a new robust model predictive control strategy for PWA systems in the presence of constraints on the states and inputs and with l2 or norm‐bounded disturbances. The proposed controller is based on piecewise quadratic Lyapunov functions. The problem of minimization of the cost function for model predictive control design is changed to minimization of the worst case of the cost function. Then, this objective is reduced to minimization of a supremum of the cost function subject to a terminal inequality by considering the induced l2‐norm. Finally, the predictive controller design problem is turned into a linear matrix inequality feasibility exercise with constraints on the input signal and state variables. It is shown that the closed‐loop system is asymptotically stable with guaranteed robust performance. The validity of the proposed method is verified through 3 well‐known examples of PWA systems. Simulation results are provided to show good convergence properties along with capability of the proposed controller to reject disturbances. 相似文献
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针对城市交通网络主干道车流量密度非连续特性,分析了交通网络车流量分段仿射模型.从最小化车流量延迟角度,给出了优化目标函数并进行凸分析.在此基础上,将城市交通网络系统描述为非完整性约束条件的非线性动态系统,利用反步法通过控制变量代换和状态转换将该系统转化为时变可控协同标准型的一般形式,并设计城市交通网络系统的分布式协同控制律.然后在城市主干道交通网络模型中,分别对协同分布式优化方法、定时控制、感应控制三种交通控制算法进行对比仿真分析,从仿真结果可以看出,本文所提出的协同分布式优化方法具有较好的性能,有效的降低了交通网络中车辆平均等待时间. 相似文献
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The paper presents a methodology for the construction of an explicit nonlinear control law via approximation of the nonlinear constrained finite‐time optimal control (CFTOC). This is achieved through an approximate mapping of a general nonlinear system in a set of linear piecewise affine (PWA) systems. The key advantages of this methodology are two‐fold. First, the construction of an analytic solution of the CFTOC problem leads to an efficient explicit implementation. Second, by taking advantage of model predictive control's systematic fashion to handle constraints, an improved performance can be obtained for the closed‐loop system. The proposed theory is applied in real‐time for a system with fast dynamics: a magnetic levitation benchmark. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society 相似文献
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Switching linear models can be used to represent the behavior of hybrid, time‐varying, and nonlinear systems, while generally providing a satisfactory trade‐off between accuracy and complexity. Although several control design techniques are available for such models, the effect of modeling errors on the closed‐loop performance has not been formally evaluated yet. In this paper, a data‐driven synthesis scheme is thus introduced to design optimal switching controllers directly from data, without needing a model of the plant. In particular, the theory will be developed for piecewise affine controllers, which have proven to be effective in many real‐world engineering applications. The performance of the proposed approach is illustrated on some benchmark simulation case studies. 相似文献
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Hongwen Zhang Kai Liu Shangmin Zhang Hong Qiao Bobo Qiu 《Asian journal of control》2017,19(6):2232-2239
This paper considers the adaptive control problem for piecewise affine systems (PWS), a novel synthesis framework is presented based on the piecewise quadratic Lyapunov function (PQLF) instead of the common quadratic Lyapunov function to achieve the less conservatism. First, by designing the projection‐type piecewise adaptive law, the problem of the adaptive control of PWS can be reduced to the control problem of augmented piecewise systems. Then, we construct the piecewise affine control law for augmented piecewise systems in such a way that the PQLF can be employed to establish the stability and performance. In particular, the Reciprocal Projection Lemma is employed to formulate the synthesis condition as linear matrix inequalities (LMIs), which enables the proposed PQLF approach to be numerically solvable. Finally, an engineering example is shown to illustrate the synthesis results. 相似文献
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Decreasing‐horizon Robust Model Predictive Control With Specified Settling Time To A Terminal Constraint Set 
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下载免费PDF全文 Robust model predictive control for discrete‐time linear systems with norm‐bounded disturbances is investigated in this paper. The control objective is to steer the system state to a terminal constraint set within specified number of steps. Meanwhile, the performance of the closed‐loop control system is optimized. A decreasing‐horizon predictive control strategy is proposed. Moreover, affine state‐feedback control laws with memory of prior states are adopted over the prediction horizon. To optimize the system performance, an ‐type cost function is considered in this paper. It is shown that finite settling time is achieved, if the optimization problem in the proposed control strategy is initially solvable. Some simulations are presented to show the effectiveness of the proposed control strategy. 相似文献
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In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model’s improvements is to reflect the societal feedback on the disease and confinement features. The SEIR model parameters are allowed to be time-varying, and the ranges of their values are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. The identified model is then applied to predict the SARS-CoV-2 virus propagation under various conditions of confinement. For this purpose, an interval predictor is designed, allowing variations and uncertainties in the model parameters to be taken into account. The code and the utilized data are available on Github. 相似文献
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The problem of robust adaptive predictive control for a class of discrete-time nonlinear systems is considered. First, a parameter estimation technique, based on an uncertainty set estimation, is formulated. This technique is able to provide robust performance for nonlinear systems subject to exogenous variables. Second, an adaptive MPC is developed to use the uncertainty estimation in a framework of min–max robust control. A Lipschitz-based approach, which provides a conservative approximation for the min–max problem, is used to solve the control problem, retaining the computational complexity of nominal MPC formulations and the robustness of the min–max approach. Finally, the set-based estimation algorithm and the robust predictive controller are successfully applied in two case studies. The first one is the control of anonisothermal CSTR governed by the van de Vusse reaction. Concentration and temperature regulation is considered with the simultaneous estimation of the frequency (or pre-exponential) factors of the Arrhenius equation. In the second example, a biomedical model for chemotherapy control is simulated using control actions provided by the proposed algorithm. The methods for estimation and control were tested using different disturbances scenarios. 相似文献
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The main contribution of this paper is to propose a convex formulation of sufficient conditions for both stability analysis and synthesis of stabilizing controllers for stochastic piecewise affine (PWA) systems with multiplicative noise. One of the main difficulties in PWA systems is the fact that the affine terms in the dynamics make it extremely difficult to formulate the synthesis problem as a convex optimization or even convex feasibility program. The presence of multiplicative noise modeled as a Wiener process adds an additional level of difficulty to the analysis and synthesis procedures. Sufficient conditions for stability of stochastic PWA slab systems in the mean square sense are developed first using a stochastic globally quadratic Lyapunov function. Second, PWA state feedback controllers are designed such that the closed‐loop system is stochastically exponentially mean square stable. The conditions for both stability and stabilization are formulated as LMIs, which can then be solved efficiently using currently available software packages. A numerical example shows the effectiveness of the approach. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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本文介绍了简化模型预测控制算法ＳＭ－ＰＣ，指出ＳＭＰＣ算法是作为克服内部模型控制（ＩＭＣ）因式分解中求取过程传函逆阵费时等缺点而推出的一种简化算法。将本算法通过对一个多侧线精馏塔进行仿真，结果表明此算法具有良好的控制效果 相似文献
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Pascal Grieder Author Vitae Michal Kvasnica Author VitaeAuthor Vitae Manfred Morari Author Vitae 《Automatica》2005,41(10):1683-1694
Piecewise affine (PWA) systems are powerful models for describing both non-linear and hybrid systems. One of the key problems in controlling these systems is the inherent computational complexity of controller synthesis and analysis, especially if constraints on states and inputs are present. In addition, few results are available which address the issue of computing stabilizing controllers for PWA systems without placing constraints on the location of the origin.This paper first introduces a method to obtain stability guarantees for receding horizon control of discrete-time PWA systems. Based on this result, two algorithms which provide low complexity state feedback controllers are introduced. Specifically, we demonstrate how multi-parametric programming can be used to obtain minimum-time controllers, i.e., controllers which drive the state into a pre-specified target set in minimum time. In a second segment, we show how controllers of even lower complexity can be obtained by separately dealing with constraint satisfaction and stability properties. To this end, we introduce a method to compute PWA Lyapunov functions for discrete-time PWA systems via linear programming. Finally, we report results of an extensive case study which justify our claims of complexity reduction. 相似文献
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This article addresses finite‐horizon robust control of a piecewise affine system affected by uncertainty and characterized by different affine dynamics (modes) associated with a polyhedral partition of the state space. The goal is to design a static state‐feedback control law that maintains the state of the system within given—possibly time‐varying—sets, subject to actuation constraints. The proposed approach rests on two phases: a reference mode sequence with a sufficiently large robustness level is determined first, and then a tracking state‐feedback control law defined on the reach sets of the controlled system is designed to counteract uncertainty and maintain the reach sets within the reference sequence. If this is not possible and the reach sets split over different modes, then, further reference mode sequences and tracking controllers are computed. The designed state‐feedback control law is represented through a collection of controllers defined on precomputed reach sets of the closed‐loop control system. Performance of the approach is shown on some numerical examples. 相似文献
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《Journal of Process Control》2014,24(8):1237-1246
In this paper, we develop a tube-based economic MPC framework for nonlinear systems subject to unknown but bounded disturbances. Instead of simply transferring the design procedure of tube-based stabilizing MPC to an economic MPC framework, we rather propose to consider the influence of the disturbance explicitly within the design of the MPC controller, which can lead to an improved closed-loop average performance. This will be done by using a specifically defined integral stage cost, which is the key feature of our proposed robust economic MPC algorithm. Furthermore, we show that the algorithm enjoys similar properties as a nominal economic MPC algorithm (i.e., without disturbances), in particular with respect to bounds on the asymptotic average performance of the resulting closed-loop system, as well as stability and optimal steady-state operation. 相似文献