Made available in DSpace on 2014-06-11T19:22:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-02-16Bitstream added on 2014-06-13T18:49:31Z : No. of bitstreams: 1 silva_jl_me_ilha.pdf: 4436511 bytes, checksum: a3ef3dcb55e4a2eca8bbc6e79470f5cc (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / O principal objetivo do trabalho é explorar a técnica de controle robusto com Modos Deslizantes para a acomodação e atenuação de uma falha no sinal de controle de um helicóptero. Foram projetados dois controladores, o Controle com Estrutura Variável e Modos Deslizantes contínuo no tempo (CEV/MD), e o segundo é o Controle Discreto com Modos Deslizantes (CDMD). Foi usado um modelo matemático não linear que representa um simulador de voo (Helicóptero 3-DOF da Quanser R ), que é um equipamento útil para o ensino, aplicação e desenvolvimento de técnicas de controle robusto. Os resultados experimentais obtidos, fazem uma comparação entre o controle contínuo e o controle discreto. Para que essa comparação seja feita foi inserida uma falha no sinal de controle. Mesmo diante das diferenças na resposta do sinal de controle, entre os controladores, o sistema teve um bom desempenho quando controlado pelo CEV/MD e CDMD, mostrando assim a eficiência da técnica de controle com Modos Deslizantes / The main objective of this work is the exploration of the robust control technique with Sliding Mode (VSC-SM) for fault accommodation and attenuation in an aircraft’s propulsion system. Two controllers were designed, Variable Structure Control with Sliding Mode (VSCSM) and Discrete Control with Sliding Modes (DCSM). For that, it was used a mathematical model of a flight Simulator of a Quanser’s helicopter, named as 3-DOF Helicopter, which is an excellent module for teaching, application and development of robust control techniques. The results obtained in digital simulations show great performance of the system in fault when controlled by VSC-SM and DCSM

Orientador: Marcelo Carvalho Minhoto Teixeira / Banca: Jean Marcos de Souza Ribeiro / Banca: Cristiano Quevedo Andrea / Resumo: Nesta dissertação apresentam-se o princípio de funcionamento do motor de indução trifásico em regime permanente abordando os ensaios necessários para obtenção de seus parâmetros e as diferentes possibilidades de variação de velocidade. A partir disso, efetuou-se uma análise da modelagem dinâmica do motor, enfocando nas transformações de eixos, além de analisar os tipos de controle, escalar, vetorial direto e indireto (orientado pelo fluxo do rotor, pelo fluxo do estator e pelo fluxo do entreferro) e o controle direto de torque. Também se abordou os conversores CC - CA utilizados para o acionamento do motor de indução trifásico, juntamente com suas principais metodologias de modulação. Fez-se uma revisão do estado da arte dos sistemas de acionamento e controle mais estudados nos últimos anos sobre o assunto. Após, estudou-se os conceitos de estabilidade quadrática proposto por Lyapunov, juntamente com o controle H∞, os quais foram a base para o desenvolvimento de controladores robustos projetados no trabalho com desigualdade matriciais lineares (em inglês Linear Matrix Inequalities (LMIs)). Desenvolveram-se cinco tipos de controladores robustos com LMIs: o robusto, com taxa de decaimento (para sigma 1 e 10), H∞, H∞ com D-Estabilidade e H∞ com D-Estabilidade e realimentação da integral do erro de saída sendo que em todos o motor de indução trifásico foi orientado pelo fluxo do rotor. Os controladores foram projetados para quatro diferentes configurações, sendo considerados, primeiro caso - variação da velocidade (5 rad/s até a nominal); segundo caso - variação da velocidade e incerteza na resistência rotórica (3%); terceiro caso - variação na velocidade e incerteza na constante de tempo do rotor (5%); quarto caso - variação na velocidade e incertezas na constante de tempo do rotor (15%) e do estator (10%). Em todos os controladores projetados foram... / Abstract: This research shows the steady state operating principle of triphasic induction motors to approach the tests necessary to obtain their parameters and different speed variation possibilities. After were performed an analysis of the dynamics of motor modeling, focusing on the transformation of axes, and analyzing the types of control, scalar, direct and indirect vector (guided by the rotor flux at the stator flux and flux air gap) and direct torque control. The converters CC - AC used to drive the induction motor are also aborded, along with their main methods of modulation. A review of the state of the art regarding the drives and control systems most studied in recent years on the subject is presented. After were studied the concepts of quadratic stability proposed by Lyapunov, together with the H∞ control, which were the basis for the development of robust controllers based on Linear Matrix Inequality (LMI). In this research were developed five types of robust controllers with LMI: the robust controller, the controller with decay rate (for sigma 1 and 10), H∞ controller, H∞ controller with D- Stability and H∞ controller with D- Stability and feedback the integral of output error, considering in all cases that the triphasic induction motor is driven by rotor flux. The controllers were designed for four different configurations and were considered the first case - the speed variation (5 rad/s up to the rated); second case - the speed variation and uncertainty in the rotor resistance (3%); third case - variations in speed and uncertainty in the rotor time constant (5%); fourth case - variations in speed and uncertainties in the rotor time constant (15%) and the stator (10%). In all researched controllers were analyzed the response time of the outputs for a unit step input load torque disturbance. This analysis aimed to evaluate system behavior, however, for a complete and rigorous analysis ... / Mestre

Este trabalho apresenta os resultados da aplicação de três técnicas de controle utilizadas no projeto e implementação do controle de um manipulador subatuado planar de três juntas em série e de elos rígidos, projetado e construído pela Universidade Carnegie Mellon, EUA. Devido ao alto grau de não-linearidade deste sistema, seria muito difícil implementar um controlador H2, H&#8734 ou H2/H&#8734 que atuasse sozinho. Assim, propõe-se a utilização de um método de controle combinado: torque computado/H2, H&#8734 ou H2/H&#8734. No controle combinado, a porção correspondente ao torque computado lineariza e pré-compensa a dinâmica do modelo da planta nominal, enquanto a porção correspondente ao controle H2, H&#8734 ou H2/H&#8734 realiza uma pós-compensação dos erros residuais, que não foram completamente eliminados pelo método torque computado. Testes de acompanhamento de trajetória e testes de robustez são realizados aqui para comprovar a eficiência destes controladores, com resultados de implementação bastante satisfatórios. / This work presents the application results of three control techniques used for the control design and implementation of a serial planar underactuated manipulator with three joints and rigid links, designed and built by the Carnegie Mellon University, USA. Due to the high non-linearity degree of this system, it would be very difficult to implement an H2, H&#8734 or H2/ H&#8734 control which would actuate on the system by itself. Therefore, it is proposed a combined control method: computed torque/ H2, H&#8734 or H2/H&#8734. In the combined control, the portion corresponding to the computed torque linearizes and pre-compensates the dynamics of the nominal model, while the portion corresponding to the H2, H&#8734 or H2/H&#8734 control realizes a pos-compensation of the residual errors, not completely removed by the computed torque method. Trajetory tracking and robustness tests are performed here to demonstrate the efficiency of these controllers, with very satisfatory implementation results.

Orientador: Celso Pascoli Bottura / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-16T02:56:28Z (GMT). No. of bitstreams: 1 Silva_MarcusPantojada_M.pdf: 634546 bytes, checksum: 9c15ab5bd5cf1715bf9313a7d802d180 (MD5) Previous issue date: 2010 / Resumo:Este trabalho propõe uma metodologia para o controle robusto descentralizado de sistemas não lineares com incertezas variantes no tempo limitadas em norma utilizando um procedimento alternativo ao S-Procedure proposto por Yakubovich. Com base em nosso procedimento, desenvolvemos também uma metodologia de projeto de observadores robustos descentralizados para uma classe de sistemas não lineares variantes no tempo limitados em norma. Com o estado estimado pelo observador descentralizado projetamos um controlador descentralizado por realimentação de saída que estabiliza o sistema. Outro problema que é resolvido nesse trabalho é o projeto de controlador robusto H1 descentralizado para uma classe de sistemas não lineares variantes no tempo limitados em norma sujeitos a distúrbios externos. Exemplos que ilustram aplicações das metodologias propostas são apresentados / Abstract: This work proposes a methodology for decentralized robust control of nonlinear systems with time-varying uncertainties norm bounded using an alternative procedure to the S-Procedure proposed by Yakubovich. Based on our procedure a decentralized robust observer design methodology for a class of time-varying norm bounded nonlinear systems is also developed. With the state estimated by the decentralized observer we design an output feedback decentralized controller that stabilizes the system. Another problem that is solved in this work is the design of a decentralized H1 robust controller for a class of time-varying norm bounded nonlinear systems subject to external disturbances. Examples illustrating the application of the proposed methodologies are presented / Mestrado / Automação / Mestre em Engenharia Elétrica

This thesis investigates Bicoprime Factorisations (BCFs) and their possible uses in robust control theory. BCFs are a generalisation of coprime factorisations, which have been well known and widely used by the control community over the last few decades. Though they were introduced at roughly the same time as coprime factorisations, they have been largely ignored, with only a very small number of results derived in the literature. BCFs are first introduced and the fundamental theory behind them is developed. This includes results such as internal stability in terms of BCFs, parametrisation of the BCFs of a plant and state space constructions of BCFs. Subsequently, a BCF uncertainty structure is proposed, that encompasses both left and right coprime factor uncertainty. A robust control synthesis procedure is then developed with respect to this BCF uncertainty structure. The proposed synthesis method is shown to be advantageous in the following two aspects: (1) the standard assumptions associated with H-infinity control synthesis are directly fulfilled without the need of loop shifting or normalisation of the generalised plant and (2) any or all of the plant's unstable dynamics can be ignored, thus leading to a reduction in the dimensions of the Algebraic Riccati Equations (AREs) that need to be solved to achieve robust stabilisation. Normalised BCFs are then defined, which are shown to provide many advantages, especially in the context of robust control synthesis. When using a normalised BCF of the plant, lower bounds on the achievable BCF robust stability margin can be easily and directly computed a priori, as is the case for normalised coprime factors. Although the need for an iterative procedure is not completely avoided when designing an optimal controller, it is greatly simplified with the iteration variable being scalar. Unlike coprime factorisations where a single ARE needs to be solved to achieve normalisation, two coupled AREs must be satisfied for a BCF to be normalised. Two recursive methods are proposed to solve this problem. Lastly, an example is presented where the theory developed is used in a practical scenario. A quadrotor Unmanned Aerial Vehicle (UAV) is considered and a normalised BCF controller is designed which in combination with feedback linearisation is used to control both the attitude and position of the vehicle.

Abstract In this thesis a set of new algorithms is introduced for Iterative Learning Control (ILC) and Repetitive Control (RC). Both areas of study are relatively new in control theory, and the common denominator for them is that they concentrate on controlling systems that include either reference signals or disturbances which are periodic. This provides opportunities for using past information or experience so that the control system learns the control action that results in good performance in terms of reference tracking or disturbance rejection. The first major contribution of the thesis is the algebraic analysis of ILC systems. This analysis shows that in the discrete-time case ILC algorithm design can be considered as designing a multivariable controller for a multivariable static plant and the reference signal that has to be tracked is a multivariable step function. Furthermore, the algebraic analysis reveals that time-varying algorithms should be used instead of time-invariant ones in order to guarantee monotonic convergence of the error in norm. However, from the algebraic analysis it is not clear how to select the free parameters of a given ILC algorithm. Hence in this thesis optimisation methods are used to automate this design phase. Special emphasis is placed on the so called Norm-Optimal Iterative Learning Control (NOILC) that was originally developed in (Amann:1996) as a new result it is shown that a convex modification of the existing predictive algorithm will result in a considerable improvement in convergence speed. Because the NOILC algorithm is computationally quite complex, a new set of Parameter-Optimal ILC algorithms are derived that converge under certain assumptions on the original plant. Three of these new algorithms will result in monotonic convergence to zero tracking error for an arbitrary discrete-time, linear, time-invariant plant. This a very strong property that has been earlier reported for only a small number of ILC algorithms. In the RC case it is shown that an existing RC algorithm that has been widely analysed and used in the research literature is in fact highly unrobust if the algorithm is implemented using sampled-data processing. Consequently, in this thesis a new optimality based discrete-time RC algorithm is derived, which converges to zero tracking error asymptotically for an arbitrary linear, time-invariant discrete-time plant under mild controllability and observability conditions.

Networked control systems (NCSs) are known as distributed control systems (DCSs) which are based on traditional feedback control systems but closed via a real-time communication channel. In an NCS, the control and feedback signals are exchanged among the system’s components in the form of information packages through the communication channel. The research of NCSs is important from the application perspective due to the significant advantages over the traditional point-to-point control. However, the insertion of the communication links would also bring challenges and constraints such as the network-induced delays, the missing packets, and the inter symbol interference (ISI) into the system design. In order to tackle these issues and move a step further toward industry applications, two important design problems are investigated in the control areas: Tracking Control (Chapter 2–Chapter 5) and Signal Estimation (Chapter 6–Chapter8). With the fact that more than 90% of control loops in industry are controlled by proportional-integral-derivative (PID) controllers, the first work in this thesis aims to propose the design algorithm on PID controllers for NCSs. Such a design will not require the change or update of the existing industrial hardware, and it will enjoy the advantages of the NCSs. The second motivation is that, due to the network-induced constraints, there is no any existing work on tuning the PID gains for a general NCS with a state-space model. In Chapter 2, the PID tracking control for multi-variable NCSs subject to time-varying delays and packet dropouts is exploited. The H_infty control is employed to attenuate the load disturbance and the measurement noise. In Chapter 3, the probabilistic delay model is used to design the delay-scheduling tracking controllers for NCSs. The tracking control strategy consists of two parts: (1) the feedforward control can enhance the transient response, and (2) the feedback control is the digital PID control. In order to compensate for the delays on both communication links, the predictive control scheme is adopted. To make full use of the delay information, it is better to use the Markov chain to model the network-induced delays and the missing packets. A common assumption on the Markov chain model in the literature is that the probability transition matrix is precisely known. However, the assumption may not hold any more when the delay is time-varying in a large set and the statistics information on the delays is inadequate. In Chapter 4, it is assumed that the transition matrices are with partially unknown elements. An observer-based robust energy-to-peak tracking controller is designed for the NCSs. In Chapter 5, the step tracking control problem for the nonlinear NCSs is in- vestigated. The nonlinear plant is represented by Takagi-Sugeno (T-S) fuzzy linear model. The control strategy is a modified PI control. With an augmentation technique, the tracking controller design problem is converted into an H_infty optimization problem. The controller parameters can be obtained by solving non-iterative linear matrix inequality conditions. The state estimation problem for networked systems is explored in Chapter 6. At the sensor node, the phenomenon of multiple intermittent measurements is considered for a harsh sensing environment. It is assumed that the network-induced delay is time- varying within a bounded interval. To deal with the delayed external input and the non-delayed external input, a weighted H_infty performance is defined. A Lyapunov- based method is employed to deal with the estimator design problem. When the delay is not large, the system with delayed state can be transformed into delay-free systems. By using the probabilistic delay model and the augmentation, the H_infty filter design algorithm is proposed for networked systems in Chapter 7. Considering the phenomenon of ISI, the signals transmitted over the communication link would distort, that is, the output of the communication link is not the same with the input to the communication link. If the phenomenon occurs in the NCSs, it is desired to reconstruct the signal. In Chapter 8, a robust equalizer design algorithm is proposed to reconstruct the input signal, being robust against the measurement noise and the parameter variations. Finally, the conclusions of the dissertation are summarized and future research topics are presented. / Graduate

Legged locomotion has several interesting challenges that need to be addressed, such as the ability of dynamically walk over rough terrain like stairs or stepping stones, as well as the ability to adapt to unexpected changes in the environment and the dynamic model of the robot. This thesis is driven towards solving these challenges and makes contributions on theoretical and experimental aspects to address: dynamic walking, model uncertainty, and rough terrain. On the theoretical front, we introduce and develop a unified robust and adaptive control framework that enables the ability to enforce stability and safety-critical constraints arising from robotic motion tasks under a high level of model uncertainty. We also present a novel method of walking gait optimization and gait library to address the challenge of dynamic robotic walking over stochastically generated stepping stones with significant variations in step length and step height, and where the robot has knowledge about the location of the next discrete foothold only one step ahead. On the experimental front, our proposed methods are successfully validated on ATRIAS, an underactuated, human-scale bipedal robot. In particular, experimental demonstrations illustrate our controller being able to dynamically walk at 0.6 m/s over terrain with step length variation of 23 to 78 cm, as well as simultaneous variation in step length and step height of 35 to 60cm and -22 to 22cm respectively. In addition to that, we also successfully implemented our proposed adaptive controller on the robot, which enables the ability to carry an unknown load up to 68 lb (31 kg) while maintaining very small tracking errors of about 0.01 deg (0.0017 rad) at all joints. To be more specific, we firstly develop robust control Lyapunov function based quadratic program (CLFQP) controller and L1 adaptive control to handle model uncertainty for bipedal robots. An application is dynamic walking while carrying an unknown load. The robust CLF-QP controller can guarantee robustness via a quadratic program that can be extended further to achieve robust safety-critical control. The L1 adaptive control can estimate and adapt to the presence of model uncertainty in the system dynamics. We then present a novel methodology to achieve dynamic walking for underactuated and hybrid dynamcal bipedal robots subject to safety-critical constraints. The proposed controller is based on the combination of control Barrier functions (CBFs) and control Lyapunov functions (CLFs) implemented as a state-based online quadratic program to achieve stability under input and state constraints. The main contribution of this work is the control design to enable stable dynamical bipedal walking subject to strict safety constraints that arise due to walking over a terrain with randomly generated discrete footholds. We next introduce Exponential Control Barrier Functions (ECBFs) as means to enforce high relativedegree safety constraints for nonlinear systems. We also develop a systematic design method that enables creating the Exponential CBFs for nonlinear systems making use of tools from linear control theory. Our method creates a smooth boundary for the safety set via an exponential function, therefore is called Exponential CBFs. Similar to exponential stability and linear control, the exponential boundary of our proposed method helps to have smoother control inputs and guarantee the robustness under model uncertainty. The proposed control design is numerically validated on a relative degree 4 nonlinear system (the two-link pendulum with elastic actuators and experimentally validated on a relative degree 6 linear system (the serial cart-spring system). Thanks to these advantages of Exponential CBFs, we then can apply the method to the problem of 3D dynamic walking with varied step length and step width as well as dynamic walking on time-varying stepping stones. For the work of using CBF for stepping stones, we use only one nominal walking gait. Therefore the range of step length variation is limited ([25 : 60](cm)). In order to improve the performance, we incorporate CBF with gait library and increase the step length range significantly ([10 : 100](cm)). While handling physical constraints and step transition via CBFs appears to work well, these constraints often become active at step switching. In order to resolve this issue, we introduce the approach of 2-step periodic walking. This method not only gives better step transitions but also offers a solution for the problem of changing both step length and step height. Experimental validation on the real robot was also successful for the problem of dynamic walking on stepping stones with step lengths varied within [23 : 78](cm) and average walking speed of 0:6(m=s). In order to address the problems of robust control and safety-critical control in a unified control framework, we present a novel method of optimal robust control through a quadratic program that offers tracking stability while subject to input and state-based constraints as well as safety-critical constraints for nonlinear dynamical robotic systems under significant model uncertainty. The proposed method formulates robust control Lyapunov and barrier functions to provide guarantees of stability and safety in the presence of model uncertainty. We evaluate our proposed control design on different applications ranging from a single-link pendulum to dynamic walking of bipedal robot subject to contact force constraints as well as safety-critical precise foot placements on stepping stones, all while subject to significant model uncertainty. We conduct preliminary experimental validation of the proposed controller on a rectilinear spring-cart system under different types of model uncertainty and perturbations. To solve this problem, we also present another solution of adaptive CBF-CLF controller, that enables the ability to adapt to the effect of model uncertainty to maintain both stability and safety. In comparison with the robust CBF-CLF controller, this method not only can handle a higher level of model uncertainty but is also less aggressive if there is no model uncertainty presented in the system.

Variable Horizon Model Predictive Control (VH-MPC) is a form of predictive control that includes the horizon length as a decision variable in the constrained optimisation problem solved at each iteration. It has been recently applied to completion problems, where the system state is to be steered to a closed set in finite time. The behaviour of the system once completion has occurred is not considered part of the control problem. This thesis is concerned with three aspects of robustness and optimality in VH-MPC completion problems. In particular, the thesis investigates robustness to well defined but unpredictable changes in system and controller parameters, robustness to bounded disturbances in the presence of certain input parameterisations to reduce computational complexity, and optimal robustness to bounded disturbances using tightened constraints. In the context of linear time invariant systems, new theoretical contributions and algorithms are developed. Firstly, changing dynamics, constraints and control objectives are addressed by introducing the notion of feasible contingencies. A novel algorithm is proposed that introduces extra prediction variables to ensure that anticipated new control objectives are always feasible, under changed system parameters. In addition, a modified constraint tightening formulation is introduced to provide robust completion in the presence of bounded disturbances. Different contingency scenarios are presented and numerical simulations demonstrate the formulation’s efficacy. Next, complexity reduction is considered, using a form of input parameterisation known as move blocking. After introducing a new notation for move blocking, algorithms are presented for designing a move-blocked VH-MPC controller. Constraints are tightened in a novel way for robustness, whilst ensuring that guarantees of recursive feasibility and finite-time completion are preserved. Simulations are used to illustrate the effect of an example blocking scheme on computation time, closed-loop cost, control inputs and state trajectories. Attention is now turned towards mitigating the effect of constraint tightening policies on a VH-MPC controller’s region of attraction. An optimisation problem is formulated to maximise the volume of an inner approximation to the region of attraction, parameterised in terms of the tightening policy. Alternative heuristic approaches are also proposed to deal with high state dimensions. Numerical examples show that the new technique produces substantially improved regions of attraction in comparison to other proposed approaches, and greatly reduces the maximum required prediction horizon length for a given application. Finally, a case study is presented to illustrate the application of the new theory developed in this thesis to a non-trivial example system. A simplified nonlinear surface excavation machine and material model is developed for this purpose. The model is stabilised with an inner-loop controller, following which a VH-MPC controller for autonomous trajectory generation is designed using a discretised, linearised model of the stabilised system. Realistic simulated trajectories are obtained from applying the controller to the stabilised system and incorporating the ideas developed in this thesis. These ideas improve the applicability and computational tractability of VH-MPC, for both traditional applications as well as those that go beyond the realm of vehicle manœuvring.

Orientador: Ricardo Coração de Leão Fontoura de Oliveira / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-26T15:54:55Z (GMT). No. of bitstreams: 1 Vieira_HenriquedeSouza_M.pdf: 1027517 bytes, checksum: 9dcae7f42b15c7b6a4659c57bea547f7 (MD5) Previous issue date: 2015 / Resumo: Os problemas de estabilização e controle H? robustos por realimentação de estados para sistemas lineares incertos em domínios politópicos são investigados nesta dissertação. São propostas novas técnicas de síntese baseadas em condições LMIs com busca em escalares, abordando de maneira unificada sistemas contínuos e discretos no tempo. A principal novidade da técnica proposta é o uso efetivo de matrizes de Lyapunov polinomiais de grau arbitrário para certificar a estabilidade robusta do sistema em malha fechada. A segunda vantagem da abordagem proposta é que as melhores condições de síntese por realimentação de estados atualmente disponíveis na literatura podem ser reproduzidas por meio de escolhas particulares dos parâmetros escalares. Para o problema de controle H? também é proposto um procedimento iterativo como alternativa à busca dos escalares. Experimentos numéricos ilustram o potencial e a eficácia da técnica proposta / Abstract: The problems of robust stabilization and H? control by state-feedback for uncertain linear systems in polytopic domains are investigated in this dissertation. New synthesis techniques based on LMI conditions with scalar searches, addressing in a unified way continuous and discrete-time systems, are proposed. The main novelty of the proposed method is the effective use of polynomial Lyapunov matrices of arbitrary degree to certify the robust stability of the closed-loop system. The second advantage of the proposed approach is that the best currently available state-feedback synthesis conditions in the literature can be reproduced by particular choices of the scalars. Regarding the H? control problem, an iterative procedure is also proposed as an alternative to the scalar searches. Numerical experiments illustrate the potential and efficacy of the proposed methods / Mestrado / Automação / Mestre em Engenharia Elétrica