LMI-based stability and performance conditions for continuous-time nonlinear systems in Takagi-Sugeno's form.

This correspondence presents the stability analysis and performance design of the continuous-time fuzzy-model-based control systems. The idea of the nonparallel-distributed-compensation (non-PDC) control laws is extended to the continuous-time fuzzy-model-based control systems. A nonlinear controller with non-PDC control laws is proposed to stabilize the continuous-time nonlinear systems in Takagi-Sugeno's form. To produce the stability-analysis result, a parameter-dependent Lyapunov function (PDLF) is employed. However, two difficulties are usually encountered: 1) the time-derivative terms produced by the PDLF will complicate the stability analysis and 2) the stability conditions are not in the form of linear-matrix inequalities (LMIs) that aid the design of feedback gains. To tackle the first difficulty, the time-derivative terms are represented by some weighted-sum terms in some existing approaches, which will increase the number of stability conditions significantly. In view of the second difficulty, some positive-definitive terms are added in order to cast the stability conditions into LMIs. In this correspondence, the favorable properties of the membership functions and nonlinear control laws, which allow the introduction of some free matrices, are employed to alleviate the two difficulties while retaining the favorable properties of PDLF-based approach. LMI-based stability conditions are derived to ensure the system stability. Furthermore, based on a common scalar performance index, LMI-based performance conditions are derived to guarantee the system performance. Simulation examples are given to illustrate the effectiveness of the proposed approach.     

A new approach to the discretization of continuous-time controllers

A new method for discretizing continuous-time controllers is derived, using principles of controller approximation. It focuses on the closed-loop use of the discrete-time controller. The resulting approximation criterion is a measure for stability of the control system, provides an upper bound on the sampling time for which stability can be guaranteed, and because it is based on continuous-time controller approximation it indicates the cost of discretization in terms of performance degradation. The discrete-time controller is obtained through minimization of this criterion, which can be performed with standard software used in H_∞ controller design     

Robust exponential stabilization for network-based switched control systems

It has become a common practice to employ networks in control systems for connecting controllers and sensors/actuators on controlled plants and processes. A network-based switched control system, as a special case of networked control systems, is studied. Such a system is represented with network-induced delays and packet dropout as a switched delay system. Sufficient conditions for robust exponential stability are derived for a class of switching signals with average dwell time. A stabilization design for continuous-time, linear switched plant with nonlinear perturbation under a given communication network via a hybrid state feedback controller is proposed. A hybrid controller design is network-dependent and given in terms of linear matrix inequalities.     

随机网络中的H∞输出跟踪控制研究

研究随机网络控制系统的输出跟踪问题。采用线性矩阵不等式方法,推导控制器存在的充分条件,介绍控制器的设计方法。该控制器能够保证相对于所有能量有界的外界扰动信号,随机网络控制系统的H∞性能指标小于一个定值γ。仿真实验结果表明,利用该方法设计的控制器输出误差较小。     

Stability analysis and synthesis of fuzzy singularly perturbed systems

In this paper, we investigate the stability analysis and synthesis problems for both continuous-time and discrete-time fuzzy singularly perturbed systems. For continuous-time case, both the stability analysis and synthesis can be parameterized in terms of a set of linear matrix inequalities (LMIs). For discrete-time case, only the analysis problem can be cast in LMIs, while the derived stability conditions for controller design are nonlinear matrix inequalities (NMIs). Furthermore, a two-stage algorithm based on LMI and iterative LMI (ILMI) techniques is developed to solve the resulting NMIs and the stabilizing feedback controller gains can be obtained. For both continuous-time and discrete-time cases, the reduced-control law, which is only dependent on the slow variables, is also discussed. Finally, an illustrated example based on the flexible joint inverted pendulum model is given to illustrate the design procedures.     

网络控制系统的鲁棒L1跟踪控制

将L1性能约束引入网络控制系统中,研究具有时延和不确定性的网络控制系统的模型参考输出跟踪问题。基于线性矩阵不等式方法推出了该网络控制系统的稳定性和控制器设计的充分条件,并将控制器的设计转化为一个凸优化的求解问题。所设计的控制器能够保证相对于所有峰值有界的外界扰动信号,网络控制系统具有L1性能约束水平。仿真实例证实了该设计方法的有效性。     

Feedback controller design for plants with modes and disturbances above the sampling frequency

The digital feedback controller design technique of Eitelberg (1988) could not treal closed-loop performance accurately if the continuous-time plan. had significant models and signals above the sampling frequency. Here, the above simple techinque's applicability is extended by implementing the controller with additional analogue low-pass filters, cancelled by digital ‘high-pass’ terms at or below the sampling frequency.     

Design and stabilization of sampled-data neural-network-based control systems.

This paper presents the design and stability analysis of a sampled-data neural-network-based control system. A continuous-time nonlinear plant and a sampled-data three-layer fully connected feedforward neural-network-based controller are connected in a closed loop to perform the control task. Stability conditions will be derived to guarantee the closed-loop system stability. Linear-matrix-inequality- and genetic-algorithm-based approaches will be employed to obtain the largest sampling period and the connection weights of the neural network subject to the considerations of the system stability and performance. An application example will be given to illustrate the design procedure and effectiveness of the proposed approach.     

Hybrid state-space fuzzy model-based controller with dual-ratesampling for digital control of chaotic systems

We develop a hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems. A Takagi-Sugeno (TS) fuzzy model is used to model the chaotic dynamic system and the extended parallel-distributed compensation technique is proposed and formulated for designing the fuzzy model-based controller under stability conditions. The optimal regional-pole assignment technique is also adopted in the design of the local feedback controllers for the multiple TS linear state-space models. The proposed design procedure is as follows: an equivalent fast-rate discrete-time state-space model of the continuous-time system is first constructed by using fuzzy inference systems. To obtain the continuous-time optimal state-feedback gains, the constructed discrete-time fuzzy system is then converted into a continuous-time system. The developed optimal continuous-time control law is finally converted into an equivalent slow-rate digital control law using the proposed intelligent digital redesign method. The main contribution of the paper is the development of a systematic and effective framework for fuzzy model-based controller design with dual-rate sampling for digital control of complex such as chaotic systems. The effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic Chua circuit     

随机不确定网络控制系统的L_2-L_∞输出跟踪控制

本文研究了一类具有时延和凸多面体不确定性的随机网络控制系统的模型参考输出跟踪问题。基于线性矩阵不等式方法推出了该随机网络控制系统的稳定性和控制器设计的充分条件,并将控制器的设计转化为一个凸优化的求解问题。所设计的控制器能够保证相对于所有能量有界的外界扰动信号,随机网络控制系统的L2-L∞性能指标小于一定值γ。仿真实例证实了该设计方法的有效性。     

Preservation of input-to-state stability under sampling and emulation: multi-rate case

The stabilization problem of sampled-data non-linear systems is considered under the low measurement rate constraint. A multi-rate control scheme is proposed that utilizes a numerical integration scheme to approximately predict the current state. We show that if we design a continuous-time controller for a continuous-time plant so that the closed-loop continuous-time system is input-to-state stable and then discretize the controller and implement it using sample and zero order hold devices, then input-to-state stability property will be preserved for the sampled-data multi-rate closed loop system in a practical sense.     

Robust fuzzy controller design of nonlinear dynamic systems based on H ∞ optimal criterion

A new design method of fuzzy controllers to achieve H X optimal performance for a class of uncertain nonlinear systems is presented. The dynamic behaviour of a product-sum-type fuzzy controller is analysed and the result reveals that this type of fuzzy controller behaves approximately like a state feedback controller with non-constant feedback gains which are dependent on input signals. Based on the H X control design technique, a systematic analysis and design of the fuzzy controller is presented for guaranteeing the stability or even the performance. Even though the bound of the plant nonlinearity is unknown, the influence of the nonlinear term on the system error is attenuated to a prescribed level by the proposed fuzzy controller. Finally, the fuzzy controller is applied to the Duffing forced oscillation system, which confirms the validity of the controller.     

Distributed cooperative stabilisation of continuous-time uncertain nonlinear multi-agent systems

This paper addresses the distributed cooperative stabilisation problem of continuous-time uncertain nonlinear multi-agent systems. By approximating the uncertain dynamics using neural networks, a distributed adaptive cooperative controller, based on the state information of the neighbouring agents, is proposed. The control design is developed for any undirected connected communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case. An observer-based distributed cooperative controller is devised and a parameter dependent Riccati inequality is employed to prove stability of the overall multi-agent systems. This design is less complex than the other design methods and has a favourable decouple property between the observer design and the controller design for uncertain nonlinear multi-agent systems. For both cases, the developed controllers guarantee that all signals in the closed-loop network are uniformly ultimately bounded, and the states of all agents cooperatively converge to a small neighbourhood of origin. A comparative study is given to show the efficacy of the proposed method.     

网络控制系统稳定性的图理论

针对具有有界时延和数据包丢失的网络控制系统,提出了一种新的稳定性判据.基于Lyapunov方法和图论理论,给出非线性离散和连续刚络控制系统渐近稳定的充分条件,获得保持这两类系统稳定的最大允许时延界.得到控制器设计方法.并且,利用区间矩阵的谱特征.给出网络控制系统区间稳定的充分条件.设计算法,获得比例积分反馈控制器增益.算例表明所提方法的有效性.     

基于优化性能的重复控制器设计

提出一种基于优化性能的重复控制器设计方法.首先,对重复控制器中时滞环节的时延进行修正,以补偿由于低通滤波器的引入所带来的相位滞后,进而提高系统在参考/干扰信号基频处的增益,增强系统对基频信号的跟踪/抑制能力;其次,在重复控制器中加入超前校正环节,不仅拓宽了低通滤波器的带宽,而且提高了系统的高频增益,使得系统在高次谐波处的性能得以大幅提升.重复控制器的参数通过求解2个优化问题得到.在保证系统稳定的前提下,提出的设计方法最大限度地提升了系统的性能.针对光盘驱动器控制系统的仿真结果证实了该设计方法的有效性.     

Robust H-infinity control of uncertain stochastic time-delay linear repetitive processes

Repetitive processes are a distinct class of 2D systems of both theoretic and practical interest. The robust H-infinity control problem for uncertain stochastic time-delay linear continuous repetitive processes is investigated in this paper. First, sufficient conditions are proposed in terms of stochastic Lyapunov stability theory, Itˆo differential rule and linear matrix inequality technology. The corresponding controller design is then cast into a convex optimization problem. Attention is focused on constructing an admissible controller, which guarantees that the closed-loop repetitive processes are mean-square asymptotically stable and have a prespecified H-infinity performance γ with respect to all energy-bounded input signals. A numerical example illustrates the effectiveness of the proposed design scheme.     

Stability connection between sampled-data fuzzy control systems with quantization and their approximate discrete-time model

This paper concerns the stability of a sampled-data Takagi-Sugeno (T-S) fuzzy control system with quantization, when a controller design is based on an approximate discrete-time model of the plant without quantization. The motivations come from the facts that digital devices for interfacing a plant with a controller quantize signals and an exact discrete-time model of the T-S fuzzy system is generally not amenable to synthesis process. We show that the concerned system is Lagrange stabilizable by the controller asymptotically stabilizing the approximate discrete-time model. A constructive design algorithm for the developed stability analysis is proposed in terms of linear matrix inequalities.     

An uncertainty compensator for robust control of wheeled mobile robots

This paper proposes an uncertainty compensator to design a novel robust control for mobile robots with dynamic and kinematic uncertainties. A novel gradient-based adaptive fuzzy estimator is developed to compensate uncertainties with minimum required feedback signals. As a novelty, the proposed approach uses the tracking error and its first time derivative to form the estimation error of uncertainty, and guarantees that both the estimation error and tracking error converge asymmetrically to ignorable value. Advantages of the proposed robust control are simplicity in design, robustness against uncertainties, guaranteed stability, and good control performance. The control approach is verified by stability analysis. Simulation results and experimental results illustrate the effectiveness of the proposed control. Experimental evaluation of the proposed controller is expressed for two different low-cost nonholonomic wheeled mobile robots. The proposed control design is compared with an adaptive control approach to confirm the superiority of the proposed approach in terms of precision, simplicity of design, and computations.