In control theory using the state-space method, it is often assumed that a matrix is of full rank to further mathematical development. Few people stop to ask two questions: (1) How far is the ‘distance’ between the given full-rank matrix and a non-full-rank matrix?, and (2) How does this ‘distance’ affect control? In robust system analysis and design, in addition to verifying that a system is stable, one also measures how far it is from an unstable system. The simplest stability measurement for a single-input-single-output (SISO) linear system is the gain margin and phase margin. Similarly, beyond a ‘Yes’ or ‘No’ answer, for a full-rank matrix in control, we should ask the above two questions. Pursuing such questions leads to a lot of interesting and useful results. Some of them are well-documented in the literature; some are yet to be fully explored. This paper illustrates some existing research and proposes some future studies. In general, we can review all control lemmas and theorems based on matrix full-rank conditions to explore further studies. The study can also extend to non-linear systems. The basic nonlinear system controllability (observability) tests are based on if the relevant matrices, constructed using Lie Bracket (Lie Derivative), are of full rank. Furthermore, similar studies can be on another important matrix property: positiveness, and on more challenging research into the degrees of controllability and observability for networked control systems.

Human Learning Optimization (HLO) is a simple yet powerful meta-heuristic developed based on a simplified human learning model. Many cognitive activities of humans contain an element of reasoning, and with reasoning, humans can gain deeper information on problems to boost learning performance. Inspired by this fact, this paper proposes a novel human learning optimization algorithm with reasoning learning (HLORL), in which a social reasoning learning operator (SRLO) is developed by using multiple social information sources to improve the global search ability of the algorithm. A parameter study is performed to give the recommended values of the control parameters. It also analyzes and discusses the role and function of the social reasoning learning operator. Finally, the proposed HLORL is applied to solve the CEC14 benchmark functions and 0-1 knapsack problems. The performance of HLORL is compared with the previous HLO variants and other state-of-art metaheuristics. The experimental results demonstrate that the proposed HLORL has significant advantages over the compared algorithms.

We here investigate the secure control of networked control systems developing a new dynamic watermarking (DW) scheme. First, the weaknesses of the conventional DW scheme are revealed, and the tradeoff between the effectiveness of false data injection attack (FDIA) detection and system performance loss is analyzed. Second, we propose a new DW scheme, and its attack detection capability is interrogated using the additive distortion power of a closed-loop system. Furthermore, the FDIA detection effectiveness of the closed-loop system is analyzed using auto/cross-covariance of the signals, where the positive correlation between the FDIA detection effectiveness and the watermarking intensity is measured. Third, the tolerance capacity of FDIA against the closed-loop system is investigated, and theoretical analysis shows that the system performance can be recovered from FDIA using our new DW scheme. Finally, the experimental results from a networked inverted pendulum system demonstrate the validity of our proposed scheme.

X-ray images of castings are widely used in manufacturing for quality assurance. This article investigates the X-ray-image-based defective detection. The main contributions in this article are twofold: first, a new full-image method is proposed to classify defective castings and nondefective ones; and second, by combining two technologies, spatial attention mechanism and bilinear pooling used in deep convolutional neural networks (CNNs), a new spatial attention bilinear CNN is proposed to enhance the representation power of CNN. To validate the above initiatives, extensive experimental studies have been carried out to show the advantages of the new method over a number of existing ones.

This short article presents an opinion that control system study up to date can be divided into four generations; namely, 1 transfer function based; 2 state-space based; 3 networked control systems; and 4 control in the new AI era.

In this paper, we presented a WNCS co-simulation platform based on OPNET/Simulink to verify the validity of the theory and method proposed in the study of wireless network control system (WNCS). The platform combines OPNET with Simulink, and produces the mathematical model of the control system by Simulink. OPNET simulates the network part, forming a co-simulation platform based on OPNET and Simulink. In order to simulate the real network environment more accurately, this paper added the Mobile Ad Hoc Network Routing Protocol (MANET) to the platform and carried on the secondary development of it, so as to realize the co-simulation of the control system and network environment under the framework of network protocol. Finally, through the simulation of the single-stage inverted pendulum control system in the wireless network environment, the effectiveness and good scalability of the platform were verified.

This paper is motivated by a recently published IEEE AC paper and its targeted applications: “Distributed Synthesis of Local Controllers for Networked Systems with Arbitrary Interconnection Topologies”. This is a very interesting work in this area. However, the results presented in the IEEE paper have two major limitations: (1) it only applies to linear systems, and (2) robustness is only discussed in a remark without further investigation. In the work presented in this paper, with the same main features of the approach in the IEEE paper: “local and scalable”, we have applied our design to a class of non-linear systems. This is demonstrated by controller design for a system of N-inverted pendulums coupled by N-1 springs. Despite this achievement, our work still has two limitations: (1) it only applies to a class of nonlinear systems, and (2) although we have studied the robustness of our design in some detail, a systematic and theoretical result is still yet to be developed. These issues and planned future work are discussed in the paper.

To improve the security of smart grids (SGs) by finding the system vulnerability, this paper investigates the sparse attack vectors' construction method for malicious false data injection attack (FDIA). The drawbacks of the existing attack vector construction methods include avoiding discussing the feasible region and validity of the attack vector. For the above drawbacks, this paper has three main contributions: (1) To construct the appropriate attack evading bad data detection (BDD), the feasible region of the attack vector is proved by projection transformation theory. The acquisition of the feasible region can help the defender to formulate the defense strategy; (2) an effective attack is proposed and the constraint of effectiveness is obtained using norm theory; (3) the domain of the state variations caused by the attack vector in the feasible region is calculated, while the singular value decomposition method is adopted. Finally, an attack vector is constructed based on l(0)-norm using OMP algorithms in the feasible domain. Simulation results confirm the feasibility and effectiveness of the proposed technique.

This paper deals with the modelling and control for wind turbine combined with a battery energy storage system (WT/BESS). A proportional-integral (PI) controller of pitch angle is applied to adjust the output power of WT, and a method for battery scheduling is presented for maintaining the state of charging (SOC) of BESS. When the battery level is below the lower limit, we increase the expected output power of wind turbine through raising the operation point to charge the battery. Considering the effect of charging/discharging, a switched linear system model with two equilibriums is presented firstly for such WT/BESS system. The region stability is analyzed and an approach for estimating the corresponding stable region is also given. The effectiveness of the proposed results is demonstrated by a numerical example.

This paper considers global exponential stabilization (GES) of switched linear discrete-time system under language constraint which is generated by non-deterministic finite state automata. A technique in linear matrix inequalities called S-procedure is employed to provide sufficient conditions of GES which are less conservative than the existing Lyapunov-Metzler condition. Moreover, by revising the construction of Lyapunov matrices and the corresponding switching control policy, a more flexible result is obtained such that stabilization path at each moment might be multiple. Finally, a numerical example is given to illustrate the effectiveness of the proposed results.

This paper considers the global exponential stabilizability (GES) of a switched linear system under language constraints, which can be described by a nondeterministic finite state automaton. Firstly, the automaton is represented as a labeled diagraph to reduce the problem to the GES analysis in strongly connected components. Secondly, we analysis the properties of the lifted labeled diagraph, which can express the dwell time constraints intuitively. Based on the lifted labeled diagraph, we generalize the Lyapunov-Metzler condition to an M-step version, and propose a less conservative condition based on S-procedure. Finally, a numerical example is provided to demonstrate the S-procedure condition.

This paper considers global exponential stabilization (GES) of switched system under language constraint which is generated by a non-deterministic finite state automaton. The S-procedure characterization is employed to provide sufficient conditions of GES which are less conservative than the existing Lyapunov-Metzler condition. Moreover, by revising the construction of Lyapunov matrices and the min-switching control policy, a more flexible result is obtained such that stabilization path at each moment might be multiple. Finally, a numerical example is given to illustrate the effectiveness of the proposed results.

Currently cyber-security has attracted a lot of attention, in particular in wireless industrial control networks (WICNs). In this paper, the stability of wireless networked control systems (WNCSs) under deception attacks is studied with a token-based protocol applied to the data link layer (DLL) of WICNS. Since deception attacks cause the stability problem of WNCSs by changing the data transmitted over wireless network, it is important to detect deception attacks, discard the injected false data and compensate for the missing data (i.e., the discarded original data with the injected false data). The main contributions of this paper are: (1) With respect to the character of the token-based protocol, a switched system model is developed. Different from the traditional switched system where the number of subsystems is fixed, in our new model this number will be changed under deception attacks. (2) For this model, a new Kalman filter (KF) is developed for the purpose of attack detection and the missing data reconstruction. (3) For the given linear feedback WNCSs, when the noise level is below a threshold derived in this paper, the maximum allowable duration of deception attacks is obtained to maintain the exponential stability of the system. Finally, a numerical example based on a linearized model of an inverted pendulum is provided to demonstrate the proposed design.

This paper proposes novel randomized gossip-consensus-based sync (RGCS) algorithms to realize efficient time calibration in dynamic wireless sensor networks (WSNs). First, the unreliable links are described by stochastic connections, reflecting the characteristic of changing connectivity gleaned from dynamic WSNs. Secondly, based on the mutual drift estimation, each pair of activated nodes fully adjusts clock rate and offset to achieve network-wide time synchronization by drawing upon the gossip consensus approach. The converge-to-max criterion is introduced to achieve a much faster convergence speed. The theoretical results on the probabilistic synchronization performance of the RGCS are presented. Thirdly, a Revised-RGCS is developed to counteract the negative impact of bounded delays, because the uncertain delays are always present in practice and would lead to a large deterioration of algorithm performances. Finally, extensive simulations are performed on the MATLAB and OMNeT++ platform for performance evaluation. Simulation results demonstrate that the proposed algorithms are not only efficient for synchronization issues required for dynamic topology changes but also give a better performance in terms of converging speed, collision rate, and the robustness of resisting delay, and outperform other existing protocols.

This paper considers a special class of hybrid system called switching Markov jump linear system. The system transition is governed by two rules. One is Markov chain and the other is a deterministic rule. Furthermore, the transition probability of the Markov chain is not only piecewise but also orchestrated by a deterministic switching rule. In this paper, the mean square stability of the systems is studied when the deterministic switching is subject to two different dwell time conditions, ie, having a lower bound and having both lower and high bounds. The main contributions of this paper are two relevant stability theorems for the systems under study. A numerical example is provided to demonstrate the theoretical results.

This paper is concerned with the security control problem of the networked control system (NCSs) subjected to denial of service (DoS) attacks. In order to guarantee the security performance, this paper treats the influence of packet dropouts due to DoS attacks as a uncertainty of triggering condition. Firstly, a novel resilient triggering strategy by considering the uncertainty of triggering condition caused by DoS attacks is proposed. Secondly, the event-based security controller under the resilient triggering strategy is designed while the DoS-based security performance is preserved. At last, the simulation results show that the proposed resilient triggering strategy is resilient to DoS attacks while guaranteing the security performance.

Because of the high integration of control, communication, computer and network technology, how to deal with various anomaly behaviors of control systems is a problem that should be solved by researchers. Especially some activities such as data injections, DoS attacks and device failure must be considered. Based on the analysis of dynamic behaviors of industrial process control systems with varying process state variables, a data mining method is proposed on summarizing normal behavior features of the control systems. Depending on association rules, a similarity factor is formulated using a real-time data mining method for describing the likeness between real-time frequent itemsets and normal frequent itemsets. Representative values of change behaviors for process variables and the corresponding generation method are illustrated in detail. On the basis of comparison between several real-time frequent itemsets and the normal frequent itemsets, a reliability parameter is given to describe the abnormal status of a control system within a certain time. Simulation results show that the proposed method can detect anomaly behaviors of a process control system in time, which has practical significance in industrial applications.

For the switched model predictive control, this paper reviews the recent research advance. Based on the analysis tools of linear matrix inequality (LMI) and invariant set theory, this paper studies the principle of model predictive control combined with switched system theory, and introduces the related research literature and methods when research plants and performance indexes are switched. Based on the stability and robustness analysis methods of model predictive control and switched system theory, it studies how to ensure the stability and robustness of the system. At the same time, it points out the advantages of switching model predictive control and the challenges it faces in the future development.

In this paper, a new class of switched system, two-level switched system, is studied for its finite-time stability and finite-time boundedness problem. For such switched systems, by combining the basic analysis of finite-time stability with the multi-Lyapunov functions and dwell-time methods in switched systems, in the method of linear matrix inequality, the sufficient conditions and the feedback stabilization method for the switched system to satisfy the finite-time stability under arbitrary switching rules and based on a certain range of dwelling time switching rules are given. Finally, the numerical simulation example is given to verify the correctness of the theory.