一种新的数据驱动的非线性自适应切换控制方法

针对一类非线性离散时间动态系统, 提出了一种新的非线性自适应切换控制方法. 该方法首先把非线性项分解为前一拍可测部分与未知增量和的形式, 并充分利用被控对象的大数据信息和知识, 把非线性项前一拍可测数据与未知增量都用于控制器设计, 分别设计了线性自适应控制器, 带有非线性项前一拍可测数据补偿的非线性自适应控制器以及带有非线性项未知增量估计与补偿的非线性自适应控制器. 三个自适应控制器通过切换函数和切换规则来协调控制被控对象. 既保证了闭环系统的稳定性, 同时又提高了闭环系统的性能. 分析了闭环切换系统的稳定性和收敛性. 最后, 通过水箱液位系统的物理实验, 实验结果验证了所提算法的有效性.     

具有非线性扰动的网络控制系统的鲁棒稳定化

针对一类具有随机时延和非线性扰动的网络控制系统,利用变采样周期的方法,将连续被控对象离散化,使网络控制系统建模为部分转移概率未知的非线性Markov跳变系统.通过随机Lyapunov方法,给出保证整个闭环系统随机稳定的充分条件,同时得到非线性扰动项的最大界.仿真算例表明了所提出方法的有效性.     

变风量空调末端双闭环系统的模型辨识和仿真

研究变风量空调末端部分控制系统的节能优化问题时,对于末端系统的优化控制应以系统中被控的风阀和房间模型为基础.采用西安建筑科技大学变风量空调实验平台,对末端风阀被控对象采用闭环间接法送行辨识.利用LabView软件对外环温度控制器进行在线仿真设计,创造闭环辨识性条件,建立被控室温房间对象模型.最后,在Sumlink工具箱中用辨识模型进行末端双闭环控制系统的仿真.仿真结果表明,辨识出的模型精确度较高.用于末端节能优化控制研究中可提升控制性能,并为变风量空调节能优化控制提供了参考依据.     

非线性系统的输入多采样率模糊优化控制

基于多采样率数字控制理论,讨论了非线性连续被控对象和输入多采样率模糊控制器的设计问题.提出用线性矩阵不等式凸优化技术构建非线性系统的输入多采样率T-S模糊模型,并相应地研究了基于优化区域极点配置的PDC状态反馈控制.通过解代数Riccati方程得到控制器的参数,给出了优化数字控制器的设计算法和闭环系统的稳定性条件.计算机仿真表明了所提出方法的有效性.     

一类非线性网络控制系统的稳定性分析

网络诱导时延是影响网络控制系统稳定性和动态性能的主要因素.针对一类仿射非线性被控对象模型,利用泰勒展开进行局部线性化.考虑网络诱导时延,采用状态反馈控制器,建立基于状态反馈控制器的闭环控制系统模型.通过Lyapunov方法证明,所得最大允许时延能够保证闭环网络控制系统稳定.最后以Simulink构建一个仿射非线性被控对象模型,通过仿真证明了本文方法的正确性和有效性.     

具有传感器故障的非线性关联大系统的可靠控制

考虑一类非线性关联大系统的可靠控制器设计问题,该系统具有常时滞、参数不确定性、非线性扰动和传感器故障.其中参数不确定性满足匹配条件,非线性扰动满足范数有界条件,传感器具有部分失效的模型.本文的目的是设计无记忆分散控制器来镇定该系统.通过解线性矩阵不等式获得此控制器,使得当传感器器发生故障时被控系统能够保持渐近稳定.最后通过仿真的例子,验证该状态反馈控制器的可行性.     

二阶非线性系统自抗扰控制的全局渐近稳定性

自抗扰技术应用已十分广泛,但其稳定性和收敛性分析仍是一个核心问题.因此,基于二阶非线性动态系统,设计了线性自抗扰控制器,并利用李雅普诺夫函数方法,通过理论分析和数学证明得到了系统大范围渐近稳定时的控制参数可行域.当被控对象的动态模型已知时,只要系统总扰动的导数满足利普希茨条件,控制参数可以从得到的可行域内任意选择.当被控对象的动态模型未知时,还需满足总扰动关于输入和外扰的二阶导数等于零这个条件.然后针对不同的利普希茨常数绘制了参数可行域,并对系统进行了数值仿真,体现了自抗扰控制技术的强鲁棒性.这些分析都建立在扩张状态观测器和控制器相结合的基础上.     

非线性时变系统开闭环P型迭代学习控制的收敛性

对于非线性时变系统,给出了其开闭环P型迭代学习控制收敛的充要条件.这些收 敛条件与被控系统状态方程的具体形式无关.对比表明,该文的结论改进了现有结果.     

输入饱和下非线性系统的事件触发控制器设计

本文研究了具有输入饱和的非线性系统事件触发控制策略设计问题.首先,针对输入饱和下非线性系统,建立混杂系统模型.其次,当非线性函数满足Lipschitz条件下,给出闭环混杂系统局部一致渐近稳定性的稳定判据,并设计了事件触发饱和控制器.然后,当非线性函数满足扇区条件时,给出闭环混杂系统框架下满足局部一致渐近稳定性的LMI条件,并设计了事件触发饱和控制器.进一步地,在事件触发饱和控制器作用下,分析了非线性系统的半全局鲁棒镇定性.最后,结合两个仿真实例说明了所提出事件触发控制策略的有效性.     

具有不确定性的非线性系统自适应神经网络L2增益控制

针对存在不确定性的非线性系统,提出了自适应神经网络L2增益控制器设计方法,将基于Hamilton—Jacobi—Issacs（HJI）不等式和自适应神经网络策略相结合,有效地克服了需要被控对象精确建模的局限性．神经网络对系统模型的偏差进行拟合;为了补偿拟合误差,引入补偿控制器和神经网络权值自适应调节律,通过在线自适应修正神经网络权值,来保证闭环系统满足相应的L2性能准则．仿真结果表明提出的控制器设计方法是有效的,克服了一般方法需要被控对象精确建模的局限性．     

Semi‐Global Robust Output Regulation for A Class of Singular Nonlinear Systems with Unknown Algebraic Equations

This paper considers semi‐global robust output regulation problem for a class of singular nonlinear systems whose algebraic equations are not precisely known. Since the algebraic equations are not known, the output regulation problem of singular nonlinear systems cannot be solved by directly reducing the singular nonlinear system into a normal nonlinear system. Based on internal model principle, we convert the robust output regulation problem of singular nonlinear systems into a robust stabilization problem of an augmented singular nonlinear system. The augmented singular nonlinear system is also with unknown algebraic equations. However, without transforming the singular nonlinear system into a normal nonlinear system, it is shown that the augmented singular nonlinear system can be semi‐globally stabilized by a high gain output feedback control law under some reasonable assumptions. Moreover, the semi‐global stabilization control law of the augmented singular nonlinear systems also solves the semi‐global robust output regulation problem of the original singular nonlinear system.     

一类饱和不确定非线性系统静态抗饱和控制设计

研究一类执行器幅值与速率饱和的不确定非线性系统静态抗饱和控制问题.采用线性微分包含的方法处理系统模型中的非线性项.给出了抗饱和补偿器设计方法,该方法能同时保证闭环鲁棒稳定及鲁棒性能.给出了此类非线性系统代数环良定的充要条件,从而将抗饱和补偿器设计问题转化为线性矩阵不等式约束的凸优化问题.最后通过仿真算例说明了所提出方法的有效性.     

Static anti‐windup design for a class of nonlinear systems

This paper focuses on the problem of static anti‐windup design for a class of multivariable nonlinear systems subject to actuator saturation. The considered class regards all systems that are rational on the states or that can be conveniently represented by a rational system with algebraic constraints considering some variable changes. More precisely, a method is proposed to compute a static anti‐windup gain which ensures regional stability for the closed‐loop system assuming that a dynamic output feedback controller is previously designed to stabilize the nonlinear system. The results are based on a differential algebraic representation of rational systems. The control saturation effects are taken into account by the application of a generalized sector bound condition. From these elements, LMI‐based conditions are devised to compute an anti‐windup gain with the aim of enlarging the closed‐loop region of attraction. Several numerical examples are provided to illustrate the application of the proposed method. Copyright © 2012 John Wiley & Sons, Ltd.     

Global finite-time control for a class of switched nonlinear systems with different powers via output feedback

This paper is concerned with the problem of global finite-time control for switched nonlinear systems whose nonlinear terms satisfy homogenous growth conditions. At first, we design homogenous output feedback controllers for nominal switched nonlinear systems by adding a power integrator method. Then, we employ the homogeneous domination approach to scale homogeneous observers and controllers to render switched nonlinear systems with lower-triangular homogenous growth condition globally finite-time stable. Finally, the proposed control method can be extended to switched nonlinear systems satisfying with upper-triangular homogeneous growth condition. Two examples are provided to demonstrate the effectiveness of the proposed control scheme.     

一类确定性多变量非线性系统的自适应控制

本文研究了可用确定性多变量Hammerstein模型描述的一类多变量非线性系统的自适 应控制,基于对一步最优控制律所产生的闭环系统的稳定性条件的分析,提出了一种适用于线 性部分为具有任意关联矩阵的非最小相位系统的简单次优控制律及相应的直接自适应控制算 法,并证明了算法的全局收敛性.     

Reduction of stable differential–algebraic equation systems via projections and system identification

Most large-scale process models derived from first principles are represented by nonlinear differential–algebraic equation (DAE) systems. Since such models are often computationally too expensive for real-time control, techniques for model reduction of these systems need to be investigated. However, models of DAE type have received little attention in the literature on nonlinear model reduction. In order to address this, a new technique for reducing nonlinear DAE systems is presented in this work. This method reduces the order of the differential equations as well as the number and complexity of the algebraic equations. Additionally, the algebraic equations of the resulting system can be replaced by an explicit expression for the algebraic variables such as a feedforward neural network. This last property is important insofar as the reduced model does not require a DAE solver for its solution but system trajectories can instead be computed with regular ODE solvers. This technique is illustrated with a case study where responses of several different reduced-order models of a distillation column with 32 differential equations and 32 algebraic equations are compared.     

An output feedback precompensator for nonlinear DAE systems with control-dependent state-space

This note considers singular systems of nonlinear differential and algebraic equations (DAEs) whose constrained state space depends on the control inputs. A state-space realization of such systems cannot be derived independently of the controller design. An output feedback precompensator is derived, which results in a modified DAE system whose state-space is invariant under any feedback control law and can be used for output feedback controller synthesis. Its application is illustrated by a nonlinear electrical circuit example.     

LMI-based model predictive control for switched nonlinear systems

This paper proposes an LMI approach to model predictive control of nonlinear systems with switching between multiple modes. In this approach, at each mode, the nonlinear system is divided to a linearized model in addition to a nonlinear term. A sum of squares (SOS) optimization problem is presented to find a quadratic bound for the nonlinear part. The stability condition of the switching system is obtained by using a discrete Lyapunov function and then the sufficient state feedback control law is achieved so that guarantees the stability of the system and also minimizes an infinite prediction horizon performance index. Moreover, two other LMI optimization problems are solved at each mode in order to find the maximum area region of convergence of the nonlinear system inscribed in the region of stability. The performance and effectiveness of the proposed MPC approach are illustrated by two case studies.     

Robust state observer and control design using command-to-state mapping

In this paper, by introducing the concept of command-to-state/output mapping, it is shown that the state of an uncertain nonlinear system can robustly be estimated if command-to-state mapping of the system and that of an uncertainty-free observer converge to each other. Then, a global Jacobian system is defined to capture this convergence property for the dynamics of estimation error, and a set of general stability and convergence conditions are derived using Lyapunov direct method. It is also shown that the conditions are constructive and can be reduced to an algebraic Lyapunov matrix equation by which nonlinear feedback in the observer and its corresponding Lyapunov function can be searched in a way parallel to those of nonlinear control design. Case studies and examples are used to illustrate the proposed observer design method. Finally, observer-based control is designed for systems whose uncertainties are generated by unknown exogenous dynamics.     

非线性系统降维观测器设计

对Lipschitz非线性系统降维观测器进行了讨论.首先考虑了降维观测器存在之条件, 然后给出了此条件下的降维观测器的具体设计方法,该设计方法基于与非线性函数的Lipschitz 常数有关的代数Riccati不等式的求解.最后,针对一个具体实际控制模型的仿真,验证了文中 所提出之方法的实用性.