Nonlinear Networked Control Systems Research Articles

Formula omitted] non-fragile observer-based dynamic event-triggered sliding mode control for nonlinear networked systems with sensor saturation and dead-zone input

This paper considers the problem of robust non-fragile observer-based dynamic event-triggered sliding mode control (SMC) for a class of discrete-time Lipschitz nonlinear networked control systems subject to sensor saturation and dead-zone input nonlinearity. First, an improved dynamic event-triggered scheme (DETS) in consideration of sensor saturation is proposed to reduce the number of data transmission. Next, a non-fragile observer is designed to estimate the system state, which facilitates the construction of the discrete sliding surface. By using a reformulated Lipschitz property, the error dynamics and sliding mode dynamics are modeled as a unified linear parameter varying (LPV) networked system with time-varying delays. Then, based on this model, sufficient conditions are established to guarantee the resulting closed-loop system to be asymptotically stable with a given disturbance attenuation level. Furthermore, an observer-based event-triggered SMC law is designed to drive the trajectories of the observer system onto a region near equilibrium point in a finite time in the presence of dead-zone input nonlinearity. Finally, two practical examples are employed to demonstrate the effectiveness of the proposed method.

Fuzzy-model-based fault detection for nonlinear networked control systems with periodic access constraints and Bernoulli packet dropouts

In this paper, the problem of fault detection for nonlinear networked control systems subject to both communication constraints and packet dropouts is investigated. Despite the huge bulk of studies in the area of linear networked control systems, nonlinear networked control systems have been less involved. In the proposed method, Takagi–Sugeno fuzzy model is employed to represent nonlinear networked control systems. To model the communication network, access constraints and packet dropouts are respectively considered as periodic sequences and Bernoulli processes. Based on the optimal periodic residual generator theory, a fuzzy-model-based observer is proposed to deal with the problem of fault detection for nonlinear networked control systems. Both residual evaluation and correspondence threshold are also investigated to generate confident fault alarms. Finally, the effectiveness of the proposed fault detection scheme for nonlinear networked control systems is illustrated and some simulation results are carried out to validate the proposed approach.

Iterative learning control for uncertain nonlinear networked control systems with random packet dropout

SummaryThis paper proposes a novel networked iterative learning control (NILC) scheme with adjustment factor for a class of discrete‐time uncertain nonlinear systems with stochastic input and output packet dropout modeled as 0‐1 Bernoulli‐type random variable. Firstly, the equivalence relation between the realizability of controlled system and the input‐output coupling parameter (IOCP) is established. Secondly, in order to overcome the main obstacle arising from the unknown IOCP, an identification technique is developed for it. Thirdly, it is strictly proved that, under certain conditions, the tracking errors driven by the developed NILC scheme are convergent to zero along iteration direction in the sense of expectation. Finally, an example is given to demonstrate the effectiveness of the proposed NILC scheme and the merits of adjustment factor.

Attack Detection and Approximation in Nonlinear Networked Control Systems Using Neural Networks.

In networked control systems (NCS), a certain class of attacks on the communication network is known to raise traffic flows causing delays and packet losses to increase. This paper presents a novel neural network (NN)-based attack detection and estimation scheme that captures the abnormal traffic flow due to a class of attacks on the communication links within the feedback loop of an NCS. By modeling the unknown network flow as a nonlinear function at the bottleneck node and using a NN observer, the network attack detection residual is defined and utilized to determine the onset of an attack in the communication network when the residual exceeds a predefined threshold. Upon detection, another NN is used to estimate the flow injected by the attack. For the physical system, we develop an attack detection scheme by using an adaptive dynamic programming-based optimal event-triggered NN controller in the presence of network delays and packet losses. Attacks on the network as well as on the sensors of the physical system can be detected and estimated with the proposed scheme. The simulation results confirm theoretical conclusions.

Synthesizing Communication Plans for Reachability and Safety Specifications

We propose control and communication strategies for nonlinear networked control systems subject to state and input constraints. The objective is to steer the state of the system toward a prescribed target set in finite time ( reachability ), while at the same time remaining inside a safety set for all time ( safety ). By leveraging the notion of the $\delta$ -input-to-state stability (ISS) control Lyapunov function, we derive a sufficient condition to generate a communication scheduling, such that the resulting state trajectory guarantees reachability and safety. Moreover, in order to alleviate computational burden, we present a way to find a suitable communication scheduling by implementing abstraction schemes and standard graph search methodologies. Simulation examples validate the effectiveness of the proposed approach.

Model predictive control under event-triggered communication scheme for nonlinear networked systems

The paper studies the problem of event-triggered H2/H∞ model predictive control (MPC) for nonlinear networked control systems (NCSs) with bandwidth limitation and packet loss. The nonlinear system is described by the interval type-2 Takagi-Sugeno (IT-2 T-S) fuzzy model. To reduce the communication bandwidth utilization, an event-triggered communication scheme is presented to determine the transmission of the latest sampled state. The unreliable networks with packet loss are described by stochastic variables which satisfy Bernoulli binomial distribution. This paper aims at designing a fuzzy predictive controller to make the resulting closed-loop system stochastically stable with H2/H∞ performance satisfied. An online optimization MPC problem is formulated to optimize a H2 performance index while the H∞ performance index is prescribed. We provide a numerical example to illustrate the validity of the presented technique.

A novel event‐triggered extended state observer for networked control systems subjected to external disturbances

SummaryIn this paper, the event‐triggered‐based state estimation problem is investigated for a class of nonlinear networked control systems subjected to external disturbances. A novel event‐triggered extended state observer (ESO) is utilized to estimate the so‐called total disturbance, and an output predictor is adopted for the proposed ESO between two consecutive transmission instants. It is also worth pointing out that, in the newly proposed ESO, an event‐triggered mechanism is adopted to update the measurement signal so as to save the communication resource. The sufficient conditions are provided such that the estimation error dynamics is exponentially ultimately bounded. Furthermore, it is proven that the Zeno behavior does not exist for the event‐triggering rules. A number of numerical simulations are conducted to verify the validity of the theoretical results.

H∞ Control for Discrete-Time Networked T-S Fuzzy Systems with Packet Loss Based on Event-Triggered Mechanism

The H∞ state feedback control problem for a class of nonlinear networked control systems with data packet loss is studied using an event-triggered scheme. The data packet loss is described as an independent and homogeneous Bernoulli process. Under an event-triggered scheme, the nonlinear networked control system with packet loss is modeled as a Takagi-Sugeno (T-S) fuzzy system, based on which sufficient conditions on the existence of event-triggered state feedback controllers are derived such that the closed-loop system is mean-square stable with a desired H∞ performance index. The simulation results show that the presented event-triggered scheme can not only ensure the closed-loop performance but also effectively reduce the data transmission rate.

New Stability Criteria for Event‐Triggered Nonlinear Networked Control System with Time Delay

This note focuses on the stability and stabilization problem of nonlinear networked control system with time delay. To alleviate the burden of transformation channel and shorten the dynamic process simultaneously, an improved event‐triggered scheme is proposed. This paper employs an improved time delay method to enhance the performance and reduce the delay upper bound conservatism. Less conservative stability criteria related to the order N are derived by establishing an augmented Lyapunov‐Krasovskii functional manufactured for the use of Bessel‐Legendre inequality. In addition, an event‐triggered controller is designed for nonlinear networked control system with time delay. At last, numerical examples are proposed to verify the effectiveness of the new method.

Dissipativityof Nonlinear Networked Control Systems Modeled by Markovian Jump System

Networked control system (NCS) is a control system in which the control loop is closed by a shared communication networked. There are some parameters that arise when using a network in an NCS such as packet dropout, time delay, limited bandwidth, and so forth. Due to the stochastic property of such parameters, the entire system under consideration realizes the Markovian jump system. This paper considers a dissipativity notion for a class of nonlinear networked control systems. Dissipativity refers to the existence of a supply rate function dealing with the system such that the system has a dissipative property. The main result in this paper is a solvability condition for achieving dissipativity of a class of nonlinear networked control systems modeled by Markovian jump system. The solvability condition is shown by the nonlinear matrix inequalities (NLMI).

Robust <inline-formula> <tex-math notation="LaTeX">$H_{\infty}$ </tex-math> </inline-formula> Control of Lurie Nonlinear Stochastic Network Control Systems With Multiple Additive Time-Varying Delay Components

In order to further solve the stability problem in the actual network control systems, this paper first simultaneously considers the controlled object system delay and network time delay in the Lurie nonlinear stochastic network control systems. Among them, the controlled object system delay is multi-time delay and the network time delay is two additive time-varying delay component. The proposing of the two additive time-varying delay components in network control systems has advantages in producing less conservatism over the previous one with a combined delay. By employing the method of improved free weighting matrix and constructing a Lyapunov–Krasovskii functional, less conservative robust $H_{\infty }$ stability criterion is established and the controller is designed for the system in this paper. Some numerical examples are given to demonstrate the applicability of the proposed method.

Hysteresis Quantizer-Based Event-Triggered Control of Nonlinear Networked Control Systems

In this paper, we present a novel event-triggered control mechanism for nonlinear systems with hysteresis quantization. To describe the tendency of the dynamic quantizer parameter, an auxiliary parameter is created and the relationship between the quantizer parameter and the auxiliary parameter has been discussed. Via thoroughly analyzing the structure of the hysteresis quantizer, the hysteresis quantizer based event-triggered control mechanism is designed to appropriately decide the accurate signal transmission instants with simple calculation process. Moreover, under the proposed method, the nonlinear system could be stabilized and Zeno behavior could be intrinsically avoided. Furthermore, a numerical example is given to demonstrate the efficiency of the proposed mechanism.

H<sub>∞</sub> disturbance attenuation of nonlinear networked control systems via Takagi-Sugeno fuzzy model

H∞ disturbance attenuation of nonlinear networked systems which are described by the Takagi-Sugeno fuzzy time-delay systems is concerned. In the networked control system, the control signal is delayed and the closed-loop system with the controller can be modeled as a fuzzy system with time-varying delays in sensor and actuator nodes. The system often encounters the external noises that disturb its behaviors. For such a nonlinear system with delays, the H∞ disturbance attenuation problem is considered. Multiple Lyapunov-Krasovskii function with multiple integral functions allows us to obtain less conservative conditions for a networked control system to satisfy the disturbance attenuation criterion. Based on this approach, a novel control design method for a networked control system is proposed. An illustrative example is given to show the effectiveness of the proposed method.

New Results on the Observer-Based <inline-formula> <tex-math notation="LaTeX">$H_{\infty}$ </tex-math> </inline-formula> Control for Uncertain Nonlinear Networked Control Systems With Random Packet Losses

This paper presents the new results on the H ∞ control of a class of completely uncertain nonlinear networked control systems with random communication packet dropouts, which is partially considered in this paper. The uncertainties in the plant are assumed to be real and time-varying, as well as norm, bounded. The random packet losses are modeled as a Bernoulli distributed white sequence with known conditions on their probability distribution. The controller was designed as an observer-based H ∞ dynamic, such that the closed-loop system is exponentially mean square stable and the effect of the disturbance input on the controlled output is less than a minimum level γ for all admissible uncertainties. New sufficient conditions for the existence of such a controller are presented and proved based on the linear matrix inequalities' approach. The theory presented is illustrated by a numerical example to show the effectiveness of the developed techniques.

Robust packet-based nonlinear fuzzy networked control systems

A class of networked nonlinear control systems with norm-bounded uncertainties is presented in this paper. The class is represented by Takagi–Sugeno (T-S) fuzzy models with packet processing. The network loop delay is considered either as known delay or random delay. For the former case, we develop conditions that guarantee the robust asymptotic stability and state-feedback stabilization with strict dissipativity and cast the results in linear matrix inequality (LMI) framework. Next employing a probabilistic-based delay partitioning method to deal with random delay, we establish novel LMI criteria for strict dissipative stability analysis and feedback synthesis. The efficacy of the ensuing techniques is demonstrated by numerical solution of typical examples and Mont Carlo simulation.

Reliable mixed [formula omitted] and passive control for networked control systems under adaptive event-triggered scheme with actuator faults and randomly occurring nonlinear perturbations

In this paper, the problem of reliable mixed H∞ and passive control for a class of nonlinear networked control systems under the adaptive event-triggered scheme with actuator faults and randomly occurring nonlinear perturbations is studied. Firstly, a series of independent stochastic variables with certain probabilistic distribution are presented to formulate the phenomena of actuator faults. Then, different from the traditional event-triggered scheme, the threshold of adaptive event-triggered scheme is determined by an online adaptive control law instead of the preset constant value. Further, based on a novel Lyapunov functional by taking the adaptive control law into account, sufficient conditions for asymptotically stable with mixed H∞ and passive performance are obtained in terms of a set of LMIs. If these LMIs are feasible, the reliable mixed H∞ and passive control gain and the weight parameter of adaptive event-triggered scheme can be gained simultaneously. Finally, two numerical examples are provided to show the effectiveness of the developed technique.

Integrated Sliding Mode Control and Neural Networks Based Packet Disordering Prediction for Nonlinear Networked Control Systems.

In this paper, we propose a new scheme based on neural networks for predicting the packet disordering and sliding mode control (SMC) to stabilize the nonlinear networked control systems (NCSs). It is assumed that the packet disordering is unknown in the NCSs. The stochastic configuration networks (SCNs), which randomly assign the input weights and biases and analytically evaluate the output weights, are designed to solve the problem of unknown packet disordering. A new SMC scheme is developed by integrating the SCNs algorithm to learn and control the system in advance. Specifically, a novel measurement of packet disordering is constructed for the quantization of the packet disordering. In addition, the newest signal principle leads to the existence of stochastic parameters, thereby resulting in a Markovian jumping system. The effectiveness of the proposed approach is verified by some simulation results.

Finite-Time Boundedness Control for Nonlinear Networked Systems with Randomly Occurring Multi-Distributed Delays and Missing Measurements

This paper investigates the stochastic finite-time H∞ boundedness problem for nonlinear discrete time networked systems with randomly occurring multi-distributed delays and missing measurements. The randomly occurring multi-distributed delays and missing measurements are described as Bernoulli distributed white noise sequence. The goal of this paper is to design a full-order output-feedback controller to guarantee that the corresponding closed-loop system is stochastic finite-time H∞ bounded and with desired H∞ performance. By constructing a new Lyapunov-Krasovskii functional, sufficient conditions for the existence of output-feedback are established. The desired full-order output-feedback controller is designed in terms of the solution to linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the validity of the designed method.

Observer-Based H-infinity Controller for Nonlinear Singular Networked Control Systems

Observer-Based H-infinity Controller for Nonlinear Singular Networked Control Systems

Particle filter with Markovian packet dropout and time delay

This technical note is concerned with particle filter for the discrete-time nonlinear networked control system. First, modified particle filter algorithm with Markovian packet dropout and time delay is proposed, and its error covariance is benchmarked by Markovian Cramér-Rao lower bound. Second, an upper bound of the Markovian Cramér-Rao lower bound is presented for some special nonlinear networked systems. Third, some necessary conditions for the boundness of error covariance are given by obtaining some sufficient conditions for the bounded Markovian Cramér-Rao lower bound. Finally, numerical examples are presented to illustrate the efficiency of proposed particle filter.