Gain adaptation of networked dc motor controllers based on qos variations

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

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 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 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.

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.

A nonlinear networked control system in which the system information is transmitted over the network through multiple communication channels is considered. Each channel is modeled by a time-varying delay element. Stability of the control system is studied using the Lyapunov-Krasovskii method for continuous-time delayed systems. The sufficient condition for stability of the networked control system is presented in the form of a compact LMI. The results are applied to a robot arm networked control system to show the capabilities of the proposed method for nonlinear networked control applications.

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 deals with static output feedback control of a class of discrete‐time networked control systems (NCS) subject to random failures and random delays. The different random processes are modeled as Markovian chains, and the resulting closed‐loop system belongs to the class of discrete‐time Markovian jump linear systems (MJLS). The main contribution is to formulate conditions for multi‐performance design related to this class of stochastic hybrid systems. The specifications and objectives under consideration include stochastic stability, ℋ︁2and ℋ︁∞performances. Results are formulated as matrix inequalities. A numerical algorithm is provided and its running is illustrated on a numerical example. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

In this paper, static output feedback stochastic stabilization and disturbance attenuation issues for a class of discrete-time Networked Control Systems (NCSs) subject to random failures and random delays are addressed. The different random processes are modeled as Markovian chains, and the resulting closed-loop system belongs to the class of discrete-time Markovian Jump Linear Systems (MJLS). Results are formulated as matrix inequalities. A numerical algorithm based on nonconvex optimization is provided and its running is illustrated on a classical example from literature.

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.

In modern networked control applications, confidentiality and integrity are important features to address in order to prevent against attacks. Moreover, network control systems are a fundamental part of the communication components of current cyber-physical systems (e.g., automotive communications). Many networked control systems employ Time-Triggered (TT) architectures that provide mechanisms enabling the exchange of precise and synchronous messages. TT systems have computation and communication constraints, and with the aim to enable secure communications in the network, it is important to evaluate the computational and communication overhead of implementing secure communication mechanisms. This paper presents a comprehensive analysis and evaluation of the effects of adding a Hash-based Message Authentication (HMAC) to TT networked control systems. The contributions of the paper include (1) the analysis and experimental validation of the communication overhead, as well as a scalability analysis that utilizes the experimental result for both wired and wireless platforms and (2) an experimental evaluation of the computational overhead of HMAC based on a kernel-level Linux implementation. An automotive application is used as an example, and the results show that it is feasible to implement a secure communication mechanism without interfering with the existing automotive controller execution times. The methods and results of the paper can be used for evaluating the performance impact of security mechanisms and, thus, for the design of secure wired and wireless TT networked control systems.

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.

Networked synchronization control has very high technology level, which includes network technology and synchronization control technology, etc. Fault diagnosis of the devices in networked synchronization control system has a great importance for ensuring the normal operation. The radial basis function neural network with particle swarm optimization algorithm is developed. The combination method of RBF neural network and particle swarm optimization is applied to fault diagnosis of networked synchronization control system. The test results indicate that the combination model of RBF neural network and particle swarm optimization can almost entirely recognize each state of the device in networked synchronization control system. The diagnostic accuracy of the combination model of RBF neural network and particle swarm optimization is greater than that of normal RBF neural network.

NCSWT: An integrated modeling and simulation tool for networked control systems

Model Based Predictive Networked Control Systems