Nonlinear Networked Control Systems Research Articles

Dynamic self-triggered control for nonlinear systems with delays

Self-triggered control (STC) is a resource efficient approach to determine sampling instants for Networked Control Systems (NCS). Recently, a dynamic STC strategy based on hybrid Lyapunov functions for nonlinear NCS has been proposed in Hertneck and Allgöwer (2021b), however with limitation to NCS without transmission delays. In this paper, we extend this strategy for nonlinear NCS with transmission delays. The capability to handle systems with delays makes it possible to use the resulting dynamic STC mechanism in many practical scenarios where instant transmissions without delays cannot be guaranteed. The proposed dynamic STC mechanism guarantees stability despite bounded transmission delays. The effectiveness of the mechanism is illustrated with a numerical example and compared to state-of-the art literature.

Quantization level based event-triggered control with measurement uncertainties

In this paper, the quantization level based event-triggered control algorithm is novelly proposed and stability of the considered system could be guaranteed on account of hysteresis quantizer under measurement uncertainties. By carefully exploring the characteristics of nonlinear networked control systems, hysteresis quantizer is selected to avoid potential chatterings caused by frequent quantization level transitions. Two kinds of situations, one is networked control system without considering measurement uncertainties, and the other takes measurement uncertainties into consideration, are separately discussed under the quantization level based event-triggered control framework. By thoroughly digging out the relationship between quantizer structure and event-triggered control mechanism, two quantization level based event-triggered control mechanisms are put forward under different situations. Moreover, no matter whether measurement uncertainties are taken into account, system stability could always be guaranteed by our proposed criteria and Zeno behavior would never happen with our method. Finally, simulations show the feasibility and superiority of our proposed algorithms.

Security Analysis of Linearization for Nonlinear Networked Control Systems Under DoS

We explore a security analysis of nonlinear networked control systems under denial-of-service (DoS) attacks. In particular, we focus on the vulnerability of a linearization approach in a stabilization problem. When linearization-based control is used, DoS attacks can make the state leave the region of attraction. This situation can occur when the initial state lies outside a certain region around the equilibrium, the size of which depends on the strength of the attacks on the network. In this article, we first derive a sufficient condition for local stability of a nonlinear system under averagely constrained DoS attacks. Then, we investigate the region of attraction and derive an explicit relation between the initial states and the DoS parameters to guarantee convergence of the state trajectories. Furthermore, we investigate a destabilization problem from the perspective of malicious attackers and present an instability condition. By a numerical example, we demonstrate a new insight foattackers to induce undesired behaviors of the control system.

Model‐free adaptive tracking control for networked nonlinear systems with data dropout

AbstractThe data‐driven tracking control problem is investigated for networked nonlinear systems subjected to data dropout. The desired time‐varying output trajectory is considered in this article, which is more general than the constant trajectory. In order to improve the tracking performance, the change rate of tracking error is additionally introduced to the performance index to design model‐free adaptive controller. Accordingly, more adjustable parameters are introduced into the controller. With the help of the approximation ability of RBFNN, an RBFNN estimation algorithm is designed to compensate for the adverse effects of data dropout. It is shown that the proposed controller can guarantee the system output to track the desired time‐varying output trajectory. Finally, two numerical simulations are provided to illustrate the effectiveness of the proposed approach.

A recurrent wavelet-based brain emotional learning network controller for nonlinear systems

Conventional control systems often suffer from the coexistence of nonlinearity and uncertainty. This paper proposes a novel brain emotional neural network to support addressing such challenges. The proposed network integrates a wavelet neural network into a conventional brain emotional learning network. This is further enhanced by the introduction of a recurrent structure to employ the two networks as the two channels of the brain emotional learning network. The proposed network therefore combines the advantages of the wavelet function, the recurrent mechanism, and the brain emotional learning system, for optimal performance on nonlinear problems under uncertain environments. The proposed network works with a bounding compensator to mimic an ideal controller, and the parameters are updated based on the laws derived from the Lyapunov stability analysis theory. The proposed system was applied to two uncertain nonlinear systems, including a Duffing-Homes chaotic system and a simulated 3-DOF spherical joint robot. The experiments demonstrated that the proposed system outperformed other popular neural-network-based control systems, indicating the superiority of the proposed system.

Unknown Input Observers for Discretized Systems With Application to Networked Systems Corrupted by Sparse Malicious Packet Drops

Digital estimators for networked systems are proposed where the plant output measurements and control signals are corrupted by independent sparse malicious packet drop errors. The estimators comprise output sparse error approximators and unknown input observers (UIOs). The advantage of using digital estimators is that in many cases the condition for the existence of an UIO fails for continuous-time (CT) plants while it holds for discretized plants. A class of CT systems for which the existence condition for the UIO holds in the discrete-time (DT) domain is characterized. The proposed digital estimators are tested on a nonlinear networked control system (NCS). As part of our analysis, we study the existence of unknown input observers for discretized systems and show that discretization does not negatively impact the existence of UIOs and in some cases can facilitate the construction of UIOs when they do not exist for the CT systems.

Fault-tolerant control for model-free networked control systems under DoS attacks

This paper studies the fault-tolerant model-free adaptive control (FT-MFAC) problem for a class of single-input single-output (SISO) nonlinear networked control systems (NCSs) under denial-of-service (DoS) attacks. A novel FT-MFAC framework is established with the consideration of DoS attacks and the sensor fault, in which DoS attacks obeying the Bernoulli distribution randomly happen in the sensor-to-controller channel and the sensor fault is approximated by the radial basis function neural network (RBFNN). Based on the proposed framework, an FT-MFAC algorithm that uses only input/output data is proposed to guarantee that the output tracking error is bounded in the sense of mean square. Finally, the effectiveness of the proposed algorithm is illustrated by a simulation.

Event-triggered fault detection for nonlinear descriptor networked control systems

This paper investigates the problem of filter-based fault detection (FD) for stochastic nonlinear descriptor networked control systems (NCSs). Based on the T-S fuzzy dynamic modeling technique, the nonlinear descriptor NCS is transformed into a combination of local linear models. Then, to save the network resources, a new adaptive event-triggered mechanism is presented to determine whether the sampled data is to be transmitted. Considering network-induced delay, data packet dropout, and asynchronous premise variables, a time-delay augmented system is established to improve the detection performance. The additional item caused by data packet dropout is regarded as a disturbance, and the effect of this part is attenuated by using the H∞ method. A sufficient condition is proposed to guarantee the admissibility of the augmented system, meanwhile, the desired filter parameters are obtained. Finally, simulation results are provided to demonstrate the feasibility of the proposed strategy.

Event-triggered H–/L∞ fault detection observer design for discrete-time Lipschitz nonlinear networked control systems in finite-frequency domain

This paper proposes an event-triggered fault detection observer (FDO) design method for discrete-time Lipschitz nonlinear networked control systems (NCSs) in finite-frequency domain. First, a discrete event-triggered transmission scheme is proposed to mitigate the utility of limited network bandwidth. Second, with the aid of a reformulated Lipschitz property, the nonlinear error dynamics are converted into a linear parameter varying (LPV) networked system model. Third, based on this model, the finite-frequency index is used to measure the worst-case fault sensitivity performance and the norm from unknown disturbance to residual is used to measure disturbance robustness performance. Next, a residual evaluation and a dynamic threshold are synthesised based on the norm. Furthermore, sufficient conditions of the FDO design are derived and transformed by a set of linear matrix inequalities (LMIs). The proposed FDO design method can significantly reduce the data transmission to relieve the communication pressure, and can also achieve better FD performance than the full frequency domain. Finally, A numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.

Quantized data‐based iterative learning control under denial‐of‐service attacks

AbstractThis article mainly studies the quantized data‐based iterative learning tracking control (QDBILTC) problem of nonlinear networked control systems in the presence of signals quantization and denial‐of‐service (DoS) attacks. The quantizer considered here is static with the logarithmic form. First, an estimate output attack compensation mechanism is designed to compensate for the effect of DoS attacks based on the extended dynamic linearization method. Then, a QDBILTC algorithm is developed to guarantee the system tracking performance and the bounded input and bounded output stability in mean‐square sense. The process of designing the QDBILTC algorithm only uses the input and output data of the system, and the proof of which uses the compression mapping principle and the mathematical induction. The effectiveness of the proposed QDBILTC algorithm is illustrated by a digital simulation.

Novel asynchronous premise reconstruction based adaptive event-triggered control for fuzzy systems with actuator failure

This paper explores the adaptive event-triggered (AET) based variable gains controller design problem for a category of discrete-time nonlinear networked control systems (NCSs) with actuator failure. An AET communication scheme is applied for NCSs to reduce the utilization of limited network bandwidth. For overcoming the asynchronous issue of premise variable caused by AET scheme, a novel asynchronous premise reconstruction technique is introduced. Meanwhile, a new variable gains controller is designed subject to AET approach, where the controller gains will be automatically updated by executing the online iteration algorithm. According to a discontinuous Lyapunov function, sufficient conditions are given to ensure that the closed-loop system is asymptotically stable and satisfies H∞ performance. Finally, in the simulation results, the validity of the proposed control method is verified and it is shown that the proposed scheme can achieve better system performances than the existing design technique with fixed threshold.

Nonfragile peak-to-peak filtering for discrete-time Takagi-Sugeno fuzzy systems with dynamic quantizations

This paper investigates the problem of nonfragile peak-to-peak filtering for a class of discrete-time nonlinear networked control systems with dynamic quantizations. The Takagi-Sugeno fuzzy model is applied to approximate the considered nonlinear networked control systems. The perturbations are also considered in the peak-to-peak filter to be designed. Unlike most work about the peak-to-peak filtering for dynamic systems with quantization, both the performance output signal and measurement output signal are quantized by two different dynamic quantizers in our work. The main attention is to design the nonfragile peak-to-peak filter which guarantees the filtering error system to be asymptotically stable and possess a peak-to-peak performance index. By employing the fuzzy basis-dependent Lyapunov function approach and the S-procedure, new sufficient conditions about designing the nonfragile peak-to-peak filter have been established, which are expressed in the form of linear matrix inequalities. In the end, a numerical example is offered to verify the effectiveness of the designed nonfragile peak-to-peak filter.

An Input Delay Approach to Interval Type-2 Fuzzy Exponential Stabilization for Nonlinear Unreliable Networked Sampled-Data Control Systems

This paper is devoted to the interval type-2 (IT2) fuzzy exponential stability for nonlinear networked sampled-data control systems with random communication links. By using the input delay approach, the designed networked IT2 fuzzy sampled-data controller can be applied in the continuous-time controlled plant, and the continuous-time Lyapunov-Krasovskii functional (LKF) is constructed. Based on the LKF theory, the stability analysis is conducted in the sense of mathematical expectation, and the sufficient conditions are determined in terms of the linear matrix inequalities. Then, the IT2 fuzzy networked controller is developed such that the networked closed-loop control system is exponentially stable. Finally, the simulation results are used to demonstrate the efficiency of the proposed design. The merits of the proposed algorithm are also shown by some comparative results.

Observer-based robust fuzzy control of nonlinear networked systems with actuator saturation

In this article, the aim is to study the observer-based robust fuzzy control of nonlinear systems subject to actuator saturation via network communication. Unlike most existing results, system outputs are sufficiently processed by an adaptive event-triggered mechanism in an aperiodic sampling manner. By utilizing Takagi–Sugeno (T–S) fuzzy description, a fuzzy observer is established based on the sampled outputs suffering from network-induced delays. A saturated fuzzy control law is then derived from the estimated states of the observer. Moreover, by using ℒ∞ performance index, the adverse effect of persistent bounded disturbance is substantially attenuated. A novel Lyapunov functional, fully considering the characteristics of aperiodic event-triggered scheme and transmission delays, is investigated to analyze system stability and synthesize the desired controller. In view of the imperfect premise matching, the knowledge of asynchronous membership functions is imported into the derivation of a novel set of sufficient conditions for controller synthesis. Finally, the proposed observer-based control algorithm is verified by an illustrative example and simulation results.

Quantized Guaranteed Cost Output Feedback Control for Nonlinear Networked Control Systems and Its Applications

The quantized guaranteed cost static output feedback control problem is investigated for a class of discrete-time nonlinear networked control systems in this article. In this article, the Takagi–Sugeno fuzzy model is put to use for the representation of considered nonlinear networked control systems, where local nonlinear models instead of local linear models are used in the Takagi–Sugeno fuzzy model. Two different dynamic quantizers are applied to quantize the control input and measurement output, respectively. Different from some previous work, a novel guaranteed cost performance function including the quantized control input is used in this article. Through using the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$S$</tex-math></inline-formula> -procedure and introducing some auxiliary scalars, sufficient conditions for the design of guaranteed cost static output feedback controller and dynamic quantizers are obtained in the form of linear matrix inequalities. Finally, the applicability of the proposed method is illustrated through the application in nonlinear mass-spring-damper mechanical system.

Active Event-Triggered Control for Nonlinear Networked Control Systems With Communication Constraints.

In this paper, a novel reference input and hysteresis quantizer-based active event-triggered control (RIHQAETC) scheme is proposed for nonlinear networked control systems with quantizer, networked induced delay, and packet dropout. Different from the traditional methods, such a design method is constructed involving the structure of the hysteresis quantizer. In view of the network induced delay and the potential packet dropout, our RIHQAETC method is designed to actively compensate the negative effects caused by these two issues. The corresponding coder and decoder are also excogitated on account of the potential packet dropout based on the proposed triggering mechanism. Furthermore, the transmission of the important triggering information can be ensured as well as the finite-gain L2 stability performance. It is demonstrated by an example that our RIHQAETC method presents a more balanced updating frequency between the plant and the controller output sides and reduces the number of total triggering.

Hybrid‐triggered fault detection filter design for networked Takagi–Sugeno fuzzy systems subject to persistent heavy noise disturbance

SummaryIn the network environment, the single time‐triggered scheme wastes limited bandwidth resources due to all the sampled data are transmitted to the networks, and the single event‐triggered scheme may increase system error because of ignoring factors such as changes in network utilization. To reduce the design conservatism, this paper is concerned with the hybrid‐triggered L1 fault detection filter design for a class of nonlinear networked control systems (NCSs) described by Takagi–Sugeno (T‐S) fuzzy model. Taking the effects of time‐triggered scheme and event‐triggered scheme into consideration simultaneously, we construct a fuzzy fault detection system. New results on stability and L1 performance are proposed for fuzzy fault detection system by exploiting the Lyapunov–Krasovskii functional and by means of the integral inequality method. Specially, attention is focused on the design of fault detection filter that guarantees a prescribed L1 noise attenuation level . Finally, two examples are presented to demonstrate the effectiveness of the proposed method.

Dynamic output feedback control for interval type-2 fuzzy systems against DoS attacks and sensor failures

This article focuses on investigating a dynamic output feedback control issue for uncertain nonlinear networked control systems (NCSs) in the presence of Denial-of-Service (DoS) attacks and sensor failures. By using the low and upper membership functions (LUMFs) of interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model, the uncertainties existing in the considered NCSs are depicted effectively. Based on the IT2 fuzzy system, a switching fuzzy model is further established to correspond to different DoS attack scenarios. According to the average dwell-time approach and Lyapunov stability theory, an IT2 fuzzy dynamic output feedback control scheme is proposed so that the exponential stability of the considered NCSs can be achieved regardless of DoS attacks and sensor failures. Lastly, illustrative examples are presented to confirm the theoretical results proposed in this paper.

Event-triggered [formula omitted] filtering for nonlinear networked control systems via T-S fuzzy model approach

This paper tackles the event-triggering filtering problem for a class of nonlinear networked control systems subject to the prescribed disturbance attenuation level. To alleviate the data transmission burden of communication channels, an event-triggering mechanism is adopted, where the data can be transmitted only if certain condition is fulfilled. The T-S fuzzy model approach is utilized to approximate the nonlinear dynamics. It is the purpose of this paper to design a filter for the addressed nonlinear system ensuring that the filtering error system is asymptotically stable whereas the prespecified H∞ criterion is guaranteed. By using Lyapunov approach in combination with matrix analysis method, the sufficient conditions are established for the existence of desired filtering parameters in terms of the solvability of certain linear matrix inequalities. Finally, a numerical simulation example is put forward to demonstrate the validity and effectiveness of the developed theoretical results.

Hybrid-triggered interval type-2 fuzzy control for networked systems under attacks

In this paper, the security control problem is considered for nonlinear networked control systems under cyber attacks. The nonlinearities are described by interval type-2 fuzzy models. To enhance bandwidth utilization and improve network control performance, a hybrid-triggered scheme is proposed. The networked control systems contain parametric uncertainties and time delays and are subject to external disturbances and cyber attacks. A hybrid-triggered-based control method is established to ensure the robust stability and a prescribed performance of the resulting closed-loop systems against attacks. Numerical simulation and a practical example of the bolt-tightening tool are provided to illustrate the effectiveness of the new control design method.