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- A Methodology to Design FPGA-based PID ControllersPublication . Lima, João; Menotti, Ricardo; Cardoso, João M. P.; Marques, EduardoThis paper presents a methodology to implement PID (Proportional, Integral, Derivative) controllers in FPGAs (Field-Programmable Gate Arrays) using fixed-point numerical representation. The Matlab/Simulink environment is used for modeling, simulation and evaluation the performance provided by different fixed-point representations using a given control process. A static bit-width analyzer is used to give a specialized fixed-point representation for each operand/operator in the controller system. After bit-width analysis, a VHDL represen-tation of the system is generated. Results show that the proposed methodology leads to shorten design cycles achieving important resource savings by employing specialized fixed-point repre-sentations.
- Neuro-genetic PID autotuning: time invariant casePublication . Lima, João; Ruano, AntonioThe Proportional, Integral and Derivative (PID) controllers are widely used in induxtrial applications. Their popularity comes from their robust performance and also from their functional simplicity.
- Neuro-genetic Pid autotuningPublication . Lima, João; Azevedo, Ana Beatriz da Piedade de; Duarte, N. M.; Fonseca, C. M.; Ruano, Antonio; Fleming, P. J.A new PID autotuning technique, involving neural networks and genetic algorithms is proposed. The validity of this approach is shown, through the results of several experiments. Special attention is given to the off-line training of one of the auto-tuner models, the criterion networks. Procedures used to obtain good training data are described.
- Comparison of off-line and on-line performance of alternative neural network modelsPublication . Lima, João; Ruano, AntonioThe Proportional Integral and Derivative (PID) controller is often used in industrial applications due to its functional simplicity and robust performance. Autotuning methods for these simple controllers are economically important. In order to accomplish this auto tuning in real time, without perturbing the closed-loop operation, models of criteria that are intended to be optimised are needed. In this paper, the ITAE criterion will be employed, as responses obtained with this criterion are well damped. In this paper neural networks are proposed as tools that allow these kinds of mappings. To improve the autotuner performance in a continuous operation, these models should be updated online. This way, the corresponding neural networks, after being trained off-line should be adapted on-line in real time. In the present work, the off-line and on-line performances of Multi-layer Perceptrons (MLPs), Radial Basis Function (RBFs) and Basis-Spline neural networks (B-splines), are analysed and compared.
- Modelo matemático + Sistema físico = Teoria dos SistemasPublication . Lima, JoãoAutomatic Control Systems are far and wide used in all modern and industrialized societies. Devices designed to control automatized tasks are each time more present from small plants to large industrial buildings. The development of mathematical models is a compulsory task for whom aim at analyzing or design any control systems. These mathematical models should reproduce some performance measures as accurate as possible. So, no matter the physical nature of the process we aim at control, an accurate mathematical model should be evaluate. So, the development of mathematical models can be considered an hi-level step over the physical nature of the system that we aim at analyze or design. For this reason the study of Systems Theory and Control Systems are considered transversal areas of the knowledge and them studies are compulsory in many branches of sciences and technologies in many universities all over the world. In spite of normal systems are non-linear the linearization procedure simplify the analysis and design of control systems and, depending on the accuracy of the model can give us good results.
- Exploiting Kant and Kimura's Matrix Inversion Algorithm on FPGAPublication . Perina, Andre Bannwart; Matias, Paulo; Marques, Eduardo; Bonato, Vanderlei; Lima, João; Kubatova, H.; Novotny, M.; Skavhaug, A.Matrix inversion for real-time applications can be a challenge for the designers since its computational complexity is typically cubic. Parallelism has been widely exploited to reduce such complexity, however most traditional methods do not scale well with the matrix size leading to communication bottlenecks. In this paper we exploit a decentralised parallel hardware architecture based on a strongly non-singular matrix inversion algorithm proposed by Kant and Kimura in 1978, which is a parallel-orientated method with communication mode independent of the matrix size, mitigating the problem of matrix scalability. The hardware architecture is implemented in two different approaches using fixed-point arithmetic: dedicated and shared. In the first approach a matrix can be inverted in linear time while the latter, for the best case, has a square complexity. Experimental results are demonstrated using a Stratix V GX FPGA. For instance, in dedicated approach an 8x8 matrix is inverted in 1.27us, while in shared approach a 64x64 matrix is inverted in 153.40us using 64 pipelined processing elements.
- Sintonia automática de controladores PID: uma abordagem neuro - genéticaPublication . Lima, João; Ruano, A. E.Os controladores PID são extensivamente utilizados em aplicações industriais. A popularidade deste tipo de controladores advém da sua simplicidade (apenas 3 termos para sintonizar) e robusto desempenho. Dado que os processos a controlar poderão variar ao longo do tempo, levando à necessidade de uma nova sintonia do controlador, métodos de sintonia automática de controladores PID revelam-se de grande interesse tanto prático como teórico. Na presente dissertação propõe-se uma técnica de sintonia automática do controlador PID, com base em metodologias de soft-computing. A sintonia de controladores pode ser vista como um problema de optimização simultânea de vários critérios assim, o sistema proposto incorpora algoritmos genéticos para esse propósito. Destinando-se o método desenvolvido a aplicações em tempo real, houve a necessidade de se proceder à modelação dos critérios de controlo. Este procedimento tem vantagem tanto a nível de consumo de tempo, como na prevenção de situações de instabilidade sempre possíveis durante um processo de optimização, e não sujeita o processo a perturbações necessárias ao processo de optimização; estes aspectos são de fundamental importância nas aplicações em tempo real. O problema de modelação de critérios de controlo bem como de parâmetros optimizados do controlador foi tratado utilizando-se redes neuronais. Foram testadas as capacidades de modelação e de adaptação de vários tipos de redes neuronais, nomeadamente perceptrão multi-camada, redes com funções de base radial e B-Splines. Os modelos neuronais a que se chegaram, juntamente com os algoritmos genéticos, formam alguns dos blocos constituintes do modelo de auto-sintonia neuro-genética que se propõe. Foi construído um simulador que implementa a presente arquitectura e valida a metodologia proposta.