Closed-loop Networked Control Systems Research Articles

Dynamic Event-triggered Control for Nonlinear PDE System with Actuator Dead-zone

A dynamic event-triggered network control scheme is proposed for a class of distributed parameter systems with time delay and nonlinearity. The security control of the PDE system under DOS attack based on dynamic event-triggered is studied. A dynamic event-triggered scheme is adopted to reduce the communication burden, that is, the sampling data will be sent only when the original trigger condition is violated. At the same time, a new model including denial of service attack (DOS) is established to describe the random network attack. When a hacker launches a DoS attack, it prevents the sampling data from reaching the destination by interfering with the network channel. DOS attacks follow no specific pattern and exhibit non-periodic behavior or irregular probability distribution. A mathematical model of a state-dependent uncertain system with an event-triggered scheme was established to study denial of service attacks. By using the Lyapunov-Krasocskii stability theory and linear matrix inequality tools, sufficient conditions were derived to ensure the index mean square stability of the state-dependent uncertain system. Based on this, sufficient conditions for the asymptotic stability of the closed-loop network control system and the expected performance index of the system were obtained. Numerical examples verified the feasibility of the method, and controller design validated the applicability of the theoretical results.

Blockchain Protocol-Based Predictive Secure Control for Networked Systems

Networked control systems (NCSs) are widely used in practical applications because of their flexibility in deployment. However, due to the dependence on the communication network, NCSs could be vulnerable to malicious cyberattacks. To address this problem, a novel blockchain technology-assisted networked predictive secure control approach is presented for the first time in this article. First, the introduction of blockchain technology brings a significant boost to the inherent resilience of the NCS in an active manner without relying on any prior knowledge of the system or potential attacks. However, blockchain technology would induce time delays unfavorable to the NCS, which could result in the low real-time performance of the control system. Subsequently, a networked Kalman filter-based predictive control is specially designed to compensate for the low real-time property of blockchain technology. A detailed analysis of the security and stability of the closed-loop NCS with the developed networked predictive secure controller is also presented, while sufficient conditions for the closed-loop system to be simultaneously stable and safe in a probabilistic sense are given. Finally, to verify the performance of the proposed approach in terms of practicality, an experimental prototype of a photovoltaic (PV)-based power generation system subjected to random cyber-attacks is built for voltage regulation.

Fault-tolerant control design for unreliable networked control systems via constrained model predictive control

This work deals with the problem of passive fault-tolerant control (FTC) for discrete-time networked control systems (NCSs). Network imperfections such as random time delay and packet dropout are modeled as a Markov chain that results in a Markovian jump linear system (MJLS). Some of the elements in the transition probability matrix (TPM) are supposed to be unknown so as to address network complexities. In addition, a comprehensive and practical fault model that considers the stochastic nature of networks is employed. By utilizing this fault model, the closed-loop NCS model is obtained by means of state augmentation technique. Then, a constrained model predictive control (MPC) is proposed to develop a fault-tolerant control strategy in which all these issues are considered as well as input constraint. Sufficient conditions to design the proposed reliable controller are derived in terms of linear matrix inequalities (LMIs). Finally, two examples are utilized to demonstrate the validity of the proposed FTC. The simulation results show that the proposed strategy works well, and results in more effective responses compared to state-of-the-arts studies.

On designing the hybrid-triggered dynamic output feedback guaranteed cost control for uncertain T-S fuzzy networked control systems with cyber attack and actuator saturation

In this paper, we study the hybrid-triggered dynamic output feedback-based guaranteed cost control issue for uncertain Takagi-Sugeno (T-S) fuzzy networked control systems (NCSs) with cyber attack and actuator saturation. The hybrid-triggered mechanism comprising of time-triggered mechanism (TTM) and event-triggered mechanism (ETM) is provided to adjust the trigger strategy due to the variety in network resource utilization. Both the switching between two trigger mechanisms and the cyber attack phenomenon in communication network are respectively represented by two Bernoulli distributions. The data quantization is characterized by the sector bound technique and actuator saturation is addressed by invoking an auxiliary matrix. The stability of closed-loop NCSs with bounded disturbance and cyber attack is expressed by the methodology of quadratic boundedness (QB). The existence criteria and design strategies for minimizing the upper bound of performance in view of dynamic output feedback controller are constructed for any admissible uncertainties. Subsequently, in the light of the cone complementarity linearization (CCL) algorithm, the controller design issue is cast into the convex optimization issue which is capable of solving by the technique about linear matrix inequalities (LMIs). Finally, simulation example is employed to demonstrate the validity of designed controller.

Dynamic Event-Triggered Fault Detection for Discrete Networked Control System With Time-Delay

The dynamic event-triggered fault detection problem for discrete networked control systems with time-delay is investigated in this paper. Firstly, for reducing the triggering times, a new dynamic event-trigged is proposed. Secondly, an observer is constructed on the controller node to generate fault residual, and the mathematical model of the closed-loop systems is established by analyzing the sequence of the transmission signal. Thirdly, by constructing a suitable Lyapunov-Krasovskii functional, the sufficient stability conditions for the closed-loop networked control systems are derived. The computing method of the observer gain matrix, the controller gain matrix and the minimal disturbance repression index is provided. Finally, a casy study on the dynamic cart is employed to illustrate the merits of the proposed approach.

Fuzzy Weighted Memory Event-Triggered Control for Networked Control Systems Subject to Deception Attacks

This paper considers the event-triggered control problem for a class of Networked Control Systems (NCS) subject to transmission delays and stochastic deception attacks. A new fuzzy weighted memory event-triggered mechanism is proposed to reduce the network bandwidth consumption and data transmission rates. In this context, a new fuzzy weighted memory state feedback controller is proposed to stabilize the closed-loop NCS. Considering the security problem of NCS, a randomly occurring deception attack model is employed, assuming bounded malicious signals injected by the attacker. Based on a suitable Lyapunov-Krasovskii functional, a design methodology is proposed, in terms of linear matrix inequalities, to synthesize both trigger parameters and NCS controller gains. Finally, a numerical example is considered to illustrated the effectiveness of proposed results, compared to previous ones from the literature.

Networked control strategy of dual linear switched reluctance motors based time delay tracking system

To reduce the influence of time delay on the tracking performance of a direct-drive motion control system, this paper concentrates on stability analysis and cooperative position tracking control issues for the dual linear switched reluctance motors (LSRMs) system with network-induced time delays. The closed-loop network control system (NCS) is constructed by modeling random and bounded network-induced time delays existing in forward and feedback channels as a discrete-time Markov chain. Incremental time delay information is introduced in Lyapunov functional analysis to satisfy the high-precision movement of master and secondary motors and improve the system control performance. The time delay compensation method is proposed to compensate for the damage to the networked control system caused by random delay. With Lyapunov stability theory and LMI are applied, stability and stabilization conditions with less computational complexity and low conservatism are obtained based on incremental time delay information insertion. Finally, the numerical simulation and the experimental platform of the motor control system are built. Simulation and experiment results demonstrate that the networked control strategy can compensate the negative impact of delay on the tracking performance of LSRMs based motion control system.

Fuzzy-logic-based event-triggered [formula omitted] control for networked systems and its application to wind turbine systems

The main objective of the study is to investigate the Takagi-Sugeno fuzzy-model-based networked control system under the fuzzy event-triggered H∞ control scheme. Instead of considering the conventional network transmission delay, the paper introduces the probability distribution based network transmission delay, which is more compatible with real time-simulations. Due to distributed transmission delay, the closed-loop network control system has become distributed delay system. To make use of full information about the membership function, the Lyapunov function candidate is designed as fuzzy-membership-dependent Lyapunov function. A switching concept with respect to the rate of changes in membership functions is introduced to design the optimal control gain matrices for the considered system. The main advantage of the fuzzy-membership-dependent Lyapunov function is that it can ensure the less conservatism of the result without increasing the number of decision variables. To validate the effectiveness of the proposed approach, two kinds are real-time systems are taken into account, one is nonlinear mass-spring-damper model, followed by an industrial example, say, surface mounted permanent magnet synchronous motor model. The corresponding simulation results show the superiority of the proposed results over the existing works.

Hierarchical type stability and stabilization of networked control systems with event-triggered mechanism via canonical Bessel–Legendre inequalities

This paper is studied with the hierarchical type stability and stabilization of networked control systems (NCSs) with event-triggered mechanism (ETM). In the cause of reducing the amount of data transmission and saving the limited network bandwidth, ETM is introduced into NCSs, and the closed-loop time-delay NCSs model with ETM is presented. An improved Lyapunov–Krasovskii functional (LKF), containing delay-product-type terms and being appropriate for the canonical BesselLegendre inequality (BLI), is first constructed. Then, by utilizing the canonical BLI and the extended reciprocally convex matrix inequality (ERCMI) to deal with the single integral terms of the derivative of LKF, a sufficient condition on asymptotically stable is derived for NCSs. Based on above N-dependent stability criteria, a co-design method is developed, which can be capable of calculating the control gain of controller and the weighting matrix of the ETM. Finally, the feasibility and superiority of the results are verified by two examples.

Event-triggered Networked H∞ Output Tracking Control Based on Dynamic Compensation Controller

In this paper, the event-triggered H∞ output tracking problem is investigated for networked control systems. In order to reduce the output tracking error as well as to improve network resource utilization, we propose an idea of dynamic compensation controller with the discrete-time event-triggered mechanism, that is, the integral term of tracking error and the state of the reference system are introduced to form states of the augmented system. We first examine the dynamic compensation idea by the H∞ output tracking control problem for linear time-invariant (LTI) systems. Then, we model the closed-loop event-triggered networked control system as a time-delay augmented linear system. By constructing a Lyapunov-Krasovskii functional with the delay fractioning technique, the stability conditions with lower conservatism are derived in the form of the linear matrix inequalities (LMIs). Furthermore, a method is proposed to design the H∞ dynamic compensation controllers and the discrete-time event-triggered mechanisms. Finally, the satellite tracking control problem is used as an example to show that the dynamical compensation idea is effective in reducing the tracking error and that the proposed method in this paper can achieve better performance than that in the existing literature.

Mixed Actual and Memory Data-based Event-Triggered H∞ Control Design for Networked Control Systems

Abstract In this paper, a new mixed event-triggered control scheme, based on the actual and memory sampled data, is proposed to reduce the network usage in Networked Control Systems (NCS) subject to network-induced delay. In this context, LMI-based conditions are provided from the selection of a convenient Lyapunov-Krasovskii functional, for the design of both the event generator for the proposed Mixed Event Triggered Control (METC) strategy and the associated memory-based sampled-data controller. The goal is to relax the number of transmitted packets, with closed-loop NCS stability guarantee, so that the network workload is mitigated. A numerical example is proposed to show the effectiveness and improvement of the proposed METC design procedure, regarding to some previous related results from the literature.

Event-based fuzzy control for T-S fuzzy networked systems with various data missing

This paper is concerned with the design of fuzzy controller for networked control systems (NCSs). T-S fuzzy system approach is adopted to study the problem. In account of NCSs, various data missing on both sides of the controller caused by event-triggered scheme, data losses and event-driven controller are involved. For handling this issue, an auxiliary random series method is presented to describe the data transferring in the network. Based on this method, the closed-loop NCSs is constructed and then analyzed via Lyapunov stability theory. Additionally, the probability of random data losses at each instant is supposed to be different which is more practical. For the purpose of obtaining more relaxed stabilization conditions, the fuzzy Lyapunov function obtained on the basis of both plant and controller fuzzy rules is employed. Furthermore, variations of membership functions are taken into account, and consequently, slack matrices are introduced to obtain less conservative result. At last, by considering a cart-damper-spring system, the effectiveness of the proposed method is illustrated.

Resilient event-triggered fault-tolerant control for networked control systems with randomly occurring nonlinearities and DoS attacks

This work studies the event-based fault-tolerant control issue of networked control systems with actuator saturation, resilient event-triggering, randomly occurring nonlinearities, and denial-of-service jamming attacks (DoS-JAs). Initially, we aim to design a resilient event-triggered (ET) communication scheme under the attacks, proposed by the known period of the jamming signal. The period values occur in uniform lower bounds for the jammer's sleeping time. Next, a closed-loop networked control system is constructed as a switched-control strategy subject to state-delay, in addition to actuator saturation, actuator faults, DoS jamming attack, parameter uncertainty and resilient ET control schemes. Based on the Lyapunov stability theory, piecewise property and Wirtinger-based integral inequality, a set of sufficient conditions are obtained to ensure that the resulting closed-loop switched system is exponentially stable against DoS jamming attacks and satisfies mixed and passivity performance index. Furthermore, the efficacy of the proposed method is demonstrated through simulated examples based on the two practical applications of satellite control systems and aircraft flight control systems.

PCC Voltage Compensation Scheme of MMC-MTDC System for Transient Stability Enhancement Under Communication Delay

Multi-terminal High Voltage Direct Current (MTDC) with modular multilevel converter (MMC) is a promising technology, because it integrates diverse energy resources. However, there is still a risk for transient stability of a system with MMC in the case of communication delay. In order to improve the transient stability of hybrid AC/DC networks, the point of common coupling (PCC) voltage compensation scheme is proposed for MMC-MTDC to maintain stable operation when communication delay occurs. Based on the established closed-loop network control system (NCS) which the MMC-MTDC participates in, the proposed control strategy utilizes the multi-layer control according to the dynamic characteristic of MMC-MTDC, and compensates the PCC voltage in the controller input signal to reduce inaccuracy case by time delay, thus offset the negative effect of communication delay on power system transient stability. The proposed control method is fully investigated in a MMC-MTDC model based on 4-generator 10-node system model and the simulation results clearly indicate the proposed strategy can effectively enhance transient stability of system.

Adaptive Neural Event-Triggered Control for Discrete-Time Strict-Feedback Nonlinear Systems.

This paper proposes a novel event-triggered (ET) adaptive neural control scheme for a class of discrete-time nonlinear systems in a strict-feedback form. In the proposed scheme, the ideal control input is derived in a recursive design process, which relies on system states only and is unrelated to virtual control laws. In this case, the high-order neural networks (NNs) are used to approximate the ideal control input (but not the virtual control laws), and then the corresponding adaptive neural controller is developed under the ET mechanism. A modified NN weight updating law, nonperiodically tuned at triggering instants, is designed to guarantee the uniformly ultimate boundedness (UUB) of NN weight estimates for all sampling times. In virtue of the bounded NN weight estimates and a dead-zone operator, the ET condition together with an adaptive ET threshold coefficient is constructed to guarantee the UUB of the closed-loop networked control system through the Lyapunov stability theory, thereby largely easing the network communication load. The proposed ET condition is easy to implement because of the avoidance of: 1) the use of the intermediate ET conditions in the backstepping procedure; 2) the computation of virtual control laws; and 3) the redundant triggering of events when the system states converge to a desired region. The validity of the presented scheme is demonstrated by simulation results.

Optimal LQG Control Under Delay-Dependent Costly Information

In the design of closed-loop networked control systems (NCSs), induced transmission delay between sensors and the control station is an often-present issue which compromises control performance and may even cause instability. A very relevant scenario in which network-induced delay needs to be investigated is costly usage of communication resources. More precisely, advanced communication technologies, e.g. 5G, are capable of offering latency-varying information exchange for different prices. Therefore, induced delay becomes a decision variable. It is then the matter of decision maker's willingness to either pay the required cost to have low-latency access to the communication resource, or delay the access at a reduced price. In this article, we consider optimal price-based bi-variable decision making problem for single-loop NCS with a stochastic linear time-invariant system. Assuming that communication incurs cost such that transmission with shorter delay is more costly, a decision maker determines the switching strategy between communication links of different delays such that an optimal balance between the control performance and the communication cost is maintained. In this article, we show that, under mild assumptions on the available information for decision makers, the separation property holds between the optimal link selecting and control policies. As the cost function is decomposable, the optimal policies are efficiently computed.

Stochastic stability of Markovian jump linear systems over networks with random quantization density and time delay

This work studies the stochastic stability of Markovian jump linear systems in a communication network-based environment. By modeling quantization density as well as the sensor-to-controller and controller-to-actuator delays as Markov chains, the closed-loop networked control systems are expressed as switched linear systems. The necessary and sufficient conditions of stochastic stability are derived. By solving a set of linear matrix inequalities with matrix inversion constraints, this work presents a three-mode-dependent state-feedback controller. Its control performance is illustrated via a numerical example.

Input-to-State Stabilization in Probability for Nonlinear Stochastic Systems Under Quantization Effects and Communication Protocols.

In this paper, the observer-based stabilization problem is investigated for a class of discrete-time nonlinear stochastic networked control systems (NCSs) with exogenous disturbances. The signal transmission from the sensors to the observer is implemented via a shared digital network, in which both uniform quantization effect and stochastic communication protocol (SCP) are taken into account to reflect several network-induced constraints. The notion of input-to-state stability in probability is introduced to describe the dynamical behaviors of the closed-loop stochastic NCS that is effectively characterized by a general nonlinear stochastic difference equation with Markovian jumping parameters. A theoretical framework is first established to felicitate the dynamics analysis of the closed-loop system in virtue of the switched Lyapunov function method and the stochastic analysis techniques. By making full use of the quantized measurement output under the scheduling of the SCP, the existence conditions for an observer-based controller are established under which the closed-loop system is input-to-state stable in probability. Then, the explicit expression of the gain matrices of the desired controller is given by resorting to a set of feasible solutions of certain matrix inequalities. The effectiveness of the theoretical results is demonstrated by a numerical simulation example.

Stabilization of uncertain systems with Markovian modes of time delay and quantization density

This work studies the stabilization of a class of control systems that use communication networks as signal transmission medium. The lateral motion of independently actuated four-wheel vehicle is modeled as an uncertain-linear system. Time delay and quantization density are modeled as Markov chains. The networked control systems U+0028 NCSs U+0029 with plants being lateral motion are first transformed to switched linear systems with uncertain parameters. Sufficient and necessary conditions for the stochastic stability of closed-loop networked control systems are then established. By solving the matrix inequalities, this work presents an output-feedback controller that depends on the modes of time delay and quantization density. The controller performance is illustrated via a vehicular lateral motion system.

Hybrid Scheduling and Quantized Output Feedback Control for Networked Control Systems

A novel co-design scheme of hybrid scheduling strategy, adaptive logarithmic quantizer and dynamic robust H-infinity output feedback controller for a class of networked control system (NCS)with communication constraints and time delay is proposed. The hybrid scheduling scheme integrates dead zone scheduling and Try Once Discard (TOD) scheduling so as to get the stronger adaptability and flexibility than the single scheduling. In this scheme, dead zone scheduling which updates the threshold according to mode-dependent control strategy is used for single node of NCS to reduce the network bandwidth utilization while TOD scheduling is used for the whole node of NCS in order to meet the requirements of communication constraints and guarantee the overall system performance.We develop the integrated design for the hybrid scheduling strategy, adaptive quantizer and dynamic robust output feedback controller to maintain asymptotic stability of the closed-loop NCS by using the multiple-Lyapunov function and switched system theory. The proposed method can improve the the quality of service (QoS) meanwhile ensure the quality of control (QoC) of overall systems, which make a better trade-off between network utilization and control performance. An simulation example demonstrates the efficiency of the proposed method.