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

This brief studies the predictive controller design of networked systems with communication delay and data loss. A networked predictive control scheme is employed to compensate for communication delay and data loss actively rather than passively. Based on analysis of the closed-loop networked predictive control systems, a design strategy of the predictive controller is proposed. The designed predictive controller can achieve the desired control performance and also guarantee the system stability. A numerical example demonstrates the compensation for communication delay and data loss in networked systems using the proposed predictive controller design strategy.

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.

This paper describes the design and implementation of an OMAP3530-based networked control system which has real-time image processing capability. It integrates an ARM core and a DSP core in the controller. The ARM core with Linux operating system is responsible for applying functional services and the DSP core is responsible for executing image processing algorithms. The due-core structure makes the novel controller available for advanced control and image processing so that the designed control system expands the application of the existed networked controllers to machine vision. Finally, a reliable application for vision-based mobile robot localization demonstrates the effectiveness of the designed system.

The rapid growth in the size and complexity of modern Cyber-Physical Systems (CPS) imposes increasing demand for the embedded resources, especially the communication resources. As a result, resource-efficient CPS design has become an important issue. Towards the design of networked embedded control systems, a major branch of CPS, reliable and deterministic communication is able to achieve satisfactory control performance. However, the amount of this type of resource that can be provided by the embedded platform is often limited. On the other hand, it is difficult to guarantee the control performance with non-deterministic communication resources, due to their unpredictable behavior. In this paper, we propose a novel control scheme to efficiently utilize elastic communication resources. In general, the non-deterministic communication resources are flexibly deployed on top of the deterministic communication resources to achieve stability and good control performance. In the rare worst-case, when non-deterministic communication is completely unavailable, the deterministic communication resources are used to guarantee stability and the control performance satisfying the design requirement. The experimental results show that the performance of the control application is ensured to satisfy the design requirement in the worst case and that better control performance is achieved when non-deterministic resources are available.

This paper discusses the model-based predictive controller design of networked nonlinear systems with communication delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation results demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.

With the information technology development of the modern ship, integrated management platform system (IPMS) has received great attention. The IPMS network architecture has the advantages of low cost, easy maintenance and great flexibility. But it inevitably introduces network delay, packet loss and other issues, so the networked control system modelling and controller design over the IPMS network becomes more and more important. In this paper, a new sliding mode networked controller, based on the T-S fuzzy model, is proposed to deal with the problems of uncertainty and disturbances in networked control system (NCS). Firstly, we choose the time delay as premise variables of the fuzzy system, so that the system with control time delay is transformed into one with no time delay based on the fuzzy fusion technology. And then, the global sliding surface is designed by the parallel distributed compensation technique. Adaptive reaching law and disturbances prediction methods are researched. The stability of IPMS networked sliding mode control system is analysed. Finally, with a certain variable time delay, the simulation results illustrate that the proposed networked controller is effective.

This paper explores stability properties of networked control systems with time-varying, but bounded delays that are introduced by network and/or consecutive packet dropouts. By using network predictive control, the networked control system can be converted into a switched system with stable and unstable subsystems. Then based on average dwell time technique, the stability of networked predictive control system can be guaranteed under some mild conditions.

In this paper, the problem of finite-time stability is studied for a class of networked predictive control systems with parameter uncertainties. Firstly, both the modelling uncertainties and the network-induced delays are considered. A networked predictive control scheme is proposed to actively compensate the network-induced delays. Secondly, a sufficient condition is given to ensure the finite-time stability of the augmented closed-loop system with time delay, where both bilinear matrix inequality and linear matrix inequality conditions are derived with the help of Lyapunov stability theorem. At the same time, an alternate algorithm is designed to obtain the gain matrices of observer and controller from bilinear matrix inequality and linear matrix inequality. Finally, a numerical example is given to confirm the feasibility of the proposed results.

The controller design techniques for Networked Control Systems (NCSs) with uncertain, time-varying network induced delay and data packet dropout is studied. A state predictor is used to predict current plant states, predicted states is used to construct control law. Combined with the state predictor, the NCS with long time delay and data packet dropout is modelled as asynchronous dynamical system with event rate constraints. Based on the model, sufficient conditions of exponential stability for NCS are given in the form of matrix inequalities. Through the feasible solution of the matrix inequalities the control law can be obtained. A numerical example demonstrates the effectiveness of the proposed method.

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.

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.

Communication jamming across various durations and frequencies leads to unpredictable and time-varying measurement transmission intervals in networked systems. Consequently, the discrete-time models of filtering error systems become time-dependent, thereby complicating the design of filters. This paper addresses the ongoing challenge of [Formula: see text] filtering for networked sampled-data systems subjected to communication jamming attacks. By incorporating the uncertain model within a polytopic framework, the analysis and synthesis conditions for a full-order [Formula: see text] filter are expressed as linear matrix inequalities. The proposed filter guarantees both asymptotic stability and [Formula: see text] performance under stealthy jamming attacks. A key novelty of the proposed approach is that it operates without requiring prior knowledge of the jammer's active or inactive periods. Another advantage of the method lies in its capability to tune the desired level of accuracy by increasing the number of vertices in the polytopic model, albeit at the cost of higher computational demand. Three benchmark examples are presented to demonstrate the effectiveness of the proposed strategy and to compare its performance with existing filters. The proposed filter achieves over 80% improvement in [Formula: see text] performance compared to existing methods. Its offline design and enhanced performance make it particularly suitable for networked and embedded control systems with constrained computational or communication capabilities.

The paper is concerned with an improved predictive control method of NCSs (Networked Control Systems) with random time delay and data dropout. The design of networked control system we proposed is based on Scenario-Based Networked Control (SBNC). Through this method the NCSs' performance is relative with an equivalent data-dropout probability. In this paper, the improved method is applied on the linear systems, and the network is in both forward and feedback channels that is more realistic. The buffer in feedback channel makes the system equivalent to a system with an extra forward delay, and the feedback channel has no delay. The simulation on the ball and beam system verifies the effectiveness and rationality of the proposed control algorithm. Besides, the comparison between a different predictive method and this improved one is achieved, and the latter one shows better tracking properties even when the network is very bad. The effects of the parameters are also considered in the simulation.

This paper is concerned with the guaranteed cost controller design of networked control systems. The continuous time plant with state-delay is studied. A new model of the networked control systems is proposed under consideration of the network-induced delay and data packet dropout. In terms of the given model, a suboptimal guaranteed cost controller design method is proposed based on linear matrix inequalities (LMI) approach. Suboptimal allowable equivalent delay bound (SAEDB) and the feedback gain of a memoryless controller can be derived by solving a set of LMI for the networked control system based on Lyapunov functional method. An example is given to show the effectiveness of our method

This work is concerned with the design of a controller for networked control system on the basis of the two disk mixed sensitivity problem. To accomplish it, the state feedback decoupling technique is used to reduce the design problem into the one of establishing filter parameters that yield a system satisfying the design specifications. The key point is that here we are concerned with both the stability and performance of the overall networked control system.