Nonlinear Networked Control Systems Research Articles

Co-Design of Adaptive Memory Event-Triggered Mechanism and Aperiodic Intermittent Controller for Nonlinear Networked Control Systems

This brief addresses the co-design problem of adaptive memory event-triggered mechanism (AMETM) and aperiodic intermittent controller (AIC) for nonlinear networked control systems. To improve the utilization efficiency of network resources,an AMETM with non-periodic waiting time is proposed, in which the Zeno behaviour is excluded. Meanwhile, an event-dependent AIC matching the proposed AMETM is designed to save more control resources and cost. Furthermore, an exponential stability criterion is established in the form of linear matrix inequality. Finally, the Chua’s circuit is provided to verify the effectiveness of the proposed AMETM and AIC.

Event-Triggered MFAC of Nonlinear NCSs Against Sensor Faults and DoS Attacks

The event-triggered model-free adaptive control (ET-MFAC) problem for nonlinear networked control systems (NNCSs) with presence of sensor faults and denial-of-service (DoS) attacks is investigated. The attack occured in sensor-to-controller networked channels is supposed to obey the Bernoulli distribution. While sensor faults are formulated as unknown functions which could be approximated by a radial basis function-based neural networks (RBF-NNs). Then an ET-MFAC algorithm is constructed to ensure the tracking performance under sensor faults and DoS attacks based on adaptive estimations. The designed control algorithm is independent with the system structure and only uses the system input and output data. An example with comparison is given to demonstrate the validity of the new ET-MFAC algorithm.

Sampled-Data-Based Dissipative Stabilization of IT-2 TSFSs Via Fuzzy Adaptive Event-Triggered Protocol.

In this research, the fuzzy adaptive event-triggered control (FAETC) issue is addressed for uncertain nonlinear networked control systems with network-induced delays (NIDs) and external disturbance. In order to effectively capture parameter uncertainties, the interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy model is utilized to represent such a system. Considering the fact that the controller is fuzzy and the threshold can promptly update its state according to the current and latest sampled signals (SSs), it becomes quite challenging to solve the dissipative stabilization problem (DSP) with the existing schemes. Then, a novel FAETC protocol is put forward to reduce the utilization of communication resources while maintaining the desired control performance. By employing the fuzzy-logic technique and the looped Lyapunov functional (LLF) approach, sufficient conditions related to the relationship between the stabilization and desired dissipative performance for the resulting system are formulated. A numerical example is used to validate the feasibility of our attained results.

Adaptive control for the nonlinear event-triggered networked control system: a decoupling method

In this paper, the adaptive control for a kind of nonlinear system over the event-driven sensors-controller communication network is addressed. Over this network, the existing strategy has been developed. However, the event-triggered mechanism and adaptive estimators are coupled together, which results in extra information delivery of the adaptive estimators over the network or extra computation equipment on the sensor side. To overcome this limitations, two kinds of adaptive control strategies are proposed in this paper. At first, the control strategy with the new event-triggered adaptive estimator is developed for the system without external disturbances where the event-triggered mechanism does not need the information of the adaptive estimators. It is proved that the closed-loop system is asymptotically stable and the Zeno behaviour is excluded. Furthermore, for the system with external disturbances, a robust control scheme with modified adaptive estimator and event-triggered mechanism is proposed and the practical stability of the closed-loop system is guaranteed. Also, the Zeno behaviour is excluded carefully. Comparing with the existing results, due to the decoupling structure of event-triggered mechanism and adaptive estimators, it is unnecessary to transfer the estimators’ information to the event-triggered mechanism on the sensor side, which saves the communication cost. What’s more, although the system state is sampled and event driven, the asymptotical stability is still guaranteed. Also, the developed strategy can handle with the external disturbances. Finally, two examples are performed to illustrate the effectiveness of the schemes and some comparisons are displayed to explain the advantages of the methods.

Event-triggered control of interconnected nonlinear systems subjected to cyber-attacks and time-varying coupling

This paper addresses the problem of efficient control of nonlinear distributed networked control systems in the presence of stochastic deception attacks and time-varying coupling strength. A strategy combining model-based and event-triggered control to reduce the number of transmissions over a network thereby, saving network resources is proposed. In this strategy, a plant model at the controller end is used to estimate the state of each subsystem. Further, the control law between the two adjacent triggering instants changes in accordance with dynamics of the plant model. The nonlinearities present in each subsystem are approximated via neural network. The neural network weights and feedback signal are updated only when the event-triggering condition at the sensor end is violated. Also, a lower bound on the inter-event time is computed to avoid the occurrence of Zeno phenomena. Finally, the efficacy of the proposed methodology are verified through simulation examples.

Security-Based Fuzzy Control for Nonlinear Networked Control Systems With DoS Attacks via a Resilient Event-Triggered Scheme

This article studies the issue of resilient event-triggered (RET)-based security controller design for nonlinear networked control systems (NCSs) described by interval type-2 (IT2) fuzzy models subject to nonperiodic denial of service (DoS) attacks. Under the nonperiodic DoS attacks, the state error caused by the packets loss phenomenon is transformed into an uncertain variable in the designed event-triggered condition. Then, an RET strategy based on the uncertain event-triggered variable is firstly proposed for the nonlinear NCSs. The existing results that utilized the hybrid triggered scheme have the defect of complex control structure, and most of the security compensation methods for handling the impacts caused by DoS attacks need to transmit some compensation data when the DoS attacks disappear, which may lead to large performance loss of the systems. Different from these existing results, the proposed RET strategy can transmit the necessary packets to the controller under nonperiodic DoS attacks to reduce the performance loss of the systems and a new security controller subject to the RET scheme and mismatched membership functions is designed to simplify the network control structure under DoS attacks. Finally, some simulation results are utilized to testify the advantages of the presented approach.

Observer-Based Switching-Like Event-Triggered Control of Nonlinear Networked Systems Against DoS Attacks

This article investigates the problem of observer-based switching-like event-triggered control (ETC) for non- linear networked systems subject to aperiodic denial-of-service (DoS) attacks. First, a full-order state observer is developed to estimate the unavailable system states and used to establish the switching-like event-triggered condition, which includes two different threshold para- meters. Second, in order to improve the bandwidth re- source utilization and compensate for the influence of DoS attacks, a switching-like event-triggered mechanism (SETM) is designed, which can adaptively switch two different threshold parameters based on the presence or absence of DoS attacks. By combining the proposed SETM, an output feedback controller is constructed and a new observer-based switching-like ETC strategy is presented for nonlinear networked systems. Meanwhile, the relationship between the inactive/active period of the DoS attacks, the parameters of the SETM, the unmeasurable states, and the sampling period in the model are quanti- tatively discussed on the basis of the new strategy. Then, in terms of the proposed control strategy, the global asymptotical stability of the nonlinear networked systems can be obtained. Finally, two examples are used to verify the feasibility and effectiveness of the designed strategy.

Dynamic Hybrid-Triggered-Based Fuzzy Control for Nonlinear Networks Under Multiple Cyberattacks

This article addresses the problem of dynamic hybrid-triggered control for nonlinear networked control systems. A novel resilient control method is presented to improve network resource utilization and system performance against cyberattacks for the underlying systems. First, a fuzzy-model-based system is established to describe the nonlinear networked systems subject to multiple cyberattacks, external disturbances, parameter uncertainties, and network-induced delays. Then, a resilient dynamic hybrid-triggered scheme is proposed to conserve the network bandwidth and reduce the effect of cyberattacks. A new codesign method of the observer-based fuzzy controller and the resilient dynamic hybrid-triggered scheme is developed. Sufficient conditions in terms of linear matrix inequalities are given such that the closed-loop system is global exponential stable with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> disturbances attenuation level. Finally, an example of lateral control in autonomous driving is given to verify the effectiveness of the developed control method.

Event-Triggered Fault-Tolerant Control for Nonlinear Networked Control Systems

This paper addresses the communication congestion and actuator fault in a nonlinear networked control system. A weighted average event-triggered mechanism adopted the weighted average of data packets is proposed to alleviate the communication congestion and save the network communication resources. Meanwhile, based on the system state estimation and fault estimation obtained by a state-fault observer, a fault-tolerant controller is designed to compensate and reduce the influence of fault and nonlinear factors in the networked control systems. The stability of the closed-loop system is proved by the Lyapunov–Kroasovskii theory, and the gains of the observer and controller are obtained by linear matrix inequalities. The feasibility of the proposed scheme is verified by the networked motor control system. The proposed weighted average event-triggered fault-tolerant control scheme can reduce the data transmission without affecting system performance. Meanwhile, it not only has fault-tolerant control performance but also reduces the influence of nonlinear factors on the system output.

Hybrid deep learning diagonal recurrent neural network controller for nonlinear systems

In the present paper, a hybrid deep learning diagonal recurrent neural network controller (HDL-DRNNC) is proposed for nonlinear systems. The proposed HDL-DRNNC structure consists of a diagonal recurrent neural network (DRNN), whose initial values can be obtained through deep learning (DL). The DL algorithm, which is used in this study, is a hybrid algorithm that is based on a self-organizing map of the Kohonen procedure and restricted Boltzmann machine. The updating weights of the DRNN of the proposed algorithm are developed using the Lyapunov stability criterion. In this concern, simulation tasks such as disturbance signals and parameter variations are performed on mathematical and physical systems to improve the performance and the robustness of the proposed controller. It is clear from the results that the performance of the proposed controller is better than other existent controllers.

Event‐triggered control of quasi‐LPV systems with communication delays

AbstractThis paper addresses the dynamic periodic event‐triggered control for local stabilization of nonlinear networked control systems with communication delays. Based on a polytopic quasi‐linear parameter‐varying (quasi‐LPV) model of the nonlinear plant and the Lyapunov–Krasovskii stability theory, a local stability analysis condition is established. Then a constructive co‐design condition is proposed to jointly design the state‐feedback control law and the trigger rule. The local asymptotic stability of the closed‐loop equilibrium point of interest is ensured with a guaranteed region of attraction where trajectories remain inside even in the presence of communication delays. An optimization procedure is proposed to perform the co‐design considering the objectives of enlarging the guaranteed region of attraction and reducing the number of transmissions. Numerical examples indicate a trade‐off between these two objectives. Also, the examples illustrate the effectiveness of the proposed dynamic event‐triggered control co‐design approach over both its static counterpart and periodic time‐triggering mechanisms.

Observer-Based Hybrid-Triggered Control for Nonlinear Networked Control Systems with Disturbances

Observer-Based Hybrid-Triggered Control for Nonlinear Networked Control Systems with Disturbances

Data-Based Security Fault Tolerant Iterative Learning Control under Denial-of-Service Attacks

This paper mainly studies the data-based security fault tolerant iterative learning control (SFTILC) problem of nonlinear networked control systems (NCSs) under sensor failures and denial-of-service (DoS) attacks. Firstly, the radial basis function neural network (RBFNN) is used to approximate the sensor failure function and a DoS attack compensation mechanism is proposed in the iterative domain to lessen the impact of DoS attacks. Then, using the dynamic linearization technology, the nonlinear system considering failures and network attacks is transformed into a linear data model. Further, based on the designed linearization model, a new data-based SFTILC algorithm is designed to ensure the satisfactory tracking performance of the system. This process only uses the input and output data of the system, and the stability of the system is proved by using the compression mapping principle. Finally, a digital simulation is used to demonstrate the effectiveness of the proposed SFTILC algorithm.

Adaptive event-triggered [formula omitted] fuzzy filter design for nonlinear networked systems via asymmetric LKF approach

This paper studies the problem of the fuzzy H∞ filter design for nonlinear networked control systems through event-triggered communication (ETC) scheme. Firstly, an improved adaptive ETC scheme is proposed to save communication resources. Secondly, an asymmetric Lyapunov-Krasovskii functional (LKF) method is introduced in the H∞ performance analysis of filter error systems. Then, a new sufficient condition is obtained to meet the H∞ performance by combining the method with membership-function-dependent approach. Further, a relaxed co-design method of the corresponding filter and event-triggering parameters is obtained. Finally, two numerical examples are provided to verify the advantage of the new approaches.

Hybrid-triggered H∞ Fault Detection for Distributed Time-delay Systems with Communication Quantization Based on T-S Fuzzy Model

In the network environment, the time-triggered mechanism wastes limited bandwidth resources due to the transmission of all sampled data to the network. The event-triggered mechanism may increase system errors due to ignoring factors such as changes in network utilization. In order to reduce the design conservatism, this paper studies the design of a hybrid-triggered H∞ fault detection filter for a class of nonlinear networked control systems described by Takagi-Sugeno (T-S) fuzzy model, and applies quantization techniques in the communication channel. Using the Lyapunov-Krasovskii functional and integral inequality methods, new results on the stability and H∞ performance of fuzzy fault detection systems are presented. In particular, the designed fault detection filter has a specific H∞ noise attenuation level γ. The final simulation results verify the effectiveness of the design.

Dynamic event-triggered control for nonlinear NCSs subject to DoS attacks

In this study, a dynamic event-triggered control problem is addressed for nonlinear networked control systems (NCSs) subject to denial-of-service (DoS) attacks. Assume that data from the plant to the controller is transmitted via a wireless transmission channel under malicious DoS attacks characterized by frequency and duration properties. On the premise of ensuring the stability and minimum inter-event time (MIET) of the systems, dynamic event-triggered mechanisms (DETMs) are proposed for the hybrid dynamic system to withstand a certain degree of DoS attacks. Three event-triggered schemes are designed for the most existing state-based control systems which further enlarge the inter-event times, and the stabilization conditions of hybrid dynamic system are given. Finally, illustrative examples are provided to verify the effectiveness of the presented theoretical results.

Interval observer-based supervision of nonlinear networked control systems

Networked control system (NCS) is a multidisciplinary area that attracts increasing attention today. In this paper, we deal with remote supervision of a nonlinear networked control systems class subject to network imperfections. Different from many existing researches that consider only the problem of small and/or constant communication delays, we focus on large and time-varying network delays problem in both measurement and control channels. The proposed method is a set-membership estimation-based predictor approach computing a guaranteed set of admissible state values when the uncertainties (i.e. measurement noises and system disturbances) are considered unknown but bounded with a priori known bounds. The state prediction strategy is used to compensate the effect of transmission delays. Finally, the theoretical results are validated through a numerical example.

Interval observer-based supervision of nonlinear networked control systems

Interval observer-based supervision of nonlinear networked control systems

Fuzzy event-triggered control for nonlinear networked control systems

This paper is focus on an event-triggered control design problem for nonlinear networked control systems with missing data and transmission delay in the interval type-2 (IT2) fuzzy form. An event-triggered controller is presented under a sampled-state-error mechanism. By dividing the event-triggered interval into some subsets, stability analysis is carried out based on Lyapunov-Krasovskii functional (LKF), and the stability of the closed-loop system is ensured. The proposed design is applied to the continuous stirred tank reactor system (CSTR) and the manipulator system. The control strategy is effective, and the merit of the event-triggered mechanism is indicated.

Design of Robust Dynamic Output Feedback Event-Triggering Controllers for Nonlinear Uncertain Systems

This paper presents a design of dynamic output feedback event-triggering control for nonlinear uncertain networked control systems. The plant and actuator asynchronously transmit the measurement and control signals over two different communication channels. We address the norm-bounded time-varying parameter uncertainties in a nonlinear plant. First, considering the exogenous disturbances and noises in the control and measurement signals, sufficient conditions for the <i>L</i>₂ stability of the nonlinear networked control systems are given in the presence of the uncertainties. Then, we propose design conditions to choose the dynamic output feedback control and triggering laws in terms of linear matrix inequalities (LMIs). The proposed conditions enable the controller and event-triggering parameters to be jointly optimized to lessen the number of transmissions, guaranteeing a certain level of <i>L</i>₂ gain. Numerical examples demonstrate the effectiveness of the proposed method.