Further analysis on network-induced time-varying delay modeling methods used in GPC design

Robust design of multiloop GPC and its application for a cement mixing plant

Networked level control is a very important part in many industries. In this paper, a new method called generalized predictive control (GPC) combined with a queuing-selecting strategy is applied for level control in networked control system (NCS). A distributed model which contains an event-driven controller, and a time-driven sensor and actuator is adopted in the system. The proposed method relieve the degradation of the network control system caused by the network-induced delay . The experiment is carried out on three-coupled-tank over real network to test the proposed method, which verifies the stability and robustness of the proposed method.

Design, Analysis and Real-time Implementation of Networked Predictive Control Systems

This paper is concerned with stability criteria of networked control systems (NCSs) with both the time-varying network-induced delay and data packet dropout taken into account. A continuous time model of NCSs with time-varying and uncertainties is proposed. Based on the dividing of the time-varying delay, a new Lyapunov functional is constructed, and a delay-dependent stability criterion is derived to guarantee the globally asymptotic stability of the networked control systems (NCSs). Expressed in terms of linear matrix inequalities (LMIs), the stability condition can be checked using the numerically efficient Matlab LMI Control Toolbox. Compared with some report methods, no slack matrix variable is introduced and the proposed methods gave a much less conservative maximum allowable delay bound (MADB). A numerical example is provided to demonstrate the effectiveness of the proposed method.

The use of a communication network in a control loop has gained increasing attention in recent years, because it can offer many advantages. One of major challenges in this so-called networked control systems (NCS) is the network-induced delay effect in the control loop. In this paper, a networked control strategy based on generalized predictive control (GPC) is presented, which can compensate for the communication network delays. A stability analysis method for the control strategy is proposed. The simulation results illustrate effectiveness of this method.

Driven by recent telecommunication demand, shared communication channels are more abundant today than ever before. These shared wired/wireless networks for communication are being exploited more and more in control systems to connect sensors, controllers and actuators resulting in so-called networked control systems (NCSs). NCSs replace the more traditional control systems where dedicated point-to-point (wired) connections are being used. The advantages of using NCS technology are inexpensive and easily modifiable communication links which allow control algorithms to be easily implemented in situations where dedicated connections are not possible (either economically or physically). However, the drawback is that the control system is susceptible to undesirable (possibly destabilizing) side-effects such as time-varying transmission intervals, time-varying delays, packet dropouts, quantization and a shared communication medium. These network-induced effects undermine fundamental assumptions on which traditional control theory is built and, therefore, it is essential to develop new techniques and tools that can be used to analyze and/or design control systems which communicate via a shared network. This thesis advances NCS analysis and design methodologies by contributing new theoretical developments, new software tools and new experimental validation results. The first new theoretical development is in the area of analyzing robust stability properties with respect to network-induced effects. A sum of squares (SOS) approach for a class of nonlinear NCSs incorporating bounded time-varying delays, bounded time-varying transmission intervals and a shared communication medium is developed. Mathematical models that describe these nonlinear NCSs are cast into suitable hybrid system formulations. Based on these hybrid system formulations, (families of) Lyapunov functions are constructed using SOS techniques. Amongst other benefits, it is shown that this technique improves the guaranteed robustness margins compared to existing work. The second new theoretical development concerns the design of networkaware decentralized controllers guaranteeing robust stability properties with respect to network-induced effects. We develop one of the first approaches based on semidefinite programming techniques to synthesize stabilizing decentralized observer-based output-feedback controllers for linear plants where the controllers, sensors and actuators are connected via a shared communication network subject to time-varying transmission intervals and delays. To effectively deal with the shared communication medium, a switched observer structure is adopted that switches based on the transmitted measured outputs and a switched controller structure is also adopted that switches based on the transmitted control inputs at each transmission time. By taking a discrete-time switched linear system perspective on modeling these decentralized NCSs, we are able to derive a general model that captures all these networked and decentralized control aspects. We provide linear matrix inequality (LMI)-based synthesis conditions which, if satisfied, provide stabilizing observer-based controllers that are both decentralized and robust to network effects. Regarding new software tools, the first prototype of a toolbox is developed to automate (robust) stability analysis (and controller design) for NCSs. Specifically, it is shown that the toolbox can be employed to efficiently verify if a linear time-invariant (LTI) plant and an LTI controller interconnected with a shared network are robust to certain network imperfections. The main intention of the toolbox is to make the available theory readily accessible to and applicable for the general control community. Additionally, the chosen software structure enables the incorporation of custom models or custom stability/performance analysis conditions in an easy manner, thereby allowing the control community to contribute and to further develop the toolbox. Finally, an experimental case study involving a wirelessly controlled inverted pendulum/cart system is investigated. In particular, the communication network itself is analyzed such that the network-induced effects can be characterized in terms of bounds on the transmission intervals and transmission delays. Based on these bounds, the prototype toolbox is applied to analyze the robustness regions for different performance specifications, which aid in tuning the controller to achieve more closed-loop robustness with respect to the network-induced effects. This leads to a validation of the developed theory in an experimental setting. In addition to the validation of the developed theory, many new insights into the network behavior are obtained and explained, thereby raising new interesting questions for future research on NCSs.

In this paper, the robust H∞ control problem is developed for a class of linear time-varying networked control system (NCS) with uncertainties and external disturbance. In network, the network-induced delay and packet dropouts are simultaneously considered. Firstly, a discrete-time switched system model is established based on the signals transmission delay in network. Then, a time-varying H∞ controller is designed. Such the controller can vary according to delay in network. Furthermore, by constructing delay-dependent Lyapunov-Krasovskii functional, a sufficient condition is given to guarantee that the closed-loop system is stochastically stable with an H∞ disturbance attenuation level in terms of nonlinear matrix inequalities. In order to solve the controller gain, the cone complementarity linearization (CCL) algorithm is employed. Finally, a networked DC motor control system is analyzed to illustrate the effectiveness of the proposed method.

Networked control systems (NCS) are in existence for quite some time. The network-induced delays and packet drops; and their effect on control system's performance has been a burning topic for last one decade. Dependability in context of NCS has not got much attention. While it is an important aspect of NCS intended to be used in critical application. The paper reviews the present state of developments in NCS and presents open problems pertaining to dependability of NCS. Solutions to these problems may increase the presence of NCS by many folds and in many fields.

A mathematical model of networked control systems (NCS) with dynamic controllers is presented when the network-induced random time-varying delays of NCS are bounded and the upper bound of which is longer than one sampling period. This paper discretizes the model of continuous-time systems, applies augmented state-space method to the model and builds a discrete-time jump system model governed by a finite state Markov process. And the necessary and sufficient conditions guaranteeing stability of the system are discussed. This paper applies interior-point algorithm to design stabilizing controllers, presents a method to get the feasible initial solution and replaces Newton direction which is generally used in the interior-point algorithm with conjugate gradient direction for simplifying the algorithm. And this improved algorithm stated above is applied effectively to the networked control system of a cart and inverted pendulum with long delays.

In the paper, we study the stability of the discrete-time networked control systems. If the network link is with a limited communication capacity, the network-induced delay is unavoidable. Considering the network-induced delay, the closed-loop networked control systems are usually subject to the delayed state. The traditional method for the study of the networked control systems is mainly to construct a Lyapunov function and derive the stability criterion. Generally, the derived stability condition is only sufficient. The selection of the Lyapunov function is attracting increasing attention as a better Lyapunov function may lead to less conservative results. In this work, we use an alternate way to get the less conservative results. A time-domain Smith predictor is employed to predict the non-delayed state. Then, the control law is the feedback of the delayed measurements and the non-delayed prediction. Simulation results are given to show that the proposed control law can expand the upper bounds with the existing relative conservative stability criterion.

Connecting a complex control system with various sensors, actuators, and controllers as a networked control system by a shared data network can effectively reduce complicated wiring connections. This system is also easy to install and maintain. The trend is to use networked control systems for time-sensitive applications, such as remote DC motor actuation control. The performance of a networked control system can be improved if the network can guarantee quality-of-service (QoS). Due to time-varying network traffic demands and disturbances, QoS requirements provided by a network may change. In this case, a network has to reallocate its resources and may not be able to provide QoS requirements to a networked control application as needed. Therefore, the application may have to gracefully degrade its performance and perform the task as best as possible with the provided network QoS. This paper proposes a novel approach for networked DC motor control systems using controller gain adaptation to compensate for the changes in QoS requirements. Numerical and experimental simulations, and prototyping, are presented to demonstrate the feasibility of the proposed adaptation scheme to handle network QoS variation in a control loop. The effective results show the promising future of the use of gain adaptation in networked control applications.

The model of NCS (Networked Control Systems) with state observer is presented when the network-induced random time-varying delays are bounded and the upper bound of which is longer than one sampling period. Thus we established a discrete-time jump system model with Markov delay. Based on this, this paper gave also initial feasible solution of interior-point algorithm to design stabilizing controllers by the optimization method. This paper generalizes previous results on delay-less state observer systems. Theoretical analysis and simulation on a cart and inverted pendulum with random time delay show that feedback control based state observer can make the system stable.

The performance of a networked control system (NCS) is affected directly and indirectly by time delays generated in network communication. This paper addresses these time delays, their effects on system performance and the measures taken in an NCS design. For a time delay that is random but less than one sampling interval T, we model the system as a time-invariant control system with constant time delay T. For a time delay that is random and greater than one sampling interval T, we consider the system as a control system with packet drop and model it as a jump linear control system. Based on the above models, we propose a systematic method to improve the control system quality of performance by choosing a proper sampling interval to reduce data transmission, optimally scheduling to minimise packet loss and optimising controller design in case of packet loss. The simulation results and lab experiments demonstrate that the design method results in high performance in networked real-time control system.

The model of NCS(Networked Control Systems) with dynamic output feedback controllers is presented when the network-induced random time-varying delays are bounded and the upper bound of which is longer than one sampling period. Based on this, this paper discretizes the model of continuous-time systems and applies augmented state-space method to it, and then establishes a discrete-time jump system model governed by a finite state Markov process. Appling interior-point algorithm to design stabilizing controllers for the system, this paper proposed an approach to get the feasible initial solution. Theoretical analysis and simulation on a cart and inverted pendulum with random time delay show that the dynamic output feedback controllers can make the system stable.

The last two decades have witnessed a great deal of interests in sensor/actuator networks (SANs), or, generally, networked control systems (NCSs). Compared to conventional system architectures, NCSs have numerous advantages such as reduced systemwiring, being easier for design, diagnosis, and maintenance, lower cost, and increased flexibility, reliability, and safety. As a result, NCSs have been widely applied to many areas, for example, automobiles, aircrafts, and spacecrafts, autonomous vehicles, transportation systems, power systems, remote monitoring and data acquisition systems, chemical processes, and many manufacturing plants. Research on NCSs has heretofore focused mainly on several basic communication constraints that can cause performance degradation or stability loss, such as network-induced delays, packet dropouts, data corruptions or disordering, and data rate limitation and quantization effects. Medium access constraint is another important issue worthy of intensive investigation, which refers to the fact that the network cannot accommodate all the nodes (sensors, actuators, subsystems, etc.) simultaneously at any time. There are other open issues awaiting investigation, too. As a special type of NCSs, sensor/actuators networks typically have a large number of devices advanced in sensing, communicational, computational, and mobility capabilities, demanding nontrivial energy. In addition, the batteries powering these devices have limited capacity and cannot be replaced or recharged conveniently. As a consequence, many interesting and challenging issues are open, for example, localization, coverage and routing of mobile sensor/actuator networks, and so forth. The special issue focuses on the state-of-the-art research and development in the analysis and design for networked control systems as well as the theoretical and technological advances in sensor and actuator networks. The intention of this special issue was to provide for researchers a forum to share their latest research results on filtering, estimation, control, and other aspects in sensor/actuator networks and networked control systems and for readers an opportunity to have an overview of the latest achievements about some interesting issues this field has been encountering. In the next section, we give a brief description of the papers in this special issue.