Master-Slave teleoperation systems are designed to extend a human's manipulation capability to remote tasks. Recent applications of these systems are in robotic therapy, telesurgery, and medical simulators. In practice, due to the uncertainties in the operator and environment dynamics, and time delay, stability and performance are compromised. Stability-based and performance-based controllers are introduced for these systems. A major class of the former controllers are based on the passivity theory and suffer from the assumed unbounded range of dynamics which is rather unrealistic. The latter class of controllers are mostly adaptive methods that are based on performance optimization. The theme of this thesis is on the development of new stability analysis methods, control strategies, and implementation techniques for enhanced trade-off between stability and performance. I have developed a less conservative passivity-based robust stability method and introduced, for the first time, the notion of Bounded Impedance Absolute Stability. The method provides mathematical and visual aids to incorporate bounds of the passive environment impedance for less conservative guaranteed stability conditions, promising a better compromise between stability and performance. I have extended the new method to include the dynamic range of the human operator for increased stability margins. I have also used the new method to develop a bilateral controller robust to time delays. Furthermore, I have investigated the effect of sampling position versus velocity for various sampling models to obtain less conservative coupled stability conditions for haptic simulation systems. Estimates of the environment dynamics are required to include their variations. Therefore, I have proposed two new real-time parameter estimation methods for linear and nonlinear contacts and experimentally evaluated and compared them with the available techniques. Finally, I have introduced needle insertion as a task in telerobotic systems to combine the expertise of the surgeon with robotic control. Here, the very first few steps needed to effectively control the targeting needles have been taken. I have developed a mechanics-based dynamic model for bevel-tip flexible needles inserted into soft tissues. Finite element models are used to estimate soft tissue deformation, while the mechanics-based model is used to predict needle deflections due to bevel-tip asymmetry. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2011-12-23 01:19:47.535

This thesis mainly proposes a new method to design Hinf Loop Shaping Robust Controller by choosing Weighting Function. In the paper, the author first introduces the concept of SISO Loop Shaping design. It utilizes Small Gain Theorem to achieve robust stability of the system and develops the relationship of Open Loop Transfer Function(L) to Robust Performance and to Robust Stability of the system.. These concepts can be extended to Hinf Loop Shaping method. As to Hinf loop shaping method, the author first introduces the problem of Robust Stability under the framework of Coprime Factor and the theory of Hinf Loop Shaping, and then discusses the relationship between stability margin and the different pole-zero system. Generally speaking, the control theories of the Loop Shaping are mainly used for making appropriate adjustments between the stability and performance of the system. Because the system can conform to the performance requirement through the choice of Weighting Function, the author proposes a new method toward MIMO system to design Hinf Loop Shaping Controller by choosing Weighting Function under the framework of Hinf Loop Shaping. Moreover, at the end of the paper,the author compares the result of the new method with that of the literature.

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O projeto de estratégias de controle preditivo (MPC) com estabilidade garantida, que incorpora explicitamente a incerteza de modelo na formulação de controle, ainda permanece uma questão em aberto na literatura, embora uma ampla teoria já tenha sido desenvolvida para a síntese de algoritmos MPC robustamente estáveis. Em verdade, as soluções existentes para o problema de MPC robusto estão longe de uma etapa aceitável de implementação prática, principalmente se o sistema de processo é composto de modos integradores ou instáveis, e também apresenta atrasos de tempo (tempos mortos) entre suas variáveis de entrada e saída. Sob esta perspectiva, o objetivo principal desta tese é desenvolver uma estrutura de síntese de controladores MPC com estabilidade robusta garantida para sistemas de processo com as características integradoras ou instáveis, assim como tempos mortos entre as variáveis. Particularmente, três diferentes estratégias de MPC robusto são desenvolvidas neste trabalho. As duas primeiras referem-se a sistemas integradores com tempos mortos: o primeiro algoritmo é baseado em uma formulação de controle em dois passos, enquanto o segundo é posto como um problema de otimização de controle em um passo e a representação de modelo em variáveis de estado é mais geral do que aquela adotada na formulação do primeiro método. A terceira estratégia proposta focaliza os sistemas instáveis com tempos mortos através de uma formulação de controle em um passo. Ademais, visando o caso de implementação prática, os controladores desenvolvidos compreende os seguintes aspectos: (i) as leis de controle livre de erro permanente são obtidas sem a necessidade de incluir uma camada de otimização adicional de cálculo de estados estacionários, devido à formulação adequada de modelos em espaço de estados na forma incremental das entradas, os quais são derivados de expressões analíticas de resposta ao degrau do sistema de processo; (ii) a incerteza de todos os parâmetros do modelo, e.g. ganhos, constantes de tempo, atrasos de tempo, é considerada na formulação do problema; (iii) as provas de estabilidade robusta segundo Lyapunov são realizadas de uma forma intuitiva através da imposição de restrições terminais de igualdade e restrições de contração de custo; (iv) a inclusão adequada de variáveis de folga, que não comprometem as propriedades estabilizantes dos controladores, assegura que os problemas de otimização são sempre viáveis; (v) integração estável com camada de otimização em tempo real, visto que os controladores são projetados de tal forma a rastrear targets ótimos para algumas entradas e saídas do processo, mantendo as variáveis remanescentes dentro de faixas pré-definidas, ao invés de set-points xos. Exemplos de simulação típicos da indústria de processo são explorados para ilustrar as potenciais utilidades dos métodos propostos e demonstrar que eles podem ser aplicados em casos reais. / The design of stable model predictive control (MPC) strategies that explicitly incorporate the model uncertainty into the control formulation still remains an open issue, although a rich theory has been developed to the synthesis of robustly stabilizing MPC schemes. In fact, the existing solutions to the robust MPC problem seem far from an acceptable stage of practical imple mentations, chiey when the process system is composed of integrating and unstable poles, as well as time delays between its input and output variables. Within this perspective, the ultimate goal of this thesis is to develop a new framework for robust MPC synthesis which guarantees closed-loop stability of integrating and unstable time delay processes. On this subject, three different robust MPC strategies are developed. The two rst concerns on integrating time delay processes; the former is based on a two-step control formulation, whereas the latter is posed as a one-step control optimization problem and state-space model description is more general than that adopted in the former formulation. The third proposed strategy focuses on one-step control formulation-based unstable time delay processes. Aiming at practical implementation purposes, the controllers proposed herein comprise the following aspects: (i) the offset free control laws are obtained without the need to include an additional steady-state calculation op timization layer due to the enclosure of proper state-space models in the incremental form of the inputs, which are derived of analytical expressions of step response of the process system; (ii) the uncertainty of all model parameters, e.g. gains, time constants, time delays and so on, is considered in the problem formulation; (iii) the proofs of robust Lyapunov stability are easily carried out of an intuitive way by imposing terminal equality constraints and cost-contracting constraints; (iv) the suitable inclusion of slack variables, which does not commit the stabil ity properties of the controllers, ensure that the proposed optimization problems are always feasible; (v) stable integration with real-time optimization layer, seeing as the controllers are designed to work in the optimum target tracking scheme where they should drive the process to the optimum operating point, while maintaining the remaining inputs and outputs inside pre dened zones instead of xed set-points. Simulation examples typical of the process industry are exploited to illustrate the helpfulness of the proposed control methods and demonstrate that they can be implemented in real applications.

Este trabalho apresenta todos os passos para a implementação de técnicas de controle preditivo em uma coluna de destilação. Inicialmente a tese introduz basicamente o funcionamento e a meta do processo de destilação. Modelos linearizados em tempo contínuo da coluna de destilação são obtidos a partir de ensaios experimentais da coluna em diferentes pontos de operação. Com base nestes modelos, várias topologias de controladores preditivos baseados em modelo são implementadas. Um otimizador em tempo real é integrado aos controladores preditivos para a redução do custo operacional da planta. Resultados simulados e resultados experimentais de todas as topologias de controladores preditivos estudados são apresentados. / This work presents all the steps to the implementation of predictive control techniques in a distillation column. First the thesis basically introduces the working and the goal of the distillation process. Linearized models in continuous time of the distillation column are obtained from experimental tests of the column in different operating points. Based on this models, several model based predictive controllers topologies are implemented. A real time optimizer is integrated with the predictive controllers to the reduction of the plant operational cost. Simulated results and experimental results of all studied predictive controllers topologies are presented.

There are two main approaches to robust stability analysis: the input-output stability framework with scaling or multiplier, and the Lyapunov functions. Analysis methods in these two directions are usually developed independently, and the relationship between the two is not clear except for some special cases. This motivates us to study the relationship between the two approaches. The generalized performance problem refers to certain frequency-domain conditions on a transfer matrix. We prove the equivalent relationship between generalized performance and robust stability under certain assumptions. The definition of generalized performance requires the internal stability of a transfer matrix, which is not a necessity for robust stability. In view of this, we derive new frequency-domain conditions for robust stability without this requirement. Our result contains a version of the circle criterion as a special case. To tackle the generalized performance problem, we propose a version of the Kalman-Yakubovich-Popov (KYP) lemma to transform the frequency-domain conditions into linear matrix inequalities (LMIs). The proposed LMI condition is then connected to the quadratic stability of an uncertain linear system. Combining the derived results gives a clear picture of the relationships between robust stability, generalized performance, quadratic stability, and KYP lemma. The connections not only unify some previous results but also extend those results to more general stability regions and types of uncertainty. In addition to robust stability analysis, we also tackle the corresponding synthesis problem, i.e. robust pole placement. The desired region for robust pole placement can be the intersection or the union of simple regions. (Simple regions are the half plane, the disk, and the outside of a disk.) One contribution of our synthesis result is that the desired region can be non-convex¡Xmost results on robust pole placement focus on convex regions only. Two examples of the longitudinal control of a combat aircraft and the attitude control of a satellite demonstrate the effectiveness of our result.

Stability is a critical issue in gain-scheduled control problems in that the closed loop system may not be stable during the transitions between operating conditions despite guarantees that the gain-scheduled controller stabilizes the plant model at fixed values of the scheduling variable. For Linear Parameter Varying (LPV) model representations, a controller interpolation method using Youla parameterization that guarantees stability despite fast transitions in scheduling variables is proposed. By interconnecting an LPV plant model with a Local Controller Network (LCN), the proposed Youla parameterization based controller interpolation method allows the interpolation of controllers of different size and structure, and guarantees stability at fixed points over the entire operating region. Moreover, quadratic stability despite fast scheduling is also guaranteed by construction of a common Lyapunov function, while the characteristics of individual controllers designed a priori at fixed operating condition are recovered at the design points. The efficacy of the proposed approach is verified with both an illustrative simulation case study on variation of a classical MIMO control problem and an experimental implementation on a multi-evaporator vapor compression cycle system. The dynamics of vapor compression systems are highly nonlinear, thus the gain-scheduled control is the potential to achieve the desired stability and performance of the system. The proposed controller interpolation/switching method guarantees the nonlinear stability of the closed loop system during the arbitrarily fast transition and achieves the desired performance to subsequently improve thermal efficiency of the vapor compression system.

The purpose of this dissertation is to study the robust control for the smart flexible linkage mechanism. The control of flexible linkage induced inertia force under high-speed rotation is taken into consideration with the system parameter uncertainties such as modeling error, truncation error, and both of control spillover and observation spillover due to the residual modes of structural control problem. Based on the principles of LQ, optimal model following (OMF) and frequency shaping, this study proposes some sufficient conditions of stability criteria for the design of robust controller, respectively. These techniques guarantee that the controlled plant, under both bounded parameter perturbations and model truncation, could remain stable. Meanwhile, searching for the optimal locating positions of sensor and actuator by applying Taguchi method and genetic algorithm (GA) combined technique is further studied. The system is modeled through employing finite element method (FEM), and the limited lower frequency part modes are separated into controlled modes and residual modes. In time domain, at first we design a Luenberger-observer-based robust controller for the finite-dimensional mode plant keeping stability in a specified region. And then, a robust controller with the OMF is designed for the controlled system to achieve the performance as those of the specified optimum model. From the view of frequency domain, the robust controller could also be deigned according to the frequency shaping principle to suppress the exciting effect of higher frequency residual modes, and similarly avoid that the system might be destabilized. Finally, the combination of Taguchi method and GA technique to search the optimal locations for placing actuator and sensor to coincide with the stability and performance requirement is also done. From the computer simulation, the middle point movement of the linkage is obviously well controlled; hence, the designed robust controllers can certainly suppress the affection of parameter uncertainties and the spillover stimulation of residual modes, and can produce satisfactory results.

In this thesis, autopilots are developed for missiles with moderate dynamics and stationary targets. The aim is to use the designs in real applications. Since the real missile model is nonlinear, a linearization process is required to get use of systematic linear controller design techniques. In the scope of this thesis, the linear quadratic full state feedback approach is applied for developing missile autopilots. However, the limitations of measurement systems on the missiles restrict the availability of all the states required for feedback. Because of this fact, the linear quadratic design will be approximated by the use of projective control theory. This method enables the designer to use preferably static feedback or if necessary a controller plus a low order compensator combination to approximate the full state feedback reference. Autopilots are checked for the validity of linearization, robust stability against aerodynamic, mechanical and measurement uncertainties.

abstract: Buck converters are electronic devices that changes a voltage from one level to a lower one and are present in many everyday applications. However, due to factors like aging, degradation or failures, these devices require a system identification process to track and diagnose their parameters. The system identification process should be performed on-line to not affect the normal operation of the device. Identifying the parameters of the system is essential to design and tune an adaptive proportional-integral-derivative (PID) controller. Three techniques were used to design the PID controller. Phase and gain margin still prevails as one of the easiest methods to design controllers. Pole-zero cancellation is another technique which is based on pole-placement. However, although these controllers can be easily designed, they did not provide the best response compared to the Frequency Loop Shaping (FLS) technique. Therefore, since FLS showed to have a better frequency and time responses compared to the other two controllers, it was selected to perform the adaptation of the system. An on-line system identification process was performed for the buck converter using indirect adaptation and the least square algorithm. The estimation error and the parameter error were computed to determine the rate of convergence of the system. The indirect adaptation required about 2000 points to converge to the true parameters prior designing the controller. These results were compared to the adaptation executed using robust stability condition (RSC) and a switching controller. Two different scenarios were studied consisting of five plants that defined the percentage of deterioration of the capacitor and inductor within the buck converter. The switching logic did not always select the optimal controller for the first scenario because the frequency response of the different plants was not significantly different. However, the second scenario consisted of plants with more noticeable different frequency responses and the switching logic selected the optimal controller all the time in about 500 points. Additionally, a disturbance was introduced at the plant input to observe its effect in the switching controller. However, for reasonable low disturbances no change was detected in the proper selection of controllers. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016