A simple design methodology of optimal model reference adaptive control (OMRAC) scheme with perturbation estimation for solving robust tracking problems is proposed in this thesis. The plant to be controlled belongs to a class of MIMO perturbed dynamic systems with input nonlinearity and time varying delay. The proposed robust tracking controller with a perturbation estimation scheme embedded is designed by using Lyapunov stability theorem. The control scheme contains three types of controllers. The first one is a linear feedback optimal controller, which is designed under the condition that no perturbation exists. The second one is an adaptive controller, it is used for adapting the unknown upper bound of perturbation estimation error. The third one is the perturbation estimation mechanism. The property of uniformly ultimately boundness is proved under the proposed control scheme, and the effects of each design parameter on the dynamic performance is also analyzed. An example is demonstrated for showing the feasibility of the proposed control scheme.

Orientador: Flavio Vasconcelos da Silva / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-07T21:48:37Z (GMT). No. of bitstreams: 1 Santos_ReginaLuciadeAndradedos_M.pdf: 2611251 bytes, checksum: 3243445f76398670aa1390de96139a08 (MD5) Previous issue date: 2006 / Resumo: Com o advento do sistema digital em rede (fieldbus) e a ampla divulgação das vantagens da utilização desta nova tecnologia aliada ao uso de instrumentos inteligentes, tornou-se inquestionável a melhora no desempenho e confiabilidade dos dados obtidos através deste sistema para o controle em novas plantas industriais ou em sistemas destinados à pesquisa tecnológica. Estratégias de controle clássicas, tais como o controle PID (proporcional ¿ integral ¿ derivativo), são largamente utilizadas no setor industrial devido à sua robustez e facilidade de implementação, embora limitações possam ser observadas quanto à adequação destes controladores às não-linearidades presentes nos sistemas reais. A utilização dos controladores adaptativos (baseados em parâmetros variáveis) permite tais adequações respeitando a dinâmica dos sistemas. Nas últimas décadas tem-se notado um significante aumento na aplicação da teoria de controladores avançados, entretanto, a sua utilização no setor produtivo ainda é incipiente. Apresenta-se, neste trabalho, uma automação híbrida alternativa para monitoramento, em tempo real, das variáveis de processo de um sistema para precipitação da enzima bromelina com supervisão, em tempo real, das condições do processo sob diferentes perturbações na carga, usando estratégia SISO em arquitetura de rede Fieldbus. Além disso, por se tratar de um bioprocesso, em batelada, as não linearidades e o aspecto essencialmente transiente da operação evidenciam a inevitável prioridade na aplicação dos controladores avançados, uma vez que os controladores convencionais possuem ação limitada neste tipo de sistema, garantindo a qualidade final da enzima obtida. Através dos resultados obtidos pôde-se comprovar a que ambos os controladores PID convencional e adaptativo tiveram um bom desempenho na manutenção da temperatura, porém houve um melhor desempenho com o PID adaptativo como foi observado pelos parâmetros de desempenho ITAE, overshoot e tempo de subida / Abstract: Fieldbus technology and intelligent sensors/actuators are increasingly being used in automated systems, opening up new possibilities for distributed control structures, mainly in new plants and research applications where is very important to have a flexible automation structure to different plant conditions with huge flow of information. Significant improvements have been seen in advanced controllers over the last years. However, linear PID controller is still applied extensively in industrial practice. The reason lies in its robustness and well-Known control design and implementation, although assumptions, simplifications, or lumping parameters are often made to build a mathematical model that may be far from the real situation. The behavior of most physical systems, especially bath systems, is nonlinear. Linear control may be effective for local operation, but is inadequate for controlling operations over a broad range. Adaptive controllers are nonlinear systems, which are commonly based on linear control theory. Despite many publications in the last decades illustrating advantages of adaptive controllers, this Kind of control is still not so common in industrial practice. One of reasons for the low incidence of application is relative difficulty to implement this controller. In this study, a comparative experimental design and tuning of conventional PID and adaptive PID controllers was developed for a pilot plant batch to precipitate of enzyme bromelain, using SISO strategy in fieldbus network architecture. The system was applied to the on line control of temperature of the extraction tank, involving a performance control analysis, under different load disturbances. From the results of this work, both controllers were considered suitable to control the temperature of the fedbatch tank. Nevertheless, the closed loop performance was improved under adaptive PID controller: the performance index ITAE, the overshoot and the rise time decreased. / Mestrado / Sistemas de Processos Quimicos e Informatica / Mestre em Engenharia Química

No description available.

No description available.

The coatings produced by an atmospheric plasma spray process (APSP) must be of uniform quality. However, the complexity of the process and the random introduction of noise variables such as fluctuations in the powder injection rate and the arc voltage make it difficult to control the coating quality that has been shown to depend upon mean values of powder particles' temperature and speed, collectively called mean particles' states (MPSs), just before they impact the substrate. Here we use a science-based methodology to develop an adaptive controller for achieving consistent MPSs. We first identify inputs into the APSP that significantly affect the MPSs, and then formulate a relationship between these two quantities. When the MPSs deviate from their desired values, the adaptive controller based on the model reference adaptive controller (MRAC) framework is shown to successfully adjust the input parameters to correct them. The performance of the controller is tested via numerical experiments using the software, LAVA-P, that has been shown to well simulate the APSP. The developed adaptive process controller is further refined by using sigma (σ) adaptive laws and including a low-pass filter that remove high-frequency oscillations in the output. The utility of the MRAC controller to achieve desired locations of NiCrAlY and zirconia powder particles for generating a 5-layered coating is demonstrated. In this case a pure NiCrAlY layer bonds to the substrate and a pure zirconia makes the coating top. The composition of the intermediate 3 layers is combination of the two powders of different mass fractions. By increasing the number of intermediate layers, one can achieve a continuous through-the-thickness variation of the coating composition and fabricate a functionally graded coating. / Doctor of Philosophy / Canned food sold in a grocery store have cans' interior surface coating with a polymer to increase the shelf life of the food. Similarly, many parts in an automobile have coatings to protect them from corrosion and possibly wear and tear. A process used to produce these coatings is rather complex and involves several variables. An undesired change these variables affects the coating quality. Automatically controlling a coating process is like a cruise control in a car. It should detect which variables have changed and either take appropriate corrective actions or shut down the process if it cannot be corrected or alert an operator to stop the process. In this work we have developed a controller to adaptively adjust the input parameters for an atmospheric plasma spray process (APSP) often used to produce thermal barrier coatings in gas turbines and blades of aircraft jet engines. These coatings hinder the flow of heat from the hot exhaust gases to the blades thereby prolonging their life span.

In this thesis, adaptive neural network controllers are designed for a high subsonic cruise missile. Two autopilot designs are included in the study using adaptive neural networks, namely an altitude hold autopilot designed for the longitudinal channel and a directional autopilot designed for heading control. Aerodynamic coefficients are obtained using missile geometry / a 5-Degree of Freedom (5-DOF) simulation model is obtained, and linearized at a single trim condition. An inverted model is used in the controller. Adaptive Neural Network (ANN) controllers namely, model inversion controllers with Sigma-Pi Neural Network, Single Hidden Layer Neural Network and Background Learning implemented Single Hidden Layer Neural Network, are deployed to cancel the modeling error and are applied for the longitudinal and directional channels of the missile. This approach simplifies the autopilot designing process by combining a controller with model inversion designed for a single flight condition with an on-line learning neural network to account for errors that are caused due to the approximate inversion. Simulations are performed both in the longitudinal and directional channels in order to demonstrate the effectiveness of the implemented control algorithms. The advantages and drawbacks of the implemented neural network based controllers are indicated.

Master’s thesis is focused on the adaptive controllers. The first theoretic part mainly describes the parametric identification, which belongs to the most important part of the adaptive controller’s structure. Classical identification methods (the recursive least squares methods) are firstly mentioned and afterwards the identification methods based on the neural network (the Marquardt-Levenberg algorithm and the new identification algorithm NIA inspired by the neural networks) are described. At the conclusion of the theoretic part there are mentioned the algorithm of the adaptive controller’s tuning which uses the identification parameters (the modified Z-N method) and the tested types of adaptive controllers. Particular results, which were found out by verifying of the adaptive controllers on the simulation and real models, are contained in second, the practical, part of the thesis. Finally, achieved results are compared with the classical discrete PID controller and with the adaptive controller of the B&R company.

No description available.

This thesis is devoted to the development of new approaches for control coordination of PSSs (power system stabilisers) and FACTS (flexible alternating current transmission system) devices for achieving and enhancing small-disturbance stability in multi-machine power systems. The key objectives of the research reported in the thesis are, through optimal control coordination of PSSs and/or FACTS devices, those of maintaining satisfactory power oscillation damping and secure system operation when the power system is subject to persisting disturbances in the form of load demand fluctuations and switching control. Although occurring less frequently, fault disturbances are also considered in the assessment of the control coordination performance. Based on the constrained optimisation method in which the eigenvalue-based objective function is minimised to identify the optimal parameters of power system damping controllers, the thesis first develops a procedure for designing the control coordination of PSSs and FACTS devices controllers. The eigenvalue-eigenvector equations associated with the selected electromechanical modes form a set of equality constraints in the optimisation. The key advance of the procedure is that there is no need for any special software system for eigenvalue calculations, and the use of sparse Jacobian matrix for forming the eigenvalue-eigenvector equations leads to the sparsity formulation which is essential for large power systems. Inequality constraints include those for imposing bounds on the controller parameters. Constraints which guarantee that the modes are distinct ones are derived and incorporated in the control coordination formulation, using the property that eigenvectors associated with distinct modes are linearly independent. The robustness of the controllers is achieved very directly through extending the sets of equality constraints and inequality constraints in relation to selected eigenvalues and eigenvectors associated with the state matrices of power systems with loading conditions and/or network configurations different from that of the base case. On recognising that the fixed-parameter controllers, even when designed with optimal control coordination, have an inherent limitation which precludes optimal system damping for each and every possible system operating condition, the second part of ii the research has a focus on adaptive control techniques and their applications to power system controllers. In this context, the thesis reports the development of a new design procedure for online control coordination which leads to adaptive PSSs and/or supplementary damping controllers (SDCs) of FACTS devices for enhancing the stability of the electromechanical modes in a multi-machine power system. The controller parameters are adaptive to the changes in system operating condition and/or configuration. Central to the design is the use of a neural network synthesised to give in its output layer the optimal controller parameters adaptive to system operating condition and configuration. A novel feature of the neural adaptive controller is that of representing the system configuration by a reduced nodal impedance matrix which is input to the neural network.

Commercial Aircraft Corporation of China, Ltd (COMAC)and Chinese Scholarship Council. / The aim of this thesis is to develop a real time PIO detection and mitigation system that consists of a detector based on short time Fourier transform(STFT) and autoregressive model(ARX) with exogenous inputs, together with an adaptive controller based mitigation system. The system not only detects the traditional PIO characteristics but also focuses on the trend of pilot behaviour by calculating the rate of change in the open loop crossover frequency. In the detection system, a sliding windowed STFT method was applied to identify the frequency and phase characteristics of the system via processing the signal of pilot input and aircraft state. An ARX model was also applied to get the rate of change of the crossover frequency. After detection, a PIO cue was shown on the primary flight display. A scheduled gain controller was coupled to provide PIO mitigation by varying stick input gain. Compensatory and tracking tests for the evaluation of this system were performed using a quasi-linear Boeing-747 aircraft model including nonlinear command gearing and actuator rate-limiting. Bandwidth and Gibson criteria were used to design PIO prone control laws for system evaluation experiments. Results from PIO tests conducted on desktop PCs were presented. These were analyzed and compared with those obtained from implementing the Real-time Oscillation Verifier module available in literature.