Computer-based control systems are widely used in vehicle applications (e.g., aircraft, marine and automobile). The earlier forms of control systems were typified by a central computer connected to sub-systems using hard-wired point-to-point communication links. However, such systems suffered from several major drawbacks: (i) fault-tolerance problems, (ii) maintenance and cabling costs, and (iii) excessive cable weight. These problems were minimised by using master-slave networks with distributed control architecture. However, using such networks raises the question of fault-tolerance and integrity of the communication system. In view of this, efforts have been made to employ the architecture provided by the IEEE 802.4 Token Bus for real time control applications although the performance of the Token Bus is not adequate for applications where fast response times are required.

The objective of this thesis is to develop a theoretical understanding of computation in networked dynamical systems and demonstrate practical applications supported by the theory. We are interested in understanding how networks of locally interacting agents can be controlled to compute arbitrary functions of the initial node states. In other words, can a dynamical networked system be made to behave like a computer? In this thesis, we take steps towards answering this question with a particular model class for distributed, networked systems which can be made to compute linear transformations.

This thesis is an effort to develop closed-loop control strategies on computer networks and study their stability in the presence of network delays and packet losses. An algorithm using predictors was designed to ensure the system stability in presence of network delays and packet losses. A single actuator magnetic ball levitation system was used as a test bed to validate the proposed algorithm. A brief study of real-time requirements of the networked control system is presented and a client-server architecture is developed using real-time operating environment to implement the proposed algorithm. Real-time performance of the communication on Ethernet based on user datagram protocol (UDP) was explored and UDP is presented as a suitable protocol for networked control systems. Predictors were designed based on parametric estimation models. Autoregressive (AR) and autoregressive moving average (ARMA) models of various orders were designed using MATLAB and an eighth order AR model was adopted based on the best-fit criterion. The system output was predicted several steps ahead using these predictors and control output was calculated using the predictions. This control output output was used in the events of excessive network delays to maintain system stability. Experiments employing simulations of consecutive packet losses and network delays were performed to validate the satisfactory performance of the predictor based algorithm. The current system compensates for up to 20 percent data losses in the network without loosing stability.

This thesis is an effort to develop closed-loop control strategies on computer networks and study their stability in the presence of network delays and packet losses. An algorithm using predictors was designed to ensure the system stability in presence of network delays and packet losses. A single actuator magnetic ball levitation system was used as a test bed to validate the proposed algorithm. A brief study of real-time requirements of the networked control system is presented and a client-server architecture is developed using real-time operating environment to implement the proposed algorithm. Real-time performance of the communication on Ethernet based on user datagram protocol (UDP) was explored and UDP is presented as a suitable protocol for networked control systems. Predictors were designed based on parametric estimation models. Autoregressive (AR) and autoregressive moving average (ARMA) models of various orders were designed using MATLAB and an eighth order AR model was adopted based on the best-fit criterion. The system output was predicted several steps ahead using these predictors and control output was calculated using the predictions. This control output output was used in the events of excessive network delays to maintain system stability. Experiments employing simulations of consecutive packet losses and network delays were performed to validate the satisfactory performance of the predictor based algorithm. The current system compensates for up to 20 percent data losses in the network without loosing stability.

Wireless networked control systems use shared wireless links to communicate between sensors and controllers, and require a channel access policy to arbitrate access to the links. Existing multiple access protocols perform this role in an agnostic manner, by remaining insular to the applications that run over the network. This approach does not give satisfactory control performance guarantees. To enable the use of wireless networks in emerging industrial applications, we must be able to systematically design wireless networked control systems that provide guaranteed performances in resource-constrained networks. In this thesis, we advocate the use of state-based channel access policies. A state-based policy uses the state of the controlled plant to influence access to the network. The state contains information about not only the plant, but also the network, due to the feedback in the system. Thus, by using the state to decide when and how frequently to transmit, a control system can adapt its contribution to the network traffic, and enable the network to adapt access to the plant state. We show that such an approach can provide better performance than existing methods. We examine two different state-based approaches that are distributed and easy to implement on wireless devices: event-based scheduling and adaptive prioritization. Our first approach uses events to reduce the traffic in the network. We use a state-based scheduler in every plant sensor to generate non-coordinated channel access requests by selecting a few critical data packets, or events, for transmission. The network uses a contention resolution mechanism to deal with simultaneous channel access requests. We present three main contributions for this formulation. The first contribution is a structural analysis of stochastic event-based systems, where we identify a dual predictor architecture that results in separation in design of the state-based scheduler, observer and controller. The second contribution is a Markov model that describes the interactions in a network of event-based systems. The third contribution is an analysis of the stability of event-based systems, leading to a stabilizing design of event-based policies. Our second approach uses state-based priorities to determine access to the network. We use a dominance protocol to evaluate priorities in a contention-based setting, and characterize the resulting control performance. An implementation and evaluation of this channel access mechanism on sensor nodes is also presented. The thesis finally examines the general networked control problem of jointly optimizing measurement and control policies, when a nonlinear measurement policy is used to perform quantization, event-triggering or companding. This contribution focuses on some of the fundamental aspects of analyzing and synthesizing control systems with state-based measurement policies in a more generalized setting. We comment on the dual effect, certainty equivalence and separation properties for this problem. In particular, we show that it is optimal to apply separation and certainty equivalence to a design problem that permits a dynamic choice of the measurement and control policies. / <p>QC 20140408</p>

Physical processes which are governed by differential equations or difference equations with discontinuous behavior can be modeled as jump systems. An important type of jump systems is the one evolving linearly among the discrete events; this type of systems is called jump linear systems. A common analysis approach is to employ stochastic processes to describe the sequences, switches, and statistic properties of the discrete events. In this thesis, the jump linear systems to be studied are governed by semi-Markov processes. This type of jump linear systems is called the semi-Markov jump linear system. Due to the nature of the jump linear system, it finds many applications in networked control systems, fault tolerant control systems, and other systems subject to abrupt changes. It is worthwhile to mention that the well studied Markov jump linear system is a special case of the semi-Markov jump linear system. The thesis consists of two parts: The analysis and synthesis of semi-Markov jump linear systems and networked dynamic systems. In Chapter 2 and Chapter 3, the stochastic stability and optimal control for semi-Markov jump linear systems with or without time delays are investigated. In Chapter 4, a novel fault tolerant control scheme is proposed based on the semi-Markov jump linear system stability conditions. Chapter 5 to Chapter 7 discuss the networked dynamic systems analysis via jump linear system approaches. The stochastic stability conditions for semi-Markov jump linear systems are firstly derived. The Lyapunov theory is used to establish the sufficient stability conditions by deriving the infinitesimal generator of the Lyapunov function. Since in practice, almost all the system models could not be identified precisely, robust control problems for systems with uncertainties are investigated based on the established stability conditions. Considering the potential applications on networked systems where time delays are inevitable, optimal control problems for systems with time-varying delays have been studied. In the fault tolerant control design, the semi-Markov process is ideal to characterize time-varying failure rates of the system components whose life time is not exponentially distributed. The designed controller is capable of maintaining the stability when an actuator malfunctions. In the networked control system analysis, stochastic processes are used to model time delays and sensor scheduling rules. Network limitations are compensated by considering more historical information or planning for all possible delays that happen in the future. Both simulations and experiments show the improvements of the control performance by using the proposed techniques. A networked haptic system is investigated via the switching system approach. In the haptic system, the avatar interacts one-dimensionally with a multi-material virtual wall in the virtual environment.The random trajectory along which the avatar moves upon the wall is modeled by stochastic processes, then the multi-material virtual wall rendering is achieved. Finally, the thesis work is summarized and two future research topics are proposed. One is on the networked control system design where delays are modeled by semi-Markov processes, and the other one is on the event-trigger scheme design for networked dynamic systems. / Graduate / 0548 / 0544 / 0546 / jihuang@uvic.ca

Research Doctorate - Doctor of Philosophy (PhD) / This thesis studies control systems with communication constraints. Such constraints arise due to the fact that practical control systems often use non-transparent communication links, i.e., links subject to data-rate constraints, random data-dropouts or random delays. Traditional control theory cannot deal with such constraints and the need for new tools and insights arises. We study two problems: control with average data-rate constraints and control over analog erasure channels with i.i.d. dropout profiles. When focusing on average data-rate constraints, it is natural to ask whether information theoretic ideas may assist the study of networked control systems. In this thesis we show that it is possible to use fundamental information theoretic concepts to arrive at a framework that allows one to tackle performance related control problems. In doing so, we show that there exists an exact link between control systems subject to average data-rate limits, and control systems which are closed over additive i.i.d. noise channels subject to a signal-to-noise ratio constraint. On the other hand, in the case of control systems subject to i.i.d. data-dropouts, we show that there exists a second-order moments equivalence between a linear feedback system which is interconnected over an analog erasure channel, and the same system when it is interconnected over an additive i.i.d. noise channel subject to a signal-to-noise ratio constraint. From the results foreshadowed above, it follows that the study of control systems closed over signal-to-noise ratio constrained additive i.i.d. noise channels is a task of relevance to many networked control problems. Moreover, the interplay between signal-to-noise ratio constraints and control objectives is an interesting issue in its own right. This thesis starts with such a study. Then, we use the resultant insights to address performance issues in control systems subject to either average data-rate constraints or i.i.d. data-dropouts. Our approach shows that, once key equivalences are exposed, standard control intuition and synthesis machinery can be used to tackle networked control problems in an exact manner. It also sheds light into fundamental results in the literature and gives (partial) answers to several previously open questions. We believe that the insights in this thesis are of fundamental importance and, to the best of the author's knowledge, novel.

The importance of real-time communication at the device level in a factory automation setup is a widely researched area. This research is an effort to experimentally verify if Ethernet can be used as a real-time communication standard in a factory automation setup, by observing the effects of packet delays, packet loss, and network congestion on the performance of a networked control system (NCS). The NCS experimental setup used in this research involves real-time feedback control of multiple plants like DC motors and a magnetic-levitation system connected to one or more controllers. A multi-client-multi-server architecture on a local area network (LAN) was developed using user datagram protocol (UDP) as the communication protocol. Key observations are as follows. (1) The multi-client-single-server system showed the highest packet delays compared to single-client-single-server architecture. (2) In the singleclient- single-server system, as the Ethernet link utilization increased beyond 82 percent, the average packet delays and steady-state error of the DC motor speed-control system increased by 2231 percent and 304 percent, respectively. (3) Even under high link utilization, adding an additional server to the NCS reduced average packet delays considerably. (4) With large packet sizes, higher packet rates were automatically throttled by Ethernet’s flow control mechanism affecting the real-time communication negatively. (5) In the multiclient- multi-server architecture, average packet delays at higher packet rates, and at higher packet lengths were found to be 40 percent lesser than the those of the single-clientsingle- server system and 87.5 percent lesser than those of the multi-client-single-server system.

A control system in which sensors, actuators, and controllers are interconnected over a communication network is called a networked control system (NCS). Enhanced computational capabilities and bandwidths in the networking technology enabled researchers to develop NCSs to implement distributed control schemes. This dissertation presents a framework for the modeling, design, stability analysis, control, and bandwidth allocation of real-time control over networks. This framework covers key research issues regarding control over networks and can be the guidelines of NCS design. A single actuator ball magnetic-levitation (maglev) system is implemented as a test bed for the real-time control over networks to illustrate and verify the theoretical results of this dissertation. Experimentally verifying the feasibility of Internet-based real-time control is another main objective of this dissertation. First, this dissertation proposes a novel NCS model in which the effects of the networkinduced time delay, data-packet loss, and out-of-order data transmission are all considered. Second, two simple algorithms based on model-estimator and predictor- and timeout-scheme are proposed to compensate for the network-induced time delay and packet loss simultaneously. These algorithms are verified experimentally by the ball maglev test bed. System stability analyses of original and compensated systems are presented. Then, a novel co-design consideration related to real-time control and network communication is also proposed. The working range of the sampling frequency is determined by the analysis of the system stability and network parameters such as time delay, data rate, and data-packet size. The NCS design chart developed in this dissertation can be a useful guideline for choosing the network and control parameters in the design of an NCS. Using a real-time operating system for real-time control over networks is also proposed as one of the main contributions of this dissertation. After a real-time NCS is successfully implemented, advanced control theories such as robust control, optimal control, and adaptive control are applied and formulated to improve the quality of control (QoC) of NCSs. Finally, an optimal dynamic bandwidth management method is proposed to solve the optimal network scheduling and bandwidth allocation problem when NCSs are connected to the same network and are sharing the network resource.

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