Adaptive Event-Triggered Output Feedback Fuzzy Control for Nonlinear Networked Systems With Packet Dropouts and Actuator Failure

This paper investigates the problem of event-triggered dynamic output feedback control for networked Takagi-Sugeno (T-S) fuzzy systems with asynchronous premise variables. Our attention is focused on the design of an event-triggered fuzzy dynamic output feedback controller that guarantees that the closed-loop system is asymptotically stable. First, with consideration of the limited bandwidth and restricted network resource, an event-triggered communication scheme is proposed to save the limited network resource. Second, different from the existing results in the literature, a fuzzy dynamic output feedback controller with asynchronous premise variables is constructed such that the premise membership functions are not necessarily the same as the networked T-S fuzzy systems. Then, by using the Wirtinger inequality and some slack matrices, a less conservative stability and stabilization conditions for the existence of fuzzy dynamic output feedback controller are derived in the form of linear matrix inequalities, which can be solved by the standard MATLAB toolbox. Finally, an example is given to demonstrate the effectiveness of the designed event-triggered fuzzy dynamic output feedback controller.

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

This paper studies the synthesis approach of dynamic output feedback model predictive control (OFMPC) for nonlinear networked control systems (NCSs), which can be described by interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model. The Bernoulli random binary distribution is exploited to describe the process of packet loss in NCSs. Compared with the existed output feedback model predictive controller based on traditional state observer, the parameter dependent dynamic OFMPC which minimizes the upper bound of a quadratic objective function in an infinite horizon is designed by applying the notion of quadratic boundedness. A numerical example is given to demonstrate the effectiveness of the proposed new design techniques.

Dynamic event-triggered security control for networked T-S fuzzy system with non-uniform sampling

In this paper, the data-based control problem is investigated for a class of networked nonlinear systems with measurement noise as well as packet dropouts in the feedback and forward channels. The measurement noise and the number of consecutive packet dropouts in both channels are assumed to be random but bounded. A data-based networked predictive control method is proposed, in which a sequence of control increment predictions are calculated in the controller based on the measured output error, and based on the control increment predictions received by the actuator, a proper control action is obtained and applied to the plant according to the real-time number of consecutive packet dropouts at each sampling instant. Then the stability analysis is performed for the networked closed-loop system. Finally, the effectiveness of the proposed method is illustrated by a numerical example.

In this study, an interval-type-2 (IT-2) fuzzy controller for nonlinear networked control systems (NNCSs) under multichannel denial-of-service (DoS) attacks is designed. First, an NNCS is modeled as an IT-2 fuzzy control system, and uncertainty is introduced into the NNCS. Second, DoS attacks are performed simultaneously in the sampler-to-controller channel and the controller-to-actuator channel. The DoS attacks are modeled via the Bernoulli distribution. Owing to the limited performance of the actuator and because DoS attacks introduce large amounts of useless data, the actuator needs to process large amounts of data; thus, this study considers the actuator saturation problem. Finally, to alleviate the pressure of channel transmission data and improve the utilization of network resources, an improved adaptive event-triggered mechanism (AETM) is proposed. Considering the above situation, a closed-loop system is established, and an IT-2 fuzzy controller is designed for the system. The simulation results for the IT-2 fuzzy control system prove the validity of the controller design proposed in this paper.

ABSTRACTThis paper focuses on the design of H∞ filter and event-triggered scheme for a class of continuous non-linear networked control systems (NCSs) based on fuzzy system appeared with time delays. First, we consider the discrete event-triggered (ET) scheme to make efficient utilisation of bandwidth. Under this ET-scheme, sensor releases the data only when our sampled-data plant violates the specific event-triggered condition. Second, the T-S fuzzy system is used to model the non-linear NCSs. Another purpose of this paper is to design filters involving delays. Such filters have a more general form than the delay-free filters that have been mostly considered in the traditional studies. By using the time-delay system, co-design of event-triggered scheme and H∞ filter for the delayed NCSs is presented in a unified frame work. To choose the latest data packet and discard the dis-ordered packet logic, zero-order hold is inserted between the fuzzy filter and event generator. Then, by using the novel fuzzy Lyapunov–Krasovskii function approach with free-weighting matrix technique, H∞ filter design of event-triggered delay NCSs is proposed. Finally, to show the effective result of our co-design method, a tunnel-diode example is given.

This paper studies the problem of dynamic output feedback H (infinity) control for nonlinear systems, which are described by Takagi-Sugeno fuzzy parts with measurable premise variables and uncertainty parts. The uncertainties are parameter dependent, unknown, and time varying but bounded. A switching fuzzy dynamic output feedback control scheme is proposed, which depends on the measurable premise variables and the bounds of the unknown parameters of the considered system, where the switching mechanism is introduced to handle the unknown parameters. A two-step linear-matrix-inequality-based optimization procedure is developed to design switching fuzzy H (infinity) controllers. An example is given to illustrate the effectiveness of the proposed design method.

Design of output feedback semiglobally practically input-to-state (SPIS) stabilizing controllers for nonlinear strict-feedback networked systems is considered. We first design continuous-time state feedback globally asymptotically (GA) stabilizing controllers and discrete-time reduced-order observers and combine the emulation of state feedback controllers and the designed observers to construct discrete-time output feedback controllers. Then we show that the designed controllers SPIS stabilize nonlinear strict-feedback networked control systems when transmission intervals are sufficiently small and communication networks satisfy suitable assumptions. A numerical example is also given to illustrate the efficiency of proposed design of controllers.

In this chapter, we investigate a class of constrained nonlinear networked control systems (NCSs) subject to external disturbances, input and state constraints, and network-induced constraints. From a practical perspective, the network-induced constraints considered include the time delays and packet dropouts on both the sensor-to-controller (S-C) channel and the controller-to-actuator (C-A) channel simultaneously. The min-max RHC method is proposed to design the control packets by incorporating the external disturbances into the optimization problem. Moreover, the input-to-state practical stability (ISpS) of the resulting nonlinear NCS is established by constructing a novel Lyapunov function.

Performance recovery-based fuzzy robust control of networked nonlinear systems against actuator fault: A deferred actuator-switching method

Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systemsIn this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.

This paper is concerned with the problem of guaranteed cost control for a class of continuous-time networked control systems based on the Takagi–Sugeno fuzzy model approach. In this study, network-induced transmission delays and packet dropouts are taken into simultaneous consideration. By the improved Lyapunov–Krasovskii functionals, a less-conservative delay-dependent condition is proposed for the stability analysis of the resulting closed-loop system. Furthermore, the sufficient condition under which the guaranteed cost controller exists is formulated in terms of linear matrix inequalities, and the suboptimum solution is obtained by a cone complementarity linearization algorithm. Finally, numerical examples are provided to illustrate the effectiveness of the proposed method.

Mode-independent fuzzy fault-tolerant variable sampling stabilization of nonlinear networked systems with both time-varying and random delays

This article studies the problem of event-triggered adaptive fault-tolerant fuzzy output feedback consensus tracking control for nonlinear fractional-order multiagent systems with actuator failures under a directed graph. Considering the fact that the actual system works near the equilibrium point most of the time, a novel dynamic event-triggering strategy with the reset mechanism is proposed, where the dynamic threshold can be actively adjusted according to the preset conditions, so that the resource utilization can be further reduced. Based on an improved event-based consensus error, the state estimator about the derivative of reference trajectory and the adaptive law about the information of graph are constructed, which makes distributed consensus tracking control achieved without obtaining global information. Then, by introducing two adaptive compensating terms to deal with actuator failures and event-triggered measurement errors, it is shown in the sense of fractional-order stability criterion that tracking errors can converge to a compact set even if the fault parameters and modes are completely unknown. Finally, the correctness of the presented method is verified by a simulation example.