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Continuous-time systems are usually modelled by differential equations arising from physical laws. However, the use of these models in practice requires discretisation. In this thesis we consider sampled-data models for linear and nonlinear systems. We study some of the issues involved in the sampling process, such as the accuracy of the sampled-data models, the artifacts produced by the particular sampling scheme, and the relations to the underlying continuous-time system. We review, extend and present new results, making extensive use of the delta operator which allows a clearer connection between a sampled-data model and the underlying continuous-time system. In the first part of the thesis we consider sampled-data models for linear systems. In this case exact discrete-time representations can be obtained. These models depend, not only on the continuous-time system, but also on the artifacts involved in the sampling process, namely, the sample and hold devices. In particular, these devices play a key role in determining the sampling zeros of the discrete-time model. We consider robustness issues associated with the use of discrete-time models for continuous-time system identification from sampled data. We show that, by using restricted bandwidth frequency domain maximum likelihood estimation, the identification results are robust to (possible) under-modelling due to the sampling process. Sampled-data models provide a powerful tool also for continuous-time optimal control problems, where the presence of constraints can make the explicit solution impossible to find. We show how this solution can be arbitrarily approximated by an associated sampled-data problem using fast sampling rates. We also show that there is a natural convergence of the singular structure of the optimal control problem from discrete- to continuous-time, as the sampling period goes to zero. In Part II we consider sampled-data models for nonlinear systems. In this case we can only obtain approximate sampled-data models. These discrete-time models are simple and accurate in a well defined sense. For deterministic systems, an insightful observation is that the proposed model contains sampling zero dynamics. Moreover, these correspond to the same dynamics associated with the asymptotic sampling zeros in the linear case. The topics and results presented in the thesis are believed to give important insights into the use of sampled-data models to represent linear and nonlinear continuous-time systems. / PhD Doctorate

This thesis is aimed at analysis of sampled-data feedback systems. Our approach is in the frequency-domain, and stresses the study of sensitivity and complementary sensitivity operators. Frequency-domain methods have proven very successful in the analysis and design of linear time-invariant control systems, for which the importance and utility of sensitivity operators is well-recognized. The extension of these methods to sampled-data systems, however, is not straightforward, since they are inherently time-varying due to the intrinsic sample and hold operations. In this thesis we present a systematic frequency-domain framework to describe sampled-data systems considering full-time information. Using this framework, we develop a theory of design limitations for sampled-data systems. This theory allows us to quantify the essential constraints in design imposed by inherent open-loop characteristics of the analog plant. Our results show that: (i) sampled-data systems inherit the difficulty imposed upon analog feedback design by the plant's non-minimum phase zeros, unstable poles, and time-delays, independently of the type of hold used; (ii) sampled-data systems are subject to additional design limitations imposed by potential non-minimum phase zeros of the hold device; and (iii) sampled-data systems, unlike analog systems, are subject to limits upon the ability of high compensator gain to achieve disturbance rejection. As an application, we quantitatively analyze the sensitivity and robustness characteristics of digital control schemes that rely on the use of generalized sampled-data hold functions, whose frequency-response properties we describe in detail. In addition, we derive closed-form expressions to compute the L2-induced norms of the sampled-data sensitivity and complementary sensitivity operators. These expressions are important both in analysis and design, particularly when uncertainty in the model of the plant is considered. Our methods provide some interesting interpretations in terms of signal spaces, and admit straightforward implementation in a numerically reliable fashion. / PhD Doctorate

The majority of computers around us are embedded in productsand dedicated to perform certain tasks. A specific task is thecontrol of a dynamic system. The computers are ofteninterconnected by communication networks forming a distributedsystem. Vehicles and manufacturing equipment are two types ofmechatronic machines which often host dedicated computercontrol systems. A research problem is how the real-timebehaviour of the computer system affects the application,especially the control of the dynamic system. If the internal or external conditions varies over time, itbecomes difficult to assign a fixed resource reservation thatwill work well in all situations. In general, the more time anapplication gets of a resource, the better its gauged orperceived quality will be. A strategy is to alter the resourcereservation when the condition changes. This can be constructedas a negotiation between competing applications, a method forwhich the termquality of control, QoC, has been coined. Scalability isthe ability to change the structure and configuration of asystem. It promotes evolving systems and a can help manage acomplex product family. An architecture for a QoC middleware ontop of a scalable computer system, has been proposed. As aquality measureof a control application, the well-knownweighted quadratic loss function used in optimal control, hasbeen revised to encompass a subset of the so called timingproperties. The timing properties are the periods and thedelays in the control loop, including time-varying period anddelay. They are the interface between control and computerengineering, from a control engineering viewpoint. The qualitymeasure can be used both offline and on-line given a model ofthe sampled-data system and an appropriate description of thetiming properties. In order to use a computer system efficiently and toguarantee its responsiveness, real-time scheduling is a must.In fixed priority scheduling each task arrives periodically andhas a fixed priority. A task with a high priority can preempt alow priority task and gain access to the resource. Thebest-case response time characterizes the delays in the system,which is useful from a control viewpoint. A new algorithm tocalculate thebest-caseresponsetime has been derived. It is based on ascheduling scenario which yields a recurrence equation. Themodel is dual to the well-known worst-case response timeanalysis. Besides the dynamic fixed priority scheduling algorithm,optimal control usingstatic schedulinghas been studied, assuming a limitedcommunication. In the static schedule, which is constructedpre-runtime, each task is assigned a time window within aschedule repeated in eternity. The optimal scheduling sequenceis sought by optimizing the overall control performance. Aninteresting aspect is that the non-specified control periodfalls out as a result of theoptimal schedule. The time-varying delay is accountedfor in the control design. Keywords:Real-time scheduling, sampled-data control,performance measure, quality of control, limited communication,time-varying delay, jitter.

¡@¡@We consider output voltage regulation of a novel twin-buck switching power converters with so-called zero voltage switching (ZVS) and zero current switching (ZCS). In order to observe the constraints imposed by ZVS and ZCS, it is necessary to adopt the pulse frequency modulation (PFM) technique, which lead to a switching system with aperiodic operating cycles. The control design is based on a sampled data model of the original switching dynamics and a linear quadratic criterion that takes the at-sampling behaviour into account. The applicability of the proposed controller is validated via numerical simulations written in MATLAB and SIMULINK. The controller is realized using Field Programmable Gate Array (FPGA). The experimental results indicate that the feedback system have good transient response and adequate robustness margin against source and load variation, which verify the applicability of the proposed control design approach.

In this thesis, digital controller design methods for sampled-data nonlinear systems are considered. Although sampled-data nonlinear control has attracted much attention in recent years, the controller design methods for sampled-data nonlinear systems are still limited. Therefore, a range of controller design methods for sampled-data nonlinear systems are developed such as backstepping, adaptive and robust backstepping, reduced-order observer-based output feedback controller design methods based on the Euler approximate model. These controllers are designed to compensate the effects of the discrepancy between the Euler approximate model and exact discrete time model, parameter estimation error in adaptive control and observer error in output feedback control which behave as disturbance. A dual-rate control scheme is presented for output-feedback stabilization of sampled-data nonlinear systems. It is shown that the designed controllers semiglobally practically asymptotically (SPA) stabilize the closed-loop sampled-data nonlinear system. Moreover, various applications of these methods are given and their performances are analyzed with simulations.

<p>The majority of computers around us are embedded in productsand dedicated to perform certain tasks. A specific task is thecontrol of a dynamic system. The computers are ofteninterconnected by communication networks forming a distributedsystem. Vehicles and manufacturing equipment are two types ofmechatronic machines which often host dedicated computercontrol systems. A research problem is how the real-timebehaviour of the computer system affects the application,especially the control of the dynamic system.</p><p>If the internal or external conditions varies over time, itbecomes difficult to assign a fixed resource reservation thatwill work well in all situations. In general, the more time anapplication gets of a resource, the better its gauged orperceived quality will be. A strategy is to alter the resourcereservation when the condition changes. This can be constructedas a negotiation between competing applications, a method forwhich the term<i>quality of control</i>, QoC, has been coined. Scalability isthe ability to change the structure and configuration of asystem. It promotes evolving systems and a can help manage acomplex product family. An architecture for a QoC middleware ontop of a scalable computer system, has been proposed.</p><p>As a<i>quality measure</i>of a control application, the well-knownweighted quadratic loss function used in optimal control, hasbeen revised to encompass a subset of the so called timingproperties. The timing properties are the periods and thedelays in the control loop, including time-varying period anddelay. They are the interface between control and computerengineering, from a control engineering viewpoint. The qualitymeasure can be used both offline and on-line given a model ofthe sampled-data system and an appropriate description of thetiming properties.</p><p>In order to use a computer system efficiently and toguarantee its responsiveness, real-time scheduling is a must.In fixed priority scheduling each task arrives periodically andhas a fixed priority. A task with a high priority can preempt alow priority task and gain access to the resource. Thebest-case response time characterizes the delays in the system,which is useful from a control viewpoint. A new algorithm tocalculate the<i>best-caseresponse</i>time has been derived. It is based on ascheduling scenario which yields a recurrence equation. Themodel is dual to the well-known worst-case response timeanalysis.</p><p>Besides the dynamic fixed priority scheduling algorithm,optimal control using<i>static scheduling</i>has been studied, assuming a limitedcommunication. In the static schedule, which is constructedpre-runtime, each task is assigned a time window within aschedule repeated in eternity. The optimal scheduling sequenceis sought by optimizing the overall control performance. Aninteresting aspect is that the non-specified control periodfalls out as a result of the<i>optimal schedule</i>. The time-varying delay is accountedfor in the control design.</p><p><b>Keywords:</b>Real-time scheduling, sampled-data control,performance measure, quality of control, limited communication,time-varying delay, jitter.</p>

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