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Abstract The Generalized Predictive Controller in transfer function representation is proposed for the cascade control task. The recommended cascade GPC (CGPC) applies one predictor and one cost function that results in several advantageous features: The disturbance regulations of the inner and the outer loops can be totally decoupled; The inner disturbance regulation is well damped, the typical overshoot of the traditional cascade control structure is avoided; The robustness properties of the inner and the outer loops can be designed separately; The anti-windup properties of the CGPC are exactly as perfect as in the case of the simple SISO GPC. The typical problem of the saturation in the inner loop, resulting in modeling error for the outer loop, is prevented. The CGPC was applied as the oxygen controller of a pilot fluidized bed boiler. The investigation is based on simulation experiments and on experiments on a pilot scale boiler. In another simulation experiment, the CGPC was applied as the temperature controller of at a steam superheater stage. The results of the experiments well illustrated the power of the proposed cascade control algorithm.

A computer model for a general clarifier-thickener has been made and used for comparing different strategies for control of such dewatering units through simulations. The model builds on widely acknowledged theory for modelling clarifier-thickeners - discretizing the settling PDE into a set of ODEs so that concentrations of solids at discrete depths inside the unit become the states of the numerical model - and it was written in the Modelica language using the modelling and simulation environment Dymola. The work of estimating model parameters for themodel and comparing different control strategies was made looking at one particular clarifier-thickener at the company Boliden's mineral processing plant in Garpenberg. Among the control strategies that were compared in simulations were simple PID control and cascade control as well as more advanced control schemes. The simulations showed that the optimal control strategy to use is cascade control using rake torque as a secondary variable, which makes sense in particular for large thickeners such as the one mainly considered in this work.

<p>Robotic manipulators have been introduced in industry as a form of increasing productivity. Today, there exist an interest to enlarge the application of these manipulators to outdoor environments. Forestry cranes used in the forestry industry are a clear example. A long term goal in this industry is the development of autonomous systems to increase the logging efficiency. In this thesis, we consider how to control the rotator of these cranes, which is an electro-hydraulically actuated motor, and is used to control the end ffector tool. Control system design for the rotator is a challenging task since the sensing is not available to full extent. The main reason is the harsh environment that these machines are exposed to and sensors such as encoders are very fragile and cannot be used. In this thesis we use alternative sensing devices, such as a magnetic sensor and a stereo camera. In the case of the camera we face a problem with big delay. A prediction method has been used to compute desired values. Due to various reasons certain measuring devices can not be used in the industry. We consider four cases for control system design where dfferent combinations of available sensors have been used. Initially angular position of the rotator is controlled using only the magnetic sensor. A cascade control setup is used where pressure and position are measurable, first using the magnetic sensor and later using the camera. When only pressure measurements are available identified models have replaced sensors for position feedback. All tests and experiments have been done using a scaled version of a real forestry crane. The available crane has similar configuration and dynamics as the real one and is therefor useful for experimental purposes.</p>

Robotic manipulators have been introduced in industry as a form of increasing productivity. Today, there exist an interest to enlarge the application of these manipulators to outdoor environments. Forestry cranes used in the forestry industry are a clear example. A long term goal in this industry is the development of autonomous systems to increase the logging efficiency. In this thesis, we consider how to control the rotator of these cranes, which is an electro-hydraulically actuated motor, and is used to control the end ffector tool. Control system design for the rotator is a challenging task since the sensing is not available to full extent. The main reason is the harsh environment that these machines are exposed to and sensors such as encoders are very fragile and cannot be used. In this thesis we use alternative sensing devices, such as a magnetic sensor and a stereo camera. In the case of the camera we face a problem with big delay. A prediction method has been used to compute desired values. Due to various reasons certain measuring devices can not be used in the industry. We consider four cases for control system design where dfferent combinations of available sensors have been used. Initially angular position of the rotator is controlled using only the magnetic sensor. A cascade control setup is used where pressure and position are measurable, first using the magnetic sensor and later using the camera. When only pressure measurements are available identified models have replaced sensors for position feedback. All tests and experiments have been done using a scaled version of a real forestry crane. The available crane has similar configuration and dynamics as the real one and is therefor useful for experimental purposes.

Visando apoiar o desenvolvimento de controladores para servoposicionadores pneumáticos, é apresentada no presente trabalho uma proposta de um procedimento baseado no uso de redes neurais para a determinação de modelos matemáticos precisos que possam ser aplicados tanto para a simulação do seu comportamento dinâmico quanto na estrutura de controladores que utilizam estratégias baseadas em modelos. No âmbito do trabalho, esse procedimento foi testado por meio de sua aplicação na identificação das forças de atrito e da relação pressão/vazão mássica nos orifícios de controle da servoválvula (que consistem nas principais não-linearidades envolvidas em tais sistemas). Além disso, determinou-se através de redes neurais a relação inversa entre as vazões desejadas e o sinal de controle da servoválvula (difeomorfismo), a qual é aplicada em técnicas de controle baseadas em modelos. Visando validar o procedimento de modelagem proposto, foram realizadas simulações em malha aberta e malha fechada, cujos resultados são comparados com os de experimentos realizados em uma bancada de testes. Com o intuito de comprovar sua eficácia em aplicações de controle, o modelo baseado em redes neurais foi utilizado no desenvolvimento de um controlador não-linear sintetizado de acordo com uma estratégia em cascata (a qual foi já testada em outros trabalhos, mostrando resultados satisfatórios quando aplicada ao controle de servoposicionadores pneumáticos). No entanto, essa estratégia apresenta dificuldades de implantação em decorrência das dificuldades associadas ao processo de identificação dos parâmetros do sistema, que são especialmente trabalhosos neste caso. As características de estabilidade em malha fechada foram analisadas por meio do segundo método Lyapunov. Os resultados experimentais em malha fechada obtidos atestam a eficácia da estratégia de controle proposta. / The development of a precise positioning system has motivated several researches in the pneumatic systems control area to overcome the problems caused by these nonlinearities, by appropriate feedback control algorithms. In this work it is proposed a methodology based on neural networks to achieve accurate mathematical models that can be used in simulation as in controllers techniques based on models. This methodology was tested through its application in identifying the phenomenon of friction and the relationship pressure/mass flow through servo valve orifices control holes. Furthermore, using neural networks, the inverse relationship between the desired flow rates and control signal of servo valve (diffeomorphism), which is applied in various control techniques based on models, was determined. To evaluate the proposed modeling methodology, simulations were done in open and closed loop, and the results were compared with experiments conducted on a real pneumatic servo positioning system. A neural network based model was used to develop a nonlinear controller according to a cascade strategy with friction compensation (which has been tested on other studies showing satisfactory results when applied to pneumatic servo positioning control). The cascade control strategy, despite showing a good performance in trajectory tracking, presents significant difficulties in implementation due mainly to difficulties associated with the system parameters identification process, which are especially expensive. The characteristics of the closed loop stability were analyzed by Lyapunov method. The experimental results obtained in closed loop attest the efficiency of the proposed control strategy.

Visando apoiar o desenvolvimento de controladores para servoposicionadores pneumáticos, é apresentada no presente trabalho uma proposta de um procedimento baseado no uso de redes neurais para a determinação de modelos matemáticos precisos que possam ser aplicados tanto para a simulação do seu comportamento dinâmico quanto na estrutura de controladores que utilizam estratégias baseadas em modelos. No âmbito do trabalho, esse procedimento foi testado por meio de sua aplicação na identificação das forças de atrito e da relação pressão/vazão mássica nos orifícios de controle da servoválvula (que consistem nas principais não-linearidades envolvidas em tais sistemas). Além disso, determinou-se através de redes neurais a relação inversa entre as vazões desejadas e o sinal de controle da servoválvula (difeomorfismo), a qual é aplicada em técnicas de controle baseadas em modelos. Visando validar o procedimento de modelagem proposto, foram realizadas simulações em malha aberta e malha fechada, cujos resultados são comparados com os de experimentos realizados em uma bancada de testes. Com o intuito de comprovar sua eficácia em aplicações de controle, o modelo baseado em redes neurais foi utilizado no desenvolvimento de um controlador não-linear sintetizado de acordo com uma estratégia em cascata (a qual foi já testada em outros trabalhos, mostrando resultados satisfatórios quando aplicada ao controle de servoposicionadores pneumáticos). No entanto, essa estratégia apresenta dificuldades de implantação em decorrência das dificuldades associadas ao processo de identificação dos parâmetros do sistema, que são especialmente trabalhosos neste caso. As características de estabilidade em malha fechada foram analisadas por meio do segundo método Lyapunov. Os resultados experimentais em malha fechada obtidos atestam a eficácia da estratégia de controle proposta. / The development of a precise positioning system has motivated several researches in the pneumatic systems control area to overcome the problems caused by these nonlinearities, by appropriate feedback control algorithms. In this work it is proposed a methodology based on neural networks to achieve accurate mathematical models that can be used in simulation as in controllers techniques based on models. This methodology was tested through its application in identifying the phenomenon of friction and the relationship pressure/mass flow through servo valve orifices control holes. Furthermore, using neural networks, the inverse relationship between the desired flow rates and control signal of servo valve (diffeomorphism), which is applied in various control techniques based on models, was determined. To evaluate the proposed modeling methodology, simulations were done in open and closed loop, and the results were compared with experiments conducted on a real pneumatic servo positioning system. A neural network based model was used to develop a nonlinear controller according to a cascade strategy with friction compensation (which has been tested on other studies showing satisfactory results when applied to pneumatic servo positioning control). The cascade control strategy, despite showing a good performance in trajectory tracking, presents significant difficulties in implementation due mainly to difficulties associated with the system parameters identification process, which are especially expensive. The characteristics of the closed loop stability were analyzed by Lyapunov method. The experimental results obtained in closed loop attest the efficiency of the proposed control strategy.

Visando apoiar o desenvolvimento de controladores para servoposicionadores pneumáticos, é apresentada no presente trabalho uma proposta de um procedimento baseado no uso de redes neurais para a determinação de modelos matemáticos precisos que possam ser aplicados tanto para a simulação do seu comportamento dinâmico quanto na estrutura de controladores que utilizam estratégias baseadas em modelos. No âmbito do trabalho, esse procedimento foi testado por meio de sua aplicação na identificação das forças de atrito e da relação pressão/vazão mássica nos orifícios de controle da servoválvula (que consistem nas principais não-linearidades envolvidas em tais sistemas). Além disso, determinou-se através de redes neurais a relação inversa entre as vazões desejadas e o sinal de controle da servoválvula (difeomorfismo), a qual é aplicada em técnicas de controle baseadas em modelos. Visando validar o procedimento de modelagem proposto, foram realizadas simulações em malha aberta e malha fechada, cujos resultados são comparados com os de experimentos realizados em uma bancada de testes. Com o intuito de comprovar sua eficácia em aplicações de controle, o modelo baseado em redes neurais foi utilizado no desenvolvimento de um controlador não-linear sintetizado de acordo com uma estratégia em cascata (a qual foi já testada em outros trabalhos, mostrando resultados satisfatórios quando aplicada ao controle de servoposicionadores pneumáticos). No entanto, essa estratégia apresenta dificuldades de implantação em decorrência das dificuldades associadas ao processo de identificação dos parâmetros do sistema, que são especialmente trabalhosos neste caso. As características de estabilidade em malha fechada foram analisadas por meio do segundo método Lyapunov. Os resultados experimentais em malha fechada obtidos atestam a eficácia da estratégia de controle proposta. / The development of a precise positioning system has motivated several researches in the pneumatic systems control area to overcome the problems caused by these nonlinearities, by appropriate feedback control algorithms. In this work it is proposed a methodology based on neural networks to achieve accurate mathematical models that can be used in simulation as in controllers techniques based on models. This methodology was tested through its application in identifying the phenomenon of friction and the relationship pressure/mass flow through servo valve orifices control holes. Furthermore, using neural networks, the inverse relationship between the desired flow rates and control signal of servo valve (diffeomorphism), which is applied in various control techniques based on models, was determined. To evaluate the proposed modeling methodology, simulations were done in open and closed loop, and the results were compared with experiments conducted on a real pneumatic servo positioning system. A neural network based model was used to develop a nonlinear controller according to a cascade strategy with friction compensation (which has been tested on other studies showing satisfactory results when applied to pneumatic servo positioning control). The cascade control strategy, despite showing a good performance in trajectory tracking, presents significant difficulties in implementation due mainly to difficulties associated with the system parameters identification process, which are especially expensive. The characteristics of the closed loop stability were analyzed by Lyapunov method. The experimental results obtained in closed loop attest the efficiency of the proposed control strategy.

No description available.

Escavadeiras hidráulicas são máquinas versáteis, amplamente utilizadas na construção civil e mineração. Máquinas melhores, mais produtivas, eficientes e que oferecem segurança ao operador são uma demanda constante da indústria. Devido a estes fatores, o controle para a automação de uma escavadeira hidráulica tem sido investigado. Este estudo tem o seu foco voltado para o controle do manipulador do equipamento, que é considerado como um dos elementos fundamentais para o desenvolvimento de uma escavadeira automática. Para desenvolver um sistema de controle viável, primeiramente, foi realizado a modelagem matemática dos subsistemas mecânico e hidráulico do manipulador; posteriormente esses modelos foram acoplados para representar a interação dos subsistemas. Todos os modelos desenvolvidos foram comparados com modelos de referência, obtidos a partir de softwares comerciais dedicados a modelagem de sistema dinâmicos. Tendo sido verificado a capacidade de representação física dos modelos, a fase de projeto do controlador para o manipulador foi iniciada. Para que o controlador seja eficiente, este deve ter duas propriedades essenciais: robustez para lidar com as incertezas e distúrbios severos, e adaptabilidade para lidar com um ambiente de operação altamente dinâmico. A fim de projetar um controlador que considera a dinâmica de cada subsistema do manipulador, a técnica de controle em cascata foi adotada. Esta consiste em dividir o sistema global em subsistemas, de tal forma que seja possível projetar um controlador para cada subsistema. Devido à complexidade do modelo matemático, técnicas avançadas de controle linear e não linear foram combinadas no projeto dos controladores dos subsistemas. O controlador sintetizado foi testado através de simulação numérica, em ambiente MATLAB/Simulink®, na execução de um ciclo completo de trabalho pelo manipulador. Os resultados obtidos foram considerados satisfatórios, mesmo na presença de incertezas, distúrbios severos e de ruídos. Posteriormente, na comparação desses resultados com os de outros controladores, ficou claro que o melhor desempenho foi obtido com o controlador proposto. Isto indica a possível aplicabilidade de tal controlador para a automação deste tipo de equipamento. / Hydraulic excavators are versatile machines, widely used in civil construction and in mining. Better, more productive, and efficient machines that offer operator safety are a constant industry demand. Due to these factors, the control for the automation of a hydraulic excavator has been investigated. This study focuses on the control of the equipment\'s manipulator, which is considered as one of the fundamental elements for the development of an automatic excavator. To develop a viable control system, first, the mathematical modeling of the mechanical and hydraulic subsystems of the manip-ulator was carried out; later these models were coupled to represent the interaction between the subsystems. All the developed models were compared with reference models, obtained from a commercial software dedicated to dynamic system modeling. Having verified the physical representation capacity of the analytical models, the de-sign phase of the controller was started. For the controller to be efficient, it must have two essential properties: robustness to deal with severe uncertainties and disturb-ances, and adaptability to handle a highly dynamic operating environment. To design a controller that considers the dynamics of each subsystem of the manipulator, the cascade control technique was adopted. This consists of dividing the global system into subsystems, in such a way that it is possible to design a controller for each sub-system. Due to the complexity of the mathematical model, advanced linear and non-linear control techniques were combined in subsystem controllers design. The synthe-sized controller was tested by numerical simulation, in MATLAB/Simulink® environ-ment, in the execution of a complete work operation by the manipulator. The results obtained were considered satisfactory, even in the presence of uncertainties, severe disturbances and noise. Subsequently, in the comparison of these results with those of others controllers, it was clear that the best performance was obtained with the pro-posed controller. This indicates the possible applicability of such a controller to the automation of this type of equipment.