An Immune-Genetic Algorithm-Based Scheduling Optimization in a Networked Control System

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

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.

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.

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.

In this paper, a novel approach for networked control system (NCS) task scheduling is proposed. The proposed neural-genetic method utilizes the information about the quality of service (QoS) over the communication network and enables online reconfigurable scheduling on distributed environment. In this way the NCS's bandwidth can be shared properly among different parallel control tasks. For NCS, two significant factors of QoS that affect validity of scheduling results are the packet loss and delay, which occurred in the communication among tasks. By adopting a Elman neural network based prediction model, the one-step ahead packet loss and time delay are obtained. The knowledge about the predict QoS factors, combined with the task execution features and the resources available in the system, are used as an entry to improve the decisions of the proposed scheduling algorithm. Such algorithm uses genetic algorithm techniques to find out the appropriate task scheduling scheme to adapt changes of application and communication circumstance. The proposed neural-genetic approach is evaluated through simulation by using a model parameterized with the features obtained from a real scenario of Ethernet based control system. The simulation results clearly show the effectiveness of the proposed approach in solving the task scheduling problems in NCS.

ABSTRACTIn practical networked control systems (NCS), such as smart grids, cooperative robotics, and sensor networks, often multiple control applications share a communication infrastructure, requiring a smart and efficient scheduling mechanism to coordinate the access to the capacity-limited communication medium. In this article we consider the problem of event-based scheduling design for NCSs consisting of multiple control loops over a shared communication medium. We extend the notion of Try-Once-Discard (TOD), which is one of the basic deterministic event-based scheduling protocols for resource constrained NCSs, to the case of multiple stochastic control systems coupled via a shared communication medium subject to capacity limitation and stochastic packet delivery failure. Showing that the overall network-induced error is a homogeneous Markov chain in our stochastic set-up, we first study stability properties of such networked systems under the TOD scheduling scheme employing the concepts of stochastic stability. Then, we derive sufficient stability conditions under the TOD rule assuming that the communication channel is not ideal, i.e. a scheduled data packet for transmission might be lost in the communication channel with a non-zero probability. Furthermore, we derive analytic performance bounds by finding uniform upper-bounds for an average quadratic cost function. The numerical simulations are performed for variety of system parameters and NCS set-ups to strengthen our stability claim as well as illustrating performance bounds. Additionally, we show that the TOD scheduling rule outperforms the conventional time-triggered, and uniform and non-uniform random channel access arbitration mechanisms, in terms of efficient coordination of channel access in stochastic NCSs.

In the past, control system networks were isolated from public external networks, so there was no way to access the control system networks from external networks. Security issues of control system networks were originated and guaranteed by itself. It can be a security by obscurity. Recently, most of devices in the control systems are changing with communication capability, and the interoperability between devices is very significant. Thus, effective management system for control system networks have been required and this have triggered connection between the control system network and external system networks. These changes make control system management easier than before, but the threat of cyberattacks from external networks are also increasing. To prevent a variety of security attacks, many security standards and solutions are applied to control systems. In this paper, we present scenario-based attack and propose a countermeasure using security control of field devices in order to improve security in control system networks.

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.

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

Wireless Model Based Predictive Networked Control System

Networked control systems are one type of distributed real-time control systems where sensors, actuator and controllers are interconnected by communication networks. The insertion of the communication network makes the analysis and design of a networked control system complex. So the performance of the control loops not only depends on the design of the control algorithms, but also on the scheduling of the shared network resource. A co-design method based on the integrated Earliest Deadline First (EDF) scheduling algorithm and the Integral of the Absolute Error (IAE) is proposed in order that the communication medium is more efficiently used and control performance is improved. The presented method can adjust the sampling period, handle three types of message and guarantees real-time transmission of periodic and aperiodic message, and non-real time message. The simulation results show that the proposed co-design method is available and improve the system resources efficiency.

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 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.

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