共查询到20条相似文献,搜索用时 15 毫秒
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终端约束区域和终端代价项在模型预测控制中起着关键的作用,针对输入受限的时滞系统,提出了终端滑模约束的模型预测控制.将满足输入约束的滑模面作为终端约束区域,使得终端约束区域扩大,有效缩短预测时域,减少计算量,有利于在线应用.最后通过仿真验证了所提方法的有效性. 相似文献
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约束非线性系统稳定经济模型预测控制 总被引:6,自引:4,他引:2
考虑约束非线性系统,提出一种新的具有稳定性保证的经济模型预测控制(Economic model predictive control,EMPC)策略.由于经济性能指标的非凸性和非正定性,引入关于经济最优平衡点的正定辅助函数.利用辅助函数的最优值函数定义原始EMPC优化问题的稳定性约束.应用终端约束集、终端代价函数和局部控制器三要素,建立闭环系统关于经济最优平衡点的渐近稳定性和渐近平均性能.进一步,结合多目标理想点概念,将提出的控制策略用于多个经济性能指标的优化控制,得到稳定多目标EMPC策略.最后,以连续搅拌反应器为例,比较仿真结果验证本文策略的有效性. 相似文献
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Squaring the circle: An algorithm for generating polyhedral invariant sets from ellipsoidal ones 总被引:2,自引:0,他引:2
This paper presents a new (geometrical) approach to the computation of polyhedral (robustly) positively invariant (PI) sets for general (possibly discontinuous) nonlinear discrete-time systems possibly affected by disturbances. Given a β-contractive ellipsoidal set , the key idea is to construct a polyhedral set that lies between the ellipsoidal sets and . A proof that the resulting polyhedral set is contractive and thus, PI, is given, and a new algorithm is developed to construct the desired polyhedral set. The problem of computing polyhedral invariant sets is formulated as a number of quadratic programming (QP) problems. The number of QP problems is guaranteed to be finite and therefore, the algorithm has finite termination. An important application of the proposed algorithm is the computation of polyhedral terminal constraint sets for model predictive control based on quadratic costs. 相似文献
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Hybrid Fuzzy Modelling for Model Predictive Control 总被引:1,自引:0,他引:1
Gorazd Karer Gašper Mušič Igor Škrjanc Borut Zupančič 《Journal of Intelligent and Robotic Systems》2007,50(3):297-319
Model predictive control (MPC) has become an important area of research and is also an approach that has been successfully
used in many industrial applications. In order to implement a MPC algorithm, a model of the process we are dealing with is
needed. Due to the complex hybrid and nonlinear nature of many industrial processes, obtaining a suitable model is often a
difficult task. In this paper a hybrid fuzzy modelling approach with a compact formulation is introduced. The hybrid system
hierarchy is explained and the Takagi–Sugeno fuzzy formulation for the hybrid fuzzy modelling purposes is presented. An efficient
method for identifying the hybrid fuzzy model is also proposed. A MPC algorithm suitable for systems with discrete inputs
is treated. The benefits of the MPC algorithm employing the hybrid fuzzy model are verified on a batch-reactor simulation
example: a comparison between the proposed modern intelligent (fuzzy) approach and a classic (linear) approach was made. It
was established that the MPC algorithm employing the proposed hybrid fuzzy model clearly outperforms the approach where a
hybrid linear model is used, which justifies the usability of the hybrid fuzzy model. The hybrid fuzzy formulation introduces
a powerful model that can faithfully represent hybrid and nonlinear dynamics of systems met in industrial practice, therefore,
this approach demonstrates a significant advantage for MPC resulting in a better control performance. 相似文献
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In this paper we consider the stabilization problem for linear continuous-time systems, under state and control constraints. We show that the largest domain of attraction to the origin can be arbitrarily closely approximated by a polyhedral domain of attraction associated to a certain (continuous) feedback stabilizing control and we show how to use existing numeric procedures for discrete-time systems to solve the continuous-time problem. We propose a new discontinuous stabilizing control law for scalar-input systems which has the advantage of being successfully applicable to systems with quantized control. 相似文献
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约束非线性系统的一个准无限时域预测控制方案 总被引:9,自引:1,他引:8
提出了一个具有准无限预测时域的模型预测控制方案,该方案可用于输入和状态的非线性系统的控制,用优化柔性状态约束条件代替了硬性状态约束,以避免优化问题的不可解,开环优化问题含有附加的终端代价项和终的约束条件,这样预测时域延伸至准无限,而需在线优化获得的控制函数仅为有限时域,如果在最初时刻优化问题有解,则闭环系统具有保证稳定性。 相似文献
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In this paper the concept of maximal admissible set (MAS) for linear systems with polytopic uncertainty is extended to non‐linear systems composed of a linear constant part followed by a non‐linear term. We characterize the maximal admissible set for the non‐linear system with unstructured uncertainty in the form of polyhedral invariant sets. A computationally efficient state‐feedback RMPC law is derived off‐line for Lipschitz non‐linear systems. The state‐feedback control law is calculated by solving a convex optimization problem within the framework of linear matrix inequalities (LMIs), which leads to guaranteeing closed‐loop robust stability. Most of the computational burdens are moved off‐line. A linear optimization problem is performed to characterize the maximal admissible set, and it is shown that an ellipsoidal invariant set is only an approximation of the true stabilizable region. This method not only remarkably extends the size of the admissible set of initial conditions but also greatly reduces the on‐line computational time. The usefulness and effectiveness of the method proposed here is verified via two simulation examples. 相似文献
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基于终端不变集的 Markov 跳变系统约束预测控制 总被引:5,自引:2,他引:3
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. 相似文献
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Ion Necoara Author Vitae Ton J.J. van den Boom Author VitaeAuthor Vitae Hans Hellendoorn Author Vitae 《Automatica》2008,44(4):971-981
Max-plus-linear (MPL) systems are a class of event-driven nonlinear dynamic systems that can be described by models that are “linear” in the max-plus algebra. In this paper we derive a solution to a finite-horizon model predictive control (MPC) problem for MPL systems where the cost is designed to provide a trade-off between minimizing the due date error and a just-in-time production. In general, MPC can deal with complex input and states constraints. However, in this paper we assume that these are not present and it is only required that the input should be a nondecreasing sequence, i.e. we consider the “unconstrained” case. Despite the fact that the controlled system is nonlinear, by employing recent results in max-plus theory we are able to provide sufficient conditions such that the MPC controller is determined analytically and moreover the stability in terms of Lyapunov and in terms of boundedness of the closed-loop system is guaranteed a priori. 相似文献
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多变量有约束过程的协调预测控制策略 总被引:5,自引:0,他引:5
针对多变量约束过程,提出了基于关联分析的协调预测控制策略,从而对系统控制性能和操作变量理想工作区起到了很好的协调作用,减少了在线控制计算工作量。 相似文献
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In this paper, a nonlinear model‐based predictive control strategy for constrained systems based on an adaptive neural network (NN) predictor is proposed. The proposed controller is robust against the model uncertainties and external bounded disturbances. Moreover, it provides offset‐free tracking behavior using the adaptive structure in the model. Based on the uncertainties bounds, the restriction of the system constraints causes robust feasibility and stability of the closed‐loop system. It is shown that the output of the NN predictor converges to the system output. Moreover, offset‐free behavior of the closed‐loop system is investigated using the Lyapunov theorem. Simulation results show the effectiveness of the proposed method as compared to the recently proposed model predictive control methods in the literature. 相似文献
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网络信息模式下分布式系统协调预测控制 总被引:6,自引:3,他引:3
工业系统中广泛存在一类由多个相互关联的子系统组成的大系统. 尽管分布式控制结构的性能没有集中式控制好,但由于其具有较高的灵活性和容错性,相对于集中控制更加适合控制上述系统.在保持容错性的情况下如何提高系统的整体性能是分布式控制的一个难点问题.本文提出了一种分布式预测控制(Distributed model predictive control, DMPC)方法,该方法通过在各子系统预测控制器的性能指标中加入输入变量对其下游子系统的影响的二次函数,来扩大分布式预测控制的协调度,进而在不增加网络连通度,不改变系统容错性的前提下,提高系统的性能.另外,本文给出了基于该协调策略的带输入约束的分布式预测控制器的设计方法,在初始可行的前提下,该方法相继可行并可保证系统渐近稳定. 相似文献
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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. 相似文献
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This paper characterises the geometric structure of receding horizon control (RHC) of linear, discrete‐time systems, subject to a quadratic performance index and linear constraints. The geometric insights so obtained are exploited to derive a closed‐form solution for the case where the total number of constraints is less than or equal to the number of degrees of freedom, represented by the number of control moves. The solution is shown to be a partition of the state space into regions for which an analytic expression is given for the corresponding control law. Both the regions and the control law are characterised in terms of the parameters of the open‐loop optimal control problem that underlies RHC and can be computed off line. The solution for the case where the total number of constraints is greater than the number of degrees of freedom is addressed via an algorithm that iteratively uses the off‐line solution and avoids on‐line optimisation. 相似文献
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Simultaneous Constrained Model Predictive Control and Identification of DARX Processes 总被引:2,自引:0,他引:2
In this work, we formulate a new approach to simultaneous constrained model predictive control and identification (MPCI). The proposed approach relies on the development of a persistent excitation (PE) criterion for processes described by DARX models. That PE criterion is used as an additional constraint in the standard on-line optimization of MPC. The resulting on-line optimization problem of MPCI is handled by successively solving a series of semi-definite programming problems. Advantages of MPCI in comparison to other closed-loop identification methods are (a) Constraints on process inputs and outputs are handled explicitly, (b) Deterioration of output regulation is kept to a minimum, while closed-loop identification is performed. The applicability of the method is illustrated by a number of simulation studies. Theoretical and computational issues for further investigation are suggested. 相似文献