Data-based predictive control for networked nonlinear systems with packet dropout and measurement noise

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.

A new approach to exponential stabilization for a class of nonlinear networked systems with stochastic delays is given in this paper. By using the fuzzy T-S method, a new model of nonlinear networked control systems with is derived. The networked induced delays are assumed to have some stochastic characteristics. A stochastic variable satisfying Bernoulli distribution is introduced with the probability of the delays taking value in different interval. With the Lyapunov stability theorem, a exponential stabilization condition and a state feedback controller design method are obtained. And all the conditions are expressed in terms of LMI. Finally, a numerical example is given to demonstrate the validity of the results.

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.

This paper presents an H ∞ controller design method for a class of Networked Control Systems (NCSs) with bounded packet dropouts. The state feedback closed-loop NCS is modeled as a Markov system. A sufficient condition for stochastic stability with an H ∞ disturbance attenuation level is derived through a Lyapunov function, which is dependent on the upper bound of the number of consecutive packet dropouts. The corresponding state feedback control law is presented in terms of linear matrix inequalities (LMIs). A numerical example is finally provided to show the effectiveness of the proposed 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.

This paper discusses the model-based predictive controller design of networked nonlinear systems with communication delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation results demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.

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.

Robust probabilistic sampling [formula omitted] output tracking control for a class of nonlinear networked systems with multiplicative noises

In this article, the problem of robust sampled-data H ∞ output tracking control is investigated for a class of nonlinear networked systems with stochastic sampling and time-varying norm-bounded uncertainties. For the sake of technical simplicity, only two different sampling periods are considered, their occurrence probabilities are given constants and satisfy Bernoulli distribution, and can be extended to the case with multiple stochastic sampling periods. By the way of an input delay, the probabilistic system is transformed into a stochastic continuous time-delay system. A new linear matrix inequality-based procedure is proposed for designing state-feedback controllers, which would guarantee that the closed-loop networked system with stochastic sampling tracks the output of a given reference model well in the sense of H ∞. Conservatism is reduced by taking the probability into account. Both network-induced delays and packet dropouts have been considered. Finally, an illustrative example is given to show the usefulness and effectiveness of the proposed H ∞ output tracking design.

In this paper, the fault estimation problem is studied for a class of nonlinear networked control systems with imperfect measurements. A novel measurement model is proposed to take time‐varying delays, random packet dropouts, and the packet‐dropout compensation into consideration simultaneously. After properly augmenting the states of the original system and the fault estimation filter, the addressed fault estimation problem is converted into an auxiliary H∞ filtering problem for a stochastic parameter system. In terms of matrix inequalities, a sufficient condition for the existence of the fault estimation filter is derived that depends on the packet dropout rate, the upper and lower bounds of time delays, and the size of the consecutive packet dropouts. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S) fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.

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

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <?Pub Dtl=""?>This paper is concerned with the optimal filtering problem for discrete-time stochastic linear systems with multiple packet dropouts, where the number of consecutive packet dropouts is limited by a known upper bound. Without resorting to state augmentation, the system is converted to one with measurement delays and a moving average (MV) colored measurement noise. An unbiased optimal filter is developed in the linear least-mean-square sense. Its solution depends on the recursion of a Riccati equation and a Lyapunov equation. A numerical example shows the effectiveness of the proposed filter. </para>

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.

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.