No description available.

This thesis is concerned with the analysis of the control design to the nonlinear networked control systems (NCSs). Ignoring the network connection and cascading actuators, the plant and sensors together, a sampled-data system is obtained. The stabilization problem of nonlinear sampled-data systems is considered under the low measurement rate constraint. Dual-rate control schemes based on the emulation design and discrete-time design approaches respectively are proposed that utilize a numerical integration model to approximately predict the current state of the plant. It is shown that using the dual-rate control schemes, input-to-state stability property will be preserved for the closed loop sampled-data system in a practical sense. On the other hand, the networked realization of nonlinear control systems is studied and a model-based control scheme is addressed as a solution to reduce the network traffic and resultantly, to attain a higher performance. The NCSs are modeled as continuous-time systems and sampled-data systems, respectively. Under the proposed control scheme, a tradeoff between satisfactory control performance and reduction of network traffic can be achieved. It is shown that by using the estimated values, generated by the plant model, instead of true values of the plant, a significant saving in the required bandwidth is achieved and this makes possible stabilization of the plant even under slow network conditions.

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

Les méthodologies de l'automatique ont joué au cours des dernières décennies un ´r^ole essentiel au sein de nombreux secteurs technologiques avancées. Cependant, de nombreuse questions restent ouvertes. Parmi celles-ci, celles concernant la stabilité et la stabilisation de systèmes non linéaires sont d'intérêt primordial. Afin de stabilizer un système (physique ou non), il est nécessaire de capter et interpreter en temps réel les informations hétérogènes caractérisant son fonctionnement afin intervenir efficacement. Actuellement ces informations ne sont pas captées en temps continu, mais de façon synchrone ou asynchrone et ceci est valable aussi pour les actuateurs. De façon très naturelle, on définit donc un système hybride, caractérisé par des dynamiques à la fois discrètes et continues. Dans ce contexte, cette thèse est orientée au développement de nouvelles méthodologies pour la stabilisation de systèmes échantillonnés non linéaires en se focalisant sur la stabilisation de formes cascades qui se retrouvent dans de nombreuse situations concretes. Pour cela, on étudiera l'effet de l'échantillonnage sur les propriétés de la dynamique continue et l'on proposera des méthodologies pour la conception de lois de commande qui ne requièrent pas d'assumptions supplémentaires au cas continu.Enfin, on étudiera l'effet de l'échantillonnage sur des systèmes présentant de retards sur les entrées. On développera des lois de commande stabilisantes exploitant la structure en cascade induite par l'échantillonnage. Des exemples académiques illustreront les calcules des solutions et leur performances tout au long du manuscript. / Over the last decades the methodologies of dynamical systems and control theory have been playing an increasingly relevant role in a lot of situations of practical interest. Though, a lot of theoretical problem still remain unsolved. Among all, the ones concerning stability and stabilization are of paramount importance. In order to stabilize a physical (or not) system, it is necessary to acquire and interpret heterogeneous information on its behavior in order to correctly intervene on it. In general, those information are not available through a continuous flow but are provided in a synchronous or asynchronous way. This issue has to be unavoidably taken into account for the design of the control action. In a very natural way, all those heterogeneities define an hybrid system characterized by both continuous and discrete dynamics. This thesis is contextualized in this framework and aimed at proposing new methodologies for the stabilization of sampled-data nonlinear systems with focus toward the stabilization of cascade dynamics. In doing so, we shall propose a small number of tools for constructing sampled-data feedback laws stabilizing the origin of sampled-data nonlinear systems admitting cascade interconnection representations. To this end, we shall investigate on the effect of sampling on the properties of the continuous-time system while enhancing design procedures requiring no extra assumptions over the sampled-data equivalent model.Finally, we shall show the way sampling positively affects nonlinear retarded dynamics affected by a fixed and known time-delay over the input signal by enforcing on the implicit cascade representation the sampling process induces onto the retarded system. Academic examples will illustrate the computational aspects together with their performances throughout the whole manuscript.

No description available.

Reinforcement Learning has received a lot of attention over the years for systems ranging from static game playing to dynamic system control. Using Reinforcement Learning for control of dynamical systems provides the benefit of learning a control policy without needing a model of the dynamics. This opens the possibility of controlling systems for which the dynamics are unknown, but Reinforcement Learning methods like Q-learning do not explicitly account for time. In dynamical systems, time-dependent characteristics can have a significant effect on the control of the system, so it is necessary to account for system time dynamics while not having to rely on a predetermined model for the system. In this dissertation, algorithms are investigated for expanding the Q-learning algorithm to account for the learning of sampling rates and dynamics approximations. For determining a proper sampling rate, it is desired to find the largest sample time that still allows the learning agent to control the system to goal achievement. An algorithm called Sampled-Data Q-learning is introduced for determining both this sample time and the control policy associated with that sampling rate. Results show that the algorithm is capable of achieving a desired sampling rate that allows for system control while not sampling “as fast as possible”. Determining an approximation of an agent’s dynamics can be beneficial for the control of hierarchical multiagent systems by allowing a high-level supervisor to use the dynamics approximations for task allocation decisions. To this end, algorithms are investigated for learning first- and second-order dynamics approximations. These algorithms are respectively called First-Order Dynamics Learning and Second-Order Dynamics Learning. The dynamics learning algorithms are evaluated on several examples that show their capability to learn accurate approximations of state dynamics. All of these algorithms are then evaluated on hierarchical multiagent systems for determining task allocation. The results show that the algorithms successfully determine appropriated sample times and accurate dynamics approximations for the agents investigated.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18993号 / 工博第4035号 / 新制||工||1621(附属図書館) / 31944 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 萩原 朋道, 教授 松尾 哲司, 准教授 古谷 栄光 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Neste trabalho, aborda-se o problema de estabilidade de sistemas com dados amostrados periodicamente, na presença de atuadores saturantes em posição e em taxa de variação. Os atuadores são modelados como sistemas de primeira ordem com saturação de entrada (saturação de magnitude) e do estado (saturação de taxa de variação). No modelo, considera-se que o sinal de controle é mantido constante entre dois instantes de amostragem consecutivos, enquanto as dinâmicas da planta linear e do atuador saturante são em tempo contínuo, i.e., não é feita discretização do sistema. O efeito da amostragem aperiódica é considerado através de um looped -funcional, derivado do funcional de Lyapunov-Krasovskii. O método desenvolvido relaciona uma função quadrática de Lyapunov e o funcional, considerando a amostragem assíncrona e o atuador saturante. Assim, se a derivada temporal do funcional ao longo das trajetórias do sistema for definida negativa, verifica-se que a função de Lyapunov é estritamente decrescente nos instantes de amostragem. Os efeitos das saturações são considerados por meio do uso da condição de setor generalizada. A partir do looped-funcional, da função de Lyapunov e das relações de setor generalizadas, são formuladas condições que permitem caracterizar a estabilidade e projetar ganhos estabilizantes da origem do sistema amostrado, em contexto local e global, através de algoritmos baseados na solução de LMIs. São propostas condições para maximização da estimativa da região de atração da origem ou, dado um conjunto de condições iniciais, para maximização do limite superior do intervalo de amostragem. As condições estabelecidas são válidas para o sistema com acesso a todos os estados, como também, no caso dos estados do atuador não estarem disponíveis `a medição. / This work addresses the problems of stability and stabilization of sampled-data systems taking into account aperiodic sampling and magnitude and rate saturating actuactors. The actuators are represented by a first-order system subject to input (magnitude saturation) and state (rate) saturation. In the considered model, the control signal is assumed to be constant between two successive sampling instants, while the dynamics of the linear plant and the saturating actuator are in continuous-time, i.e., no discretization is performed. The aperiodic sampling is taken into account from the method based on the input delay approach via looped-functional, derived from a time-dependent Lyapunov-Krasovskii functional. The developed method is based on a particular functional, that is related to a Lyapunov function. It is shown that if the time derivative of the looped- functional along the trajectories of the continuous-time system is strictly negative, then the Lyapunov function is strictly decreasing at sampling instants. The actuator saturations are taken into account from the use of a generalized sector condition. From the looped-functional, the Lyapunov function and the generalized sector conditions, the developed results lead to conditions that can be solved as LMI prob- lems for asymptotic stability assessment and stabilization local or global of the origin of the sampled-data system. Convex optimization problems are developed to com- pute an estimate of the region of attraction or, given a set of admissible initial conditions, compute the maximal admissible inter-sampling time for which the con- vergence of the trajectories to the origin is ensured. Theorical results are valid for systems with access to all the states, and also for the case that actuator states are not available to the measurement.

Neste trabalho, aborda-se o problema de estabilidade de sistemas com dados amostrados periodicamente, na presença de atuadores saturantes em posição e em taxa de variação. Os atuadores são modelados como sistemas de primeira ordem com saturação de entrada (saturação de magnitude) e do estado (saturação de taxa de variação). No modelo, considera-se que o sinal de controle é mantido constante entre dois instantes de amostragem consecutivos, enquanto as dinâmicas da planta linear e do atuador saturante são em tempo contínuo, i.e., não é feita discretização do sistema. O efeito da amostragem aperiódica é considerado através de um looped -funcional, derivado do funcional de Lyapunov-Krasovskii. O método desenvolvido relaciona uma função quadrática de Lyapunov e o funcional, considerando a amostragem assíncrona e o atuador saturante. Assim, se a derivada temporal do funcional ao longo das trajetórias do sistema for definida negativa, verifica-se que a função de Lyapunov é estritamente decrescente nos instantes de amostragem. Os efeitos das saturações são considerados por meio do uso da condição de setor generalizada. A partir do looped-funcional, da função de Lyapunov e das relações de setor generalizadas, são formuladas condições que permitem caracterizar a estabilidade e projetar ganhos estabilizantes da origem do sistema amostrado, em contexto local e global, através de algoritmos baseados na solução de LMIs. São propostas condições para maximização da estimativa da região de atração da origem ou, dado um conjunto de condições iniciais, para maximização do limite superior do intervalo de amostragem. As condições estabelecidas são válidas para o sistema com acesso a todos os estados, como também, no caso dos estados do atuador não estarem disponíveis `a medição. / This work addresses the problems of stability and stabilization of sampled-data systems taking into account aperiodic sampling and magnitude and rate saturating actuactors. The actuators are represented by a first-order system subject to input (magnitude saturation) and state (rate) saturation. In the considered model, the control signal is assumed to be constant between two successive sampling instants, while the dynamics of the linear plant and the saturating actuator are in continuous-time, i.e., no discretization is performed. The aperiodic sampling is taken into account from the method based on the input delay approach via looped-functional, derived from a time-dependent Lyapunov-Krasovskii functional. The developed method is based on a particular functional, that is related to a Lyapunov function. It is shown that if the time derivative of the looped- functional along the trajectories of the continuous-time system is strictly negative, then the Lyapunov function is strictly decreasing at sampling instants. The actuator saturations are taken into account from the use of a generalized sector condition. From the looped-functional, the Lyapunov function and the generalized sector conditions, the developed results lead to conditions that can be solved as LMI prob- lems for asymptotic stability assessment and stabilization local or global of the origin of the sampled-data system. Convex optimization problems are developed to com- pute an estimate of the region of attraction or, given a set of admissible initial conditions, compute the maximal admissible inter-sampling time for which the con- vergence of the trajectories to the origin is ensured. Theorical results are valid for systems with access to all the states, and also for the case that actuator states are not available to the measurement.

Neste trabalho, aborda-se o problema de estabilidade de sistemas com dados amostrados periodicamente, na presença de atuadores saturantes em posição e em taxa de variação. Os atuadores são modelados como sistemas de primeira ordem com saturação de entrada (saturação de magnitude) e do estado (saturação de taxa de variação). No modelo, considera-se que o sinal de controle é mantido constante entre dois instantes de amostragem consecutivos, enquanto as dinâmicas da planta linear e do atuador saturante são em tempo contínuo, i.e., não é feita discretização do sistema. O efeito da amostragem aperiódica é considerado através de um looped -funcional, derivado do funcional de Lyapunov-Krasovskii. O método desenvolvido relaciona uma função quadrática de Lyapunov e o funcional, considerando a amostragem assíncrona e o atuador saturante. Assim, se a derivada temporal do funcional ao longo das trajetórias do sistema for definida negativa, verifica-se que a função de Lyapunov é estritamente decrescente nos instantes de amostragem. Os efeitos das saturações são considerados por meio do uso da condição de setor generalizada. A partir do looped-funcional, da função de Lyapunov e das relações de setor generalizadas, são formuladas condições que permitem caracterizar a estabilidade e projetar ganhos estabilizantes da origem do sistema amostrado, em contexto local e global, através de algoritmos baseados na solução de LMIs. São propostas condições para maximização da estimativa da região de atração da origem ou, dado um conjunto de condições iniciais, para maximização do limite superior do intervalo de amostragem. As condições estabelecidas são válidas para o sistema com acesso a todos os estados, como também, no caso dos estados do atuador não estarem disponíveis `a medição. / This work addresses the problems of stability and stabilization of sampled-data systems taking into account aperiodic sampling and magnitude and rate saturating actuactors. The actuators are represented by a first-order system subject to input (magnitude saturation) and state (rate) saturation. In the considered model, the control signal is assumed to be constant between two successive sampling instants, while the dynamics of the linear plant and the saturating actuator are in continuous-time, i.e., no discretization is performed. The aperiodic sampling is taken into account from the method based on the input delay approach via looped-functional, derived from a time-dependent Lyapunov-Krasovskii functional. The developed method is based on a particular functional, that is related to a Lyapunov function. It is shown that if the time derivative of the looped- functional along the trajectories of the continuous-time system is strictly negative, then the Lyapunov function is strictly decreasing at sampling instants. The actuator saturations are taken into account from the use of a generalized sector condition. From the looped-functional, the Lyapunov function and the generalized sector conditions, the developed results lead to conditions that can be solved as LMI prob- lems for asymptotic stability assessment and stabilization local or global of the origin of the sampled-data system. Convex optimization problems are developed to com- pute an estimate of the region of attraction or, given a set of admissible initial conditions, compute the maximal admissible inter-sampling time for which the con- vergence of the trajectories to the origin is ensured. Theorical results are valid for systems with access to all the states, and also for the case that actuator states are not available to the measurement.