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

Introduction To Stochastic Calculus With Applications

This note is devoted to study the stabilization problem of stochastic nonlinear delay systems with exogenous disturbances and the event-triggered feedback control. By introducing the notation of input-to-state practical stability and an event-triggered strategy, we establish the input-to-state practically exponential mean-square stability of the suggested system. Moreover, we investigate the stabilization result by designing the feedback gain matrix and the event-triggered feedback controller, which is expressed in terms of linear matrix inequalities. Also, the lower bounds of interexecution times by the proposed event-triggered control method are obtained. Finally, an example is given to show the effectiveness of the proposed method. Compared with a large number of results for discrete-time stochastic systems, only a few results have appeared on the event-triggered control for continuous-time stochastic systems. In particular, there have been no published papers on the event-triggered control for continuous-time stochastic delay systems. This note is a first try to fill the gap on the topic.

Stabilization of Stochastic Nonlinear Delay Systems With Exogenous Disturbances and the Event-Triggered Feedback Control

In this paper, the consensus tracking problem is investigated for a class of continuous switched stochastic nonlinear multiagent systems with an event-triggered control strategy. For continuous stochastic multiagent systems via event-triggered protocols, it is rather difficult to avoid the Zeno behavior by the existing methods. Thus, we propose a new protocol design framework for the underlying systems. It is proven that follower agents can almost surely track the given leader signal with bounded errors and no agent exhibits the Zeno behavior by the given control scheme. Finally, two numerical examples are given to illustrate the effectiveness and advantages of the new design techniques.

Consensus Tracking Control of Switched Stochastic Nonlinear Multiagent Systems via Event-Triggered Strategy

This paper is concerned with the problem of global output-feedback control for a class of stochastic nonlinear time-delay systems in the presence of input saturation and unmeasurable states. As a distinctive feature, the growth assumptions imposed on the drift and diffusion terms are proven to be unnecessary, which can be removed through a technical lemma. In addition, by introducing an auxiliary system whose order is the same as the considered system, and using Lyapunov–Krasovskii functional, the adverse effects generated by input saturation and time-varying delay are eliminated. Then, based on state-observer and backstepping recursive design, an output-feedback controller is constructed to render the closed-loop system be globally bounded almost surely. Particularly, instead of converging to an arbitrarily small neighborhood of zero as in related results, the tracking error is ensured to be tuned by the design parameters and an input saturation error in the mean quartic sense. Finally, a stochastic chemical reactor system is established and shown to demonstrate the effectiveness of the proposed scheme.

Output-Feedback Control for Stochastic Nonlinear Systems Subject to Input Saturation and Time-Varying Delay

In this technical note, the problem of adaptive tracking control is investigated for a class of stochastic uncertain nonlinear systems in the presence of input saturation. To analyze the effect of input saturation, an auxiliary system is employed. With the help of backstepping technique, an adaptive stochastic tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved almost surely. Moreover, distinct from most of the existing results, the ultimate tracking error can be bounded by an explicit function of design parameters and input saturation error (the error between the control input and saturated input) in the mean quartic sense. Finally, an example is given to show the effectiveness of the proposed scheme.

Adaptive Tracking Control for a Class of Stochastic Uncertain Nonlinear Systems With Input Saturation

This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation

Event-triggered control for stochastic nonlinear systems

The problem of decentralized adaptive output tracking control of a class ofinterconnected stochastic nonlinear systems is considered. In the control design, decentralized state observers and backstepping techniques are applied.To eliminate the influences of interactions with other subsystems, a differentiable function is employed. It is shown that the designed local adaptivecontrollers can ensure that all the signals in the closed-loop system arebounded in probability. Furthermore, the tracking errors can be limited to asmall residual set around the origin in the fourth moment sense and can be adjusted by choosing suitable design parameters.

Decentralized backstepping adaptive output tracking of large-scale stochastic nonlinear systems

This note focuses on determining the value of the maximum allowable sampling period (MASP) that guarantees the stability of stochastic nonlinear sampled-data systems with emulated controllers. Two methods are proposed to compute MASP, one based on sufficient Lyapunov-like conditions on stabilization of stochastic nonlinear systems in mean square and the other from applying Barbalat's Lemma. Comparison studies are made and illustrated for the two methods by a numerical example.

Yong-Feng Gao

Papers

Adaptive Tracking Control for a Class of Stochastic Uncertain Nonlinear Systems With Input Saturation

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation

Event-triggered control for stochastic nonlinear systems

Decentralized backstepping adaptive output tracking of large-scale stochastic nonlinear systems

Estimation of Sampling Period for Stochastic Nonlinear Sampled-Data Systems With Emulated Controllers