Networked control systems are spatially distributed systems in which the communication between sensors, actuators, and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices, increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems, process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The &#x2018 control over networks &#x2019 is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of &#x2018 control over networks &#x2019 , providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research.

Networked control systems: a survey of trends and techniques

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems

Summary
This paper proposes a novel adaptive backstepping control method for parametric strict-feedback nonlinear systems with event-sampled state and input vectors via impulsive dynamical systems tools. In the design procedure, both the parameter estimator and the controller are aperiodically updated only at the event-sampled instants. An adaptive event sampling condition is designed to determine the event sampling instants. A positive lower bound on the minimal intersample time is provided to avoid Zeno behavior. The closed-loop stability of the adaptive event-triggered control system is rigorously proved via Lyapunov analysis for both the continuous and jump dynamics. Compared with the periodic updates in the traditional adaptive backstepping design, the proposed method can reduce the computation and the transmission cost. The effectiveness of the proposed method is illustrated using 2 simulation examples.

Event-triggered adaptive backstepping control for parametric strict-feedback nonlinear systems

The event-triggered control problem for switched linear system is addressed in this study. The periodical sampling scheme and event-triggering condition are incorporated in the closed-loop. The feedback control updates its value only at sampling instants as long as event-triggering condition is satisfied as well. In addition, the switchings are only allowed to occur at sampling instants and meanwhile the switching condition is satisfied. Three equivalent sufficient conditions are proposed to ensure the asymptotic stability of switched systems. In particular, one condition has a promising feature of affineness in system matrices, and as a consequence, it is extended to robust sampling case and ℒ
 2
-gain analysis. Several examples are provided to illustrate the authors' results.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cta.2016.0672

Event-triggered control for continuous-time switched linear systems

Input-to-state stability of integral-based event-triggered control for linear plants

This article studies event-triggered control for the prescribed-time bipartite consensus of first-order multiagent systems. For each agent, the new event-triggered control law and triggering condition are constructed without continuous interneighboring communication. Based on the Lyapunov stability theory and the algebraic graph theory, permissible value ranges of the designed parameters are established to guarantee that all agents reach bipartite consensus in a completely prespecified time. Moreover, a comprehensive theoretical discussion is provided to show that the Zeno behavior can be excluded during the whole time span except the prespecified settling time T. The simulation results demonstrate the feasibility of the provided methods.

Prescribed-Time Event-Triggered Bipartite Consensus of Multiagent Systems.

In this article, the bipartite consensus of first-order multiagent systems with a connected structurally balanced signed graph is studied. To reduce the communications among agents, a distributed event-triggered control law is proposed, where the event-triggering condition of each agent only uses its own state and the sampled states of its neighbours, and no knowledge of the global network topology is required. By relating to the nonexistence of some finite-time convergence, a novel analysis is given to show that there is no Zeno behavior in the proposed event-triggered multiagent system. Then, from the Lyapunov stability theory and the algebraic graph theory, it is proved that all agents can reach agreement with an identical magnitude but opposite signs. Finally, a numerical example is given to illustrate the efficiency and feasibility of the proposed results.

Event-Triggered Bipartite Consensus for Multiagent Systems: A Zeno-Free Analysis

In this paper, the effects of bounded disturbances on decentralized event-triggered control systems are studied. The input-to-state (practical) stability of integral-based event-triggered control systems and dynamic event-triggered control systems is analyzed in a uniform framework by utilizing a new Lyapunov functional approach. An estimation on the upper bound of the input-to-state stability gain is given analytically. First, Zeno behavior is excluded with the time-regularized mechanisms, that is, a prespecified lower bound of inter-event times is introduced. Then, the conditions are presented under which the considered event-triggered control systems ensure Zeno-freeness without time regularization. Finally, a numerical example is given to illustrate the efficiency and feasibility of the proposed results.

Hao Yu

Papers

Input-to-state stability of integral-based event-triggered control for linear plants

Prescribed-Time Event-Triggered Bipartite Consensus of Multiagent Systems.

Event-Triggered Bipartite Consensus for Multiagent Systems: A Zeno-Free Analysis

A Uniform Analysis on Input-to-State Stability of Decentralized Event-Triggered Control Systems

Design of data-driven PID controllers with adaptive updating rules