Analysis and Design for Nonlinear Networked Control Systems with Interval Time-Varying Delay

Event-triggered controller design of nonlinear discrete-time networked control systems in T-S fuzzy model

Event-triggered fault detection filter design for nonlinear networked systems via fuzzy Lyapunov functions

This paper is concerned with the problem of robust H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control of nonlinear stochastic systems with time-varying interval delay. Firstly, a novel kind of fuzzy model, stochastic fuzzy hyperbolic model (SFHM), is proposed to represent a class of nonlinear stochastic systems with time-varying interval delay. The SFHM is a overall nonlinear stochastic model, which is much fitter for the nonlinear multivariable plant whose expert knowledge is difficult to find. The identification of SFHM is more convenient than that of stochastic T-S fuzzy model. Specifically, it also can be seen as a neural network model and we can learn the model parameters by the learning method of neural network. Secondly, delay-range-dependent and delay-derivative-range-dependent criteria on stability and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance are developed for the SFHM by using new Lyapunov-Krasovskii functionals and improved free-weighting matrix technique for the SFHM case. Finally, simulation results show the validity of the proposed method.

Driven by recent telecommunication demand, shared communication channels are more abundant today than ever before. These shared wired/wireless networks for communication are being exploited more and more in control systems to connect sensors, controllers and actuators resulting in so-called networked control systems (NCSs). NCSs replace the more traditional control systems where dedicated point-to-point (wired) connections are being used. The advantages of using NCS technology are inexpensive and easily modifiable communication links which allow control algorithms to be easily implemented in situations where dedicated connections are not possible (either economically or physically). However, the drawback is that the control system is susceptible to undesirable (possibly destabilizing) side-effects such as time-varying transmission intervals, time-varying delays, packet dropouts, quantization and a shared communication medium. These network-induced effects undermine fundamental assumptions on which traditional control theory is built and, therefore, it is essential to develop new techniques and tools that can be used to analyze and/or design control systems which communicate via a shared network. This thesis advances NCS analysis and design methodologies by contributing new theoretical developments, new software tools and new experimental validation results. The first new theoretical development is in the area of analyzing robust stability properties with respect to network-induced effects. A sum of squares (SOS) approach for a class of nonlinear NCSs incorporating bounded time-varying delays, bounded time-varying transmission intervals and a shared communication medium is developed. Mathematical models that describe these nonlinear NCSs are cast into suitable hybrid system formulations. Based on these hybrid system formulations, (families of) Lyapunov functions are constructed using SOS techniques. Amongst other benefits, it is shown that this technique improves the guaranteed robustness margins compared to existing work. The second new theoretical development concerns the design of networkaware decentralized controllers guaranteeing robust stability properties with respect to network-induced effects. We develop one of the first approaches based on semidefinite programming techniques to synthesize stabilizing decentralized observer-based output-feedback controllers for linear plants where the controllers, sensors and actuators are connected via a shared communication network subject to time-varying transmission intervals and delays. To effectively deal with the shared communication medium, a switched observer structure is adopted that switches based on the transmitted measured outputs and a switched controller structure is also adopted that switches based on the transmitted control inputs at each transmission time. By taking a discrete-time switched linear system perspective on modeling these decentralized NCSs, we are able to derive a general model that captures all these networked and decentralized control aspects. We provide linear matrix inequality (LMI)-based synthesis conditions which, if satisfied, provide stabilizing observer-based controllers that are both decentralized and robust to network effects. Regarding new software tools, the first prototype of a toolbox is developed to automate (robust) stability analysis (and controller design) for NCSs. Specifically, it is shown that the toolbox can be employed to efficiently verify if a linear time-invariant (LTI) plant and an LTI controller interconnected with a shared network are robust to certain network imperfections. The main intention of the toolbox is to make the available theory readily accessible to and applicable for the general control community. Additionally, the chosen software structure enables the incorporation of custom models or custom stability/performance analysis conditions in an easy manner, thereby allowing the control community to contribute and to further develop the toolbox. Finally, an experimental case study involving a wirelessly controlled inverted pendulum/cart system is investigated. In particular, the communication network itself is analyzed such that the network-induced effects can be characterized in terms of bounds on the transmission intervals and transmission delays. Based on these bounds, the prototype toolbox is applied to analyze the robustness regions for different performance specifications, which aid in tuning the controller to achieve more closed-loop robustness with respect to the network-induced effects. This leads to a validation of the developed theory in an experimental setting. In addition to the validation of the developed theory, many new insights into the network behavior are obtained and explained, thereby raising new interesting questions for future research on NCSs.

Modeling and stabilization for a class of nonlinear networked control systems: A T-S fuzzy approach

This paper is concerned with the problem of designing a robust observer-based controller for discrete-time networked systems with limited information. An improved networked control system model is proposed and the effects of random packet dropout, time-varying delay, and quantization are considered simultaneously. Based on the obtained model, a stability criterion is developed by constructing an appropriate Lyapunov-Krasovskii functional and sufficient conditions for the existence of a dynamic quantized output feedback controller which are given in terms of linear matrix inequalities (LMIs) such that the augmented error system is stochastically stable with an performance level. An example is presented to illustrate the effectiveness of the proposed method.

This paper deals with the problem of guaranteed cost control for a class of nonlinear networked control systems (NCSs) with time‐varying delay. A guaranteed cost controller design method is proposed to achieve the desired control performance based on the switched T‐S fuzzy model. The switching mechanism is introduced to handle the uncertainties of NCSs. Based on Lyapunov functional approach, some sufficient conditions for the existence of state feedback robust guaranteed cost controller are presented. Simulation results show that the proposed method is effective to guarantee system’s global asymptotic stability and quality of service (QoS).

This chapter investigates the problem of stabilization of nonlinear discrete-time networked control systems (NCS) with event-triggering communication scheme in the presence of signal transmission delay. A Takagi–Sugeno (T–S) fuzzy model and parallel-distributed compensation (PDC) scheme are first employed to design a nonlinear fuzzy event-triggered controller for the stabilization of nonlinear discrete-time NCS. The idea of the event-triggering communication scheme (a soft computation algorithm) under consideration is that the current sensor data is transmitted only when the current sensor data and the previously transmitted one satisfy a certain state-dependent trigger condition. By taking the signal transmission delay into consideration and using delay system approach, a T–S fuzzy delay system model is established to describe the nonlinear discrete-time NCSs with event-triggering communication scheme. Attention is focused on the design of fuzzy event-triggered controller which ensures asymptotic stability of the closed-loop fuzzy systems. Linear matrix inequality- (LMI-) based conditions are formulated for the existence of admissible fuzzy event-triggered controller. If these conditions are feasible, a desired fuzzy event-triggered controller can be readily constructed. A nonlinear mass-spring-damper mechanical system is presented to demonstrate the effectiveness of the proposed method.

This paper is concerned with fuzzy-model based stability criteria of nonlinear networked control systems (NCSs) with time-varying transmission delays and transmission intervals based on an improved distributed input delay approach. The real-time distribution of input delays is modeled as an independent and nonidentically distributed (i.n.d.) process. A novel switching Takagi-Sugeno (T-S) fuzzy system with distributed input delays is proposed as the closed-loop model of the nonlinear NCSs. Appropriate Lyapunov-Krasovskii functional and integral bounding techniques are introduced to derive new delay-distribution-dependent sufficient conditions for the closed-loop exponential stability. Numerical examples are presented to substantiate the effectiveness and advantage of our results.

formula omitted] quantized control for nonlinear networked control systems

The primary objective of this study is to propose an interval type-2 controller design method for a class of nonlinear singular networked control systems encountering data-transmission delay and packet loss problems. This study assesses the stability analysis and design of the system controllers. First, the singular networked control systems are modeled as interval type-2 T-S fuzzy systems. The concept of parallel distributed compensation is then employed to design corresponding interval type-2 T-S fuzzy controllers. For system stability analysis, the stability conditions are identified using a specific Lyapunov function. The linear matrix inequalities are thus derived from the stability conditions. Furthermore, the controller gain matrices can be obtained by solving a set of appropriate linear matrix inequalities. Finally, a numerical example is used to conduct simulations and analysis. The simulation results verify the correctness of stability analysis. The performance of the proposed type-2 fuzzy controller is superior to the traditional fuzzy controller.

Network control system (NCS) is a kind of distributed control system, which is widely used in industrial control process. The communication network is used to exchange information and control signals among various physical components of subsystems. The transmission of data and information on the communication network to achieve system control will lead to the inevitable delay of information transmission time, which will reduce the performance and even make the system unstable. Reducing network traffic is one of the most effective methods to reduce the impact of network control system delay on system performance. This paper discusses the adjustable deadband as a method to reduce network traffic in networked control systems, and proposes a modeling method of networked control systems with random delay and communication constraints based on quasi T-S fuzzy model. Based on robust fault-tolerant control theory and information scheduling theory, the integrity design of this kind of networked control system is analyzed. After detailed theoretical analysis, simulation results are given to further verify the proposed scheme.

Tins paper is concerned with a class of nonlinear networked control systems with network-induced delay shorter than one sample period. Based on the assumptions that the actuator node is time-driven and the controller node is event-driven, a Takagi-Sugeno (T-S) fuzzy model is used to approximate the nonlinear networked systems with delay. By means of Lyapunov functions, a method for designing a fuzzy state feedback controller to satisfy the prescribed H/sub /spl infin// performance index is proposed. The results are presented in terms of linear matrix inequalities (LMIs) which can be solved by LMI toolbox in Matlab 6.5. Finally, a numerical example is given to validate the proposed method.

This paper studies the problem of adaptive eventtriggered dynamic output feedback fuzzy control for nonlinear networked control systems. Two crucial factors, packet dropouts and actuator failure, are taken into consideration simultaneously. Takagi-Sugeno fuzzy model is introduced to describe considered systems. The Bernoulli random distribution process is employed to depict the phenomenon of data missing. The actuator failure model is adopted to depict actuator failure. An innovative adaptive event-triggered strategy is built to save computational resource. In the light of Lyapunov stability theory, a fuzzy dynamic output feedback controller is designed to guarantee the stochastic stability and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance for considered systems. Finally, simulation results are provided to demonstrate the usefulness of the proposed control strategy.

This paper investigates non-fragile exponential H∞ control problems for a class of uncertain nonlinear networked control systems (NCSs) with randomly occurring information, such as the controller gain fluctuation and the uncertain nonlinearity, and short time-varying delay via output feedback controller. Using the nominal point technique, the NCS is converted into a novel time-varying discrete time model with norm-bounded uncertain parameters for reducing the conservativeness. Based on linear matrix inequality framework and output feedback control strategy, design methods for general and optimal non-fragile exponential H∞ controllers are presented. Meanwhile, these control laws can still be applied to linear NCSs and general fragile control NCSs while introducing random variables. Finally, three examples verify the correctness of the presented scheme.