T–S fuzzy-model-based piecewise [formula omitted] output feedback controller design for networked nonlinear systems with medium access constraint

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.

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

For nonlinear space-varying parabolic partial differential equation systems (PPDESs) with random time-varying delay, this article introduces a dynamic fuzzy boundary output feedback (DFBOF) control under noncollocated boundary measurement (NCBM). Initially, the nonlinear delayed PPDESs are represented by Takagi–Sugeno (T–S) fuzzy models and random time-varying delay is considered by taking the influence of uncertain factors, which belongs to two intervals in a probabilistic way. Since the system state is not fully available and NCBM makes the boundary control design very difficult, a fuzzy observer under NCBM is presented to surmount the design difficulty. Subsequently, an observer-based fuzzy boundary controller is proposed and spatial linear matrix inequality (SLMI)-based sufficient conditions to ensure mean-square exponential stability are obtained for closed-loop delayed PPDESs by utilizing the Lyapunov direct method and Wirtinger inequality. Then, to solve the SLMIs, the feasibility conditions of DFBOF controller design for nonlinear delayed PPDES are expressed in LMIs. Finally, two examples are offered to demonstrate the validity of the presented dynamic fuzzy boundary control approach.

Quantized output feedback control for nonlinear Markovian jump distributed parameter systems with unreliable communication links

In wireless sensor actuator networks, actuator nodes are very important to network coverage for wireless sensor. So according to the characteristics that wireless communication is easy to be affected by the environment, in this wireless sensor actuator network the actuator nodes are abstracted to be service providers and the sensor nodes are abstracted to be service consumers. Furthermore, the messages transferred from actuator nodes to sensor nodes are abstracted to be service requests and the coverage of sensor nodes by actuator nodes is service providing. Moreover, the service faulty ratio of actuator nodes is defined in this paper. Based on that, an actuator node coverage algorithm that satisfies the maximum request expectation is put forwarded. Its goal is to solve the mathematical expectation of maximizing the number of service requests with fixed number of sensor nodes and actuator nodes. So the optimal position of actuator nodes could be identified. The theoretic proof and simulation result show that this algorithm is more efficient compared with similar algorithms

Power efficient ultra-wideband based wireless communication for wireless body area network applications

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

This paper investigates the stabilization problem for a class of discrete‐time stochastic non‐affine nonlinear systems based on T‐S fuzzy models. Based on the function approximation capability of a class of stochastic T‐S fuzzy models, it is shown that the stabilization problem of a stochastic non‐affine nonlinear system can be solved as a robust stabilization problem of the stochastic T‐S fuzzy system with the approximation errors as the uncertainty term. By using a class of piecewise dynamic feedback fuzzy controllers and piecewise quadratic Lyapunov functions, robust semiglobal stabilization condition of the stochastic non‐affine nonlinear systems is formulated in terms of linear matrix inequalities. A simulation example illustrating the effectiveness of the proposed approach is provided in the end.

The problem of H∞ filtering design is studied for non-linear sampled-data systems using the Takagi–Sugeno (T–S) fuzzy model approach. The sampled-data filtering is to estimate the states of a continuous-time system using only sampled measurements at discrete instants of time. Traditionally, the sufficient conditions for the existence of such an H∞ filter are characterised in terms of the solution of a differential Hamilton–Jacobi inequality with jumps, which is equivalent to solving the partial differential inequality with jumps. In general, there is no analytical solution for this non-linear partial differential inequality with jumps. First, in this study, the T–S fuzzy model is proposed to represent a class of non-linear sampled-data systems. Next, by using the T–S fuzzy model, the H∞ fuzzy filtering design problem for non-linear sampled-data system is characterised in terms of a linear matrix inequality (LMI) problem. Hence, the H∞ fuzzy filter of non-linear sampled-data systems can be given via solving LMIs instead of solving a differential Hamilton–Jacobi inequality with jumps. To illustrate the results, a numerical example is included.

This paper presents the design of a state convergence (SC)-based bilateral controller for a nonlinear teleoperation system, which has been approximated by a Takagi–Sugeno (TS) fuzzy model. The selection of SC is made due to the advantages offered by this scheme both in the modeling and control design stages. The modeling stage considers master/slave systems, which can be represented by the $n$ th order differential equations, while the control design stage offers an easy way to determine the control gains required for assigning desired closed loop dynamics to teleoperation system. After the master/slave systems are represented by TS fuzzy models, a stabilizing fuzzy law is adopted which allows deploying the SC scheme with all its benefits to design the fuzzy bilateral controller. In this way, not only the simplicity of the design scheme is ensured but also the existing SC scheme is able to control a nonlinear teleoperation system based on its TS fuzzy model description. As an additional advantage, the SC-based existing linear bilateral controller can be easily derived from the SC-based proposed fuzzy bilateral controller. Various cases of master/slave systems originally reported in terms of their linear model representation and communication in the absence/presence of time delay are all discussed in the corresponding fuzzy framework. The MATLAB simulations, considering a one-degree-of-freedom teleoperation system, are performed to validate the proposed methodology for controlling a nonlinear teleoperation system.

Multiscale fuzzy Kalman filtering

This chapter aims to design a controller to robustly stabilize uncertain nonlinear systems with time-varying delay and norm-bounded uncertainties via Takagi–Sugeno (T-S) fuzzy model. The stabilization conditions are given in the form of Linear Matrix Inequalities using a single Lyapunov–Krasovskii Functional (LKF) combining the introduction of some relaxation matrices and only one tuning parameter. In comparison with the existing techniques in the literature, the proposed approach gives two great advantages. The first, is the reduction of computational complexity when the number of IF-THEN rules, r, is big. The second, concerns the conservatism reduction. Several examples are given to show the effectiveness and the merits of the design procedure.

This paper investigates the problem of robust <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> state estimation for a class of multichannel networked nonlinear systems with multiple packet dropouts. The nonlinear plant is represented by Takagi-Sugeno (T-S) fuzzy-affine dynamic models with norm-bounded uncertainties, and stochastic variables with general probability distributions are adopted to characterize the data missing phenomenon in output channels. The objective is to design an admissible state estimator guaranteeing the stochastic stability of the resulting estimation-error system with a prescribed <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> disturbance attenuation level. It is assumed that the plant premise variables, which are often the state variables or their functions, are not measurable so that the estimator implementation with state-space partition may not be synchronized with the state trajectories of the plant. Based on a piecewise-quadratic Lyapunov function combined with S -procedure and some matrix-inequality-convexifying techniques, two different approaches are developed to robust filtering design for the underlying T-S fuzzy-affine systems with unreliable communication links. All the solutions to the problem are formulated in the form of linear-matrix inequalities (LMIs). Finally, simulation examples are provided to illustrate the effectiveness of the proposed approaches.

International audience

In this paper, robust H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">infin</sub> output feedback control problem for a class of linear discrete-time switched systems with norm-bounded uncertainty and time-varying delay is investigated. A switched dynamic output feedback controller which robustly exponentially stabilizes the switched system and reduces the effect of the disturbance input on the controlled output to a prescribed level was constructed. By using switched Lyapunov function technique, a delay-dependent linear matrix inequality-based sufficient condition for the problem to be solvable is derived. Controller design is performed by solving a set of linear matrix inequalities. Finally, a simulation example is given to illustrate the validity of the results.