一类含未建模动态的奇异时滞系统的鲁棒镇定问题

利用线性矩阵不等式的方法,研究了一类同时含有参数摄动和未建模动态的线性奇异时滞系统的鲁棒镇定问题.得到了系统可鲁棒镇定的一个充分条件,用线性矩阵不等式的方法,将控制器的求解问题转化为受限线性矩阵不等式的求解问题,并给出了受限线性矩阵不等式的具体解法．最后举例说明了所提出方法的正确性．     

不确定广义系统的弹性H∞保性能控制

利用线性矩阵不等式(LMI)方法,研究被控对象与控制器同时存在摄动的H∞保性能控制问题.针对控制器存在加法式摄动情形,以线性矩阵不等式约束条件给出了广义系统弹性H∞保性能的充分条件,并以线性矩阵不等式的可行解给出了相应的控制器设计方法.通过求解具有线性矩阵不等式约束的凸优化问题,给出了弹性H∞最优保性能及最优H∞性能控制器的设计方法.仿真表明了方法的可行性.     

不确定广义系统的弹性H∞保性能控制

利用线性矩阵不等式（LMI）方法，研究被控对象与控制器同时存在摄动的H∞保性能控制问题。针对控制器存在加法式摄动情形，以线性矩阵不等式约束条件给出了广义系统弹性H∞保性能的充分条件，并以线性矩阵不等式的可行解给出了相应的控制器设计方法。通过求解具有线性矩阵不等式约束的凸优化问题，给出了弹性H∞最优保性能及最优H∞性能控制器的设计方法。仿真表明了方法的可行性。     

线性随机系统有限时间H∞ 控制

讨论一类具有时变、有限能量外部扰动的线性随机系统有限时间H∞控制问题．首先,给出了线性随机系统有限时间如控制问题的定义;然后,通过构造Lyapunov-Krasovskii函数,并结合线性矩阵不等式,给出了随机系统有限时间如控制器有解的充分条件;进一步,将该问题简化为具有线性矩阵不等式约束的优化问题,并给出了相应的求解算法;最后,通过数值算例表明了该设计方法的有效性．     

非线性系统广义模糊跟踪控制

研究一种给定 H∞ 模型参考跟踪特性的非线性系统的 T-S 广义模糊跟踪控制问题. 通过把一般的模糊模型等价变换到广义模糊模型, 引入了松弛变量, 并基于线性矩阵不等式 (LMI) 给出了新的 H∞ 跟踪控制器设计方法. 控制器参数在一组线性矩阵不等式中同时得到求解, 避免了原有方法分步求解的困难, 方法简单易行且具有鲁棒性. 两个算例表明了结论的有效性.     

一类切换线性奇异系统的状态反馈H∞控制*

研究了一类由任意多个子系统组成的线性切换奇异系统的状态反馈H∞控制问题。采用共同Lyapunov函数方法和凸组合技术,给出由矩阵不等式表示的使闭环系统渐近稳定且满足H∞性能的控制器存在的充分条件, 并设计了相应的子控制器和切换策略。采用矩阵变换,将矩阵不等式等价转换为一组线性矩阵不等式。数值算例说明了所提方法的有效性和可行性。     

模糊系统H∞控制器设计的LMI方法

应用LMI(线性矩阵不等式)方法,研究了T-S模糊系统H∞控制器的设计问题.首先给出了T-S模糊系统基于状态反馈H∞控制存在的两个新的充分条件.新条件不但简洁而且把模糊子系统间的相互作用表示为由子系统的系数矩阵构成的矩阵不等式.然后新条件被转化为可直接应用Matlab求解的线性矩阵不等式.最后应用线性矩阵不等式方法和Matlab,给出了T-S模糊系统H∞控制器的设计方法.     

自适应事件触发的马尔科夫跳变多智能体系统一致性

针对非线性马尔科夫跳变多智能体系统在有向固定拓扑下的领导跟随一致性问题,为减少智能体间不必要的通信传输,节约网络资源,保证系统性能,提出一种自适应事件触发控制策略.首先,将每一个智能体均视为马尔科夫跳变系统,且马尔科夫链的转移概率部分未知;通过简单的模型转换建立误差系统,将多智能体系统一致性问题转化为误差系统的稳定性问题;在此基础上,构造合适的Lyapunov-Krasovskii泛函并利用Jensen不等式和线性矩阵不等式等技术给出使多智能体系统达到领导跟随一致性的充分条件及控制器设计方法;通过求解线性矩阵不等式可以得到多智能体系统一致性控制器增益矩阵和事件触发参数矩阵;最后,通过数值仿真验证所提出方法的有效性.     

切换时滞线性系统的状态反馈H∞控制

研究一类由任意有限个时滞线性子系统组成的切换系统的状态反馈 控制问题。利用Lyapunov函数方法和凸组合技术,给出由矩阵不等式表示的控制器存在的充分条件,设计相应的子控制器和切换规则。采用变量替代方法,将该矩阵不等式转化为一组线性矩阵不等式。给出一个求解状态反馈控制器增益矩阵的仿真算例。     

一类非线性非最小相位系统的直接自适应控制

针对一类不确定的离散时间非线性非最小相位动态系统,提出了一种基于神经网络和多模型的直接自适应控制方法．该控制方法由线性直接自适应控制器,神经网络非线性直接自适应控制器以及切换机构组成．线性控制器用来保证闭环系统输入输出信号有界,非线性控制器用来改善系统性能．切换策略通过对上述两种控制器的切换,保证闭环系统输入输出有界的同时,改善了系统性能．理论分析以及仿真结果表明了所提出的直接自适应控制方法的有效性．     

A practical multiple model adaptive strategy for single-loop MPC

This paper details a multiple model adaptive control strategy for model predictive control (MPC). To maintain performance of this linear controller over a wide range of operating levels, a multiple model adaptive control strategy for dynamic matrix control (DMC), the process industry's standard for MPC, is presented. The method of approach is to design multiple linear DMC controllers. The tuning parameters for the linear controllers are obtained using novel analytical expressions. The controller output of the adaptive DMC controller is a weighted average of the multiple linear DMC controllers. The capabilities of the multiple model adaptive strategy for DMC are investigated through computer simulations and an experimental system.     

Multivariable direct adaptive decoupling controller using multiple models and a case study

In this paper, a multivariable direct adaptive controller using multiple models without minimum phase assumption is presented to improve the transient response when the parameters of the system jump abruptly. The controller is composed of multiple fixed controller models, a free-running adaptive controller model and a re-initialized adaptive controller model. The fixed controller models are derived from the corresponding fixed system models directly. The adaptive controller models adopt the direct adaptive algorithm to reduce the design calculation. At every instant, the optimal controller is chosen out according to the switching index. The interaction of the system is viewed as the measured disturbance which is eliminated by the choice of the weighing polynomial matrix. The global convergence is obtained. Finally, several simulation examples in a wind tunnel experiment are given to show both effectiveness and practicality of the proposed method. The significance of the proposed method is that it is applicable to a non-minimum phase system, adopting direct adaptive algorithm to overcome the singularity problem during the matrix calculation and realizing decoupling control for a multivariable system. Supported by the National Natural Science Foundation of China (Grant Nos. 60504010, 60864004), the National High-Tech Research and Development Program of China (Grant No. 2008AA04Z129), the Key Project of Chinese Ministry of Education (Grant No. 208071), and the Natural Science Foundation of Jiangxi Province (Grant No. 0611006)     

Observer-based adaptive control of uncertain time-delay switched systems with stuck actuator faults

This paper concerns the observer-based adaptive control problem of uncertain time-delay switched systems with stuck actuator faults. Under the case where the original controller cannot stabilize the faulty system, multiple adaptive controllers are designed and a suitable switching logic is incorporated to ensure the closed-loop system stability and state tracking. New delay-independent sufficient conditions for asymptotic stability are obtained in terms of linear matrix inequalities based on piecewise Lyapunov stability theory. On the other hand, adaptive laws for on-line updating of some of the controller parameters are also designed to compensate the effect of stuck failures. Finally, simulation results for reference [1] model show that the design is feasible and efficient.     

基于分片线性化方法的非线性系统多模型自适应控制

基于分片线性化方法辨识一类非线性系统 ,给出了非线性系统的多线性模型表示。基于线性模型建立多个控制器 ,基于最大最小指标切换函数构成多模型自适应控制器。给出了非线性系统多模型自适应控制算法的优化模型集建立方法 ,解决了多模型自适应控制模型多、计算量大的问题。仿真结果证明了算法的有效性     

Multi-realization of nonlinear systems

The system multi-realization problem is to find a state-variable realization for a set of systems, sharing as many parameters as possible. A multi-realization can be used to efficiently implement a multi-controller architecture for multiple model adaptive control. We extend the linear multi-realization problem to nonlinear systems. The problem of minimal multi-realization of a set of MIMO systems is introduced and solved for static feedback linearizable systems.     

基于强化学习的JLQ模型的直接自适应最优控制

研究离散时间跳变线性二次(JLQ)模型的直接自适应最优控制问题.将强化学习的理论和方法应用于JLQ模型,设计基于Q函数的策略迭代算法,以优化系统性能.在系统参数以及模态跳变概率未知的情况下,Q函数对应的参数矩阵,可通过观察给定策略下系统行为,应用递归最小二乘算法在线估计.基于此参数矩阵,可构造出新的策略使得系统性能更优.该算法可收敛到最优策略.     

Robustness design of fuzzy control for nonlinear multiple time-delay large-scale systems via neural-network-based approach

The stabilization problem is considered in this correspondence for a nonlinear multiple time-delay large-scale system. First, the neural-network (NN) model is employed to approximate each subsystem. Then, a linear differential inclusion (LDI) state-space representation is established for the dynamics of each NN model. According to the LDI state-space representation, a robustness design of fuzzy control is proposed to overcome the effect of modeling errors between subsystems and NN models. Next, in terms of Lyapunov's direct method, a delay-dependent stability criterion is derived to guarantee the asymptotic stability of nonlinear multiple time-delay large-scale systems. Finally, based on this criterion and the decentralized control scheme, a set of fuzzy controllers is synthesized to stabilize the nonlinear multiple time-delay large-scale system.     

A multivariable MRAC scheme with application to a nonlinear aircraft model

This paper revisits the multivariable model reference adaptive control (MRAC) problem, by studying adaptive state feedback control for output tracking of multi-input multi-output (MIMO) systems. With such a control scheme, the plant-model matching conditions are much less restrictive than those for state tracking, while the controller has a simpler structure than that of an output feedback design. Such a control scheme is useful when the plant-model matching conditions for state tracking cannot be satisfied. A stable adaptive control scheme is developed based on LDS decomposition of the high-frequency gain matrix, which ensures closed-loop stability and asymptotic output tracking. A simulation study of a linearized lateral-directional dynamics model of a realistic nonlinear aircraft system model is conducted to demonstrate the scheme. This linear design based MRAC scheme is subsequently applied to a nonlinear aircraft system, and the results indicate that this linearization-based adaptive scheme can provide acceptable system performance for the nonlinear systems in a neighborhood of an operating point.     

Lyapunov Design of Multivariable MRAC via Generalized Passivation

A Lyapunov design of multiple input, multiple output (MIMO) model‐reference adaptive control (MRAC) systems is proposed using new generalized passivity concepts based on WSPR and WASPR properties. The new design avoids control overparameterization and leads to the simplest unnormalized gradient algorithm by means of a passivating multiplier. To this end, a necessary and sufficient condition on the high frequency gain matrix to achieve the WASPR property is established. This condition is referred to as Positive Diagonal Jordan (PDJ) form. Based on the robustness WSPR and WASPR properties, a systematic determination of a robust passivating matrix multiplier is then presented. The advantages of the new design are illustrated by numerical simulation including a robotics adaptive visual servoing problem and a 4‐input‐4‐output dynamic system. © 2014 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd     

Guaranteed cost nonlinear tracking control of a boiler-turbine unit: an LMI approach

This article addresses the problem of designing a guaranteed cost nonlinear state feedback tracking control for a boiler-turbine unit. First, the nonlinear boiler-turbine is re-expressed as a linear system with norm bounded uncertainties via a nonlinear transformation function. Then, based on this linear model a sufficient condition for the existence of a guaranteed cost nonlinear state feedback tracking control is derived in terms of linear matrix inequalities. The advantage of the proposed tracking control design is that only a simple nonlinear controller is constructed and it does not involve feedback linearisation technique and complicated adaptive or fuzzy schemes. An industrial boiler-turbine system is used to illustrate the effectiveness of the proposed design as compared with a linearised approach.