共查询到18条相似文献,搜索用时 171 毫秒
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一类非线性系统最大可控不变集求解 总被引:1,自引:0,他引:1
针对非线性系统线性化在状态约束下最优鲁棒控制求解问题,提出了一种基于混合系统的非线性系统最大鲁棒控制不变集的方法.对于一类非线性系统通过平衡点线性化的方法转化为多模态的混合系统,并进行了混合逻辑动态模型(MLD)的建模,在不变集基本理论的基础上,通过多参数规划的混合整数规划(MIQP)的方法迭代求解最大可控不变集,并求得不变集内的最优控制器,解决系统的状态约束问题.通过一个非线性系统的实例进行建模、仿真,证明了本方法的可行性. 相似文献
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研究空中机器人(小型无人直升机)的约束优化控制问题:对小型无人直升机的非线性系统模型进行系统约简,建立混合系统的分段仿射系统模型,针对该问题求解中遇到的在线计算量大,不利于实时控制等问题,提出利用多参数二次规划离线计算出混合系统最优控制律的方法.基于多参数二次规划的方法,在最大可控不变集的可行域内进行显式优化控制器设计,通过反向动态规划,求出对应每一步的优化解,从而求得不变集作为可行域的优化解.通过实际参数的系统仿真,证明了方法的有效性. 相似文献
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以鲁棒控制不变集作为预测控制的终端约束集,设计了一种新的鲁棒预测控制算法.将预测控制在不同采样点的待优化控制律考虑为线性反馈控制律,并通过在线优化求解线性反馈增益.从理论上证明了若采用所设计的鲁棒预测控制器,则系统是输入状态稳定的.最后通过计算机仿真验证了所提出设计方法的可行性. 相似文献
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输入状态稳定的鲁棒预测控制 总被引:1,自引:0,他引:1
以有界干扰非线性系统为研究对象,设计一种基于近似可达集的鲁棒预测控制方法。该方法以鲁棒控制不变集作为终端约束集,采用一种简单的三次多项式逼近预测控制的待优化控制律,通过在线优化求解三次多项式的各项系数,并从理论上证明了所设计的鲁棒预测控制律可以使系统输入状态稳定。最后通过仿真实例验证了所提出的鲁棒预测控制方法的可行性和有效性。 相似文献
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利用混合Petri网为混合系统建模,探讨了基于不变集混合系统在Lyapunov意义下关于恢复半径的稳定性概念,并给出利用Lyapunov函数法判定混合系统稳定性、一致稳定和渐近稳定的充分条件。 相似文献
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混合系统在matlab环境下的建模和仿真 总被引:1,自引:0,他引:1
混合系统是集连续动态系统和离散事件为一体的复杂动态系统,是近年来控制理论研究领域的热门课题.由于混合系统既含连续变量义含离散事件,给处理这类系统带来了复杂性.一般混合系统建立模方法有:混合自动机,混合petri,时段演算及其扩展等模型.在概述混合系统概念与特点的基础上,介绍了混合系统研究中的建模与仿真问题.结合超市冰柜系统用混合自动机建模,并用MATLAB中的SIMULINK和STATEFLOW进行仿真.仿真结果表明效果很好,为系统分析和设计提供了有力的工具. 相似文献
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In this study, an interval-parameter fuzzy programming mixed integer programming method (IFMIP) is designed for supporting the planning of energy systems management (ESM) and air pollution mitigation control under multiple uncertainties. The IFMIP-ESM model is based on an integration of interval-parameter programming (IPP), fuzzy programming (FP), and mixed-integer programming (MIP), which can reflect multiple uncertainties presented as both interval values and fuzzy distributions numbers. Moreover, it can successfully identify dynamics of capacity expansion schemes, reflect dual dynamics in terms of interval membership function, and analyze various emission-mitigation scenarios through incorporating energy and environmental policies. The designed model is applied to a case of energy systems management in Tangshan City, China, and the results indicate that reasonable solutions obtained from the model would be helpful for decision makers to effectively (a) adjust the allocation patterns of energy resources and transform the patterns of energy consumption and economic development, (b) facilitate the implement of air pollution control action plan, and (c) analysis dynamic interactions among system cost, energy-supply security, and environmental requirement. 相似文献
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VB与Matlab混合编程的仿真应用 总被引:4,自引:0,他引:4
介绍了Visual Basic与Matlab混合编程方法在可靠性与维修性仿真中的应用。此方法突破了以往利用单一语言实现系统可靠性与维修性仿真的限制,更广泛的利用了现有技术成果,降低了编程难度,加快了编程速度。详细介绍了Visual Basic与Matlab混合编程的方法及实现步骤。包括Matlab编译环境的设置、Matlab程序编写、Matlab COM组件的编译与发布以及如何在Visual Basic中使用Matlab COM组件。详细叙述了混合编程每个步骤实现的技术关键,为可靠性与维修性仿真解决了软件实现的技术问题。最后一部分给出了利用Visual Basic与Matlab混合编程方法进行可靠性与维修性仿真的示例。 相似文献
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In this paper, a linear programming method is proposed to solve model predictive control for a class of hybrid systems. Firstly, using the (max, +) algebra, a typical subclass of hybrid systems called max-plus-linear (MPL) systems is obtained. And then, model predictive control (MPC) framework is extended to MPL systems. In general, the nonlinear optimization approach or extended linear complementarity problem (ELCP) were applied to solve the MPL-MPC optimization problem. A new optimization method based on canonical forms for max-min-plus-scaling (MMPS) functions (using the operations maximization, minimization, addition and scalar multiplication) with linear constraints on the inputs is presented. The proposed approach consists in solving several linear programming problems and is more efficient than nonlinear optimization. The validity of the algorithm is illustrated by an example. 相似文献
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In this paper, a linear programming method is proposed to solve
model predictive control for a class of hybrid systems. Firstly,
using the (max, +) algebra, a typical subclass of hybrid systems
called max-plus-linear (MPL) systems is obtained. And then, model
predictive control (MPC) framework is extended to MPL systems. In
general, the nonlinear optimization approach or extended linear
complementarity problem (ELCP) were applied to solve the MPL-MPC
optimization problem. A new optimization method based on canonical
forms for max-min-plus-scaling (MMPS) functions (using the
operations maximization, minimization, addition and scalar
multiplication) with linear constraints on the inputs is presented.
The proposed approach consists in solving several linear programming
problems and is more efficient than nonlinear optimization. The
validity of the algorithm is illustrated by an example. 相似文献
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R.Kipp Martin Dennis J. Sweeney Michael E. Doherty 《Computers & Operations Research》1985,12(2):139-149
A different branch and bound algorithm for mixed integer programming is presented. Unlike standard linear programming based branch and bound algorithms, where a single fractional variable (or Special Ordered Set) is selected for problem separation, the proposed method selects groups of variables for separation on the basis of their reduced cost in an LP relaxation. The proposed method restricts a large portion of the integer variables to zero on one branch. The net effect is that the original integer program is solved by optimizing a series of smaller, more tightly restricted, integer programs. The authors have programmed the algorithm using the Extended Control Language of the IBM MPSX/370-MIP/370 mixed integer programming package. Computational results are presented that demonstrate the efficiency of the method on problems where the variables are partitioned into multiple choice constraints containing special ordered sets of variables. While the computational results are limited to this class of problems the algorithm can, in theory, be applied to any mixed integer programming problem. 相似文献
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Regularized multiple criteria linear programming (RMCLP) model is a new powerful method for classification and has been used in various real-life data mining problems. In this paper, a new Multi-instance Classification method based on RMCLP was proposed (called MI-RMCLP), which includes two algorithms for linearly separable case and nonlinearly case separately. The key point of this method, instead of a mixed integer quadratic programming in MI-SVM, is that it is able to deal with multi-instance learning problem by an iterative strategy solving sequential quadratic programming problems. All experiment results have shown that MI-RMCLP method can converge to the optimal value in limited iterative steps and be a competitive method in multi-instance learning classification. 相似文献