B-splines neural network assisted PID autotuning

This papers describes an extantion of previous works on the subject of neural network proportional, integral and derivative (PID) autotuning. Basically, neural networks are employed to supply the three PID parameters, according to the integral of time multiplied by the absolute error (ITAE) criterion, to a standard PID controller.

B-splines neural networks assisted PID autotuning

This paper describes previous works (1), (2), on neural network pid autotuning. Basically, neural networks are employed to supply PID parameters, according to the ITAE criterion, to a standard PID controller.

Recent developments in neural network PID autotuning

PID controllers are widely used in industrial applications. Because the plant can be time variant, methods of autotuning of this type of controllers, are of great economical importance, see (Astrom, 1996). Since 1942, with the work of Ziegler and Nichols (Ziegler and Nichols, 1942), several methods have been proposed in the literature. Recently, a new technique using neural networks was proposed (Ruano et al., 1992). This technique has been shown to produce good tunings as long as certain limitations are met.

New methods for PID autotuning

In this paper a recent approach for PID autotuning, involving neural networks, is ferther developed. To make this approach adaptive, optimal PID values must be known on-line. In this paper neural network models of tuning criteria, together with the use of genetic algorithms, are proposed to solve this problem.

Neural networks assisted PID autotuning

The Proportional, Integral and Derivative (PID) controllers are standard building blocks for industrial automation. Their popularity comes from their rebust performance and also from their functional simplicity.

Neural network assisted autotuning of industrial PID controllers

A recent servey (1) has reported that the majority of industrial loops are controlled by PID-type controllers and many of the PID controllers in operation are poorly tuned. poor PID tuning is due to the lack of a simple and practical tuning method for avarage users, and due to the tedious procedurs involved in the tuning and retuning of PID controllers.

Comparison of alternative approaches to neural network PID autotuning

In this paper, a scheme for the automatic tuning of PID controllers on-line, with the assistance of trained neural networks, is proposed. The alternative approaches are presented and compared.

Neural networks assisted PID autotuning

A scheme of automatically tuning the existing industrial PID controllers using neural networks is proposed. The scheme estimates the process critical data on-line in proportional control mode.

Um modelo em simulink para sintonia automática de controladores PID usando redes neuronais

The PID controllers are widely used in industry. Whether because the plant is time-varying, or because of components ageing, these controllers need to be regularly retuned. During the last years, several methods have been proposed for PID autotuning.

Connectionist approach to PID autotuning

Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulatores comes from their rebust performance in a wide range of operationg conditions, and also from their functional simplicity, which makes them suitable for manual tuning.

A neural network PID autotuner

Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. Their popularity comes from their rebust performance and also from their functional simplicity. Whether because the plant is time-varying, or because of components ageing, these controllers need to be regularly retuned.

A connectionist approach to PID autotuning

Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulators comes from their rebust performance in a wide range of operating conditions, and also from their functional simplicity, which makes them suitable for manual tuning.

New methods for PID autotuning

Despite the developments in the control theory and technology achieved in the last decade, PID controllers still remain the type of controller most used in industry. This fact is due to its simplicity (only three terms to tune) and to their robust performance.

Métodos de soft computing para la estimación no invasiva de la temperatura en medios multicapa empleando ultrasonido retrodisperso

La seguridad y eficacia de las terapias térmicas están ligadas con la determinación exacta de la temperatura, es por ello que la retroalimentacón de la temperatura en los métodos computacionales es de vital importancia.

Instrumentação e controlo para regulação de pH em sistemas de cultivo de organismos aquáticos

A Ria Formosa é um tesouro ambiental sem paralelo, preservando uma fauna e flora únicas no mundo. A riqueza deste habitat é de enorme importância para a região, e extremamente apetecível para cientistas oriundos de todas as partes do globo, que aqui frequentemente se deslocam para conduzirem estudos científicos e experiências. O Centro de Ciências do Mar (CCMAR) da Universidade do Algarve (que inclui o Centro Experimental do Ramalhete) conduz estudos e experiências neste palco, estudos que são de inquestionável valor para o conhecimento e desenvolvimento científico. Um assunto que está a merecer a atenção da comunidade científica mundial nos últimos anos é a questão da acidificação dos oceanos. A diminuição gradual do pH das águas pode vir a ter graves repercussões nos ecossistemas marinhos, e o Centro Experimental do Ramalhete tem vindo a conduzir experiências com fauna e flora provenientes da Ria Formosa em águas com níveis de pH mais reduzido, condições que se prevê que os oceanos venham a ter no futuro. Os equipamentos de instrumentação e controlo a que o Centro tem acesso condicionam as experiências que ali são levadas a cabo pelos investigadores, pelo que o desenvolvimento de equipamentos adequados incorporando tecnologias apropriadas permitiria a realização de novas e melhores experiências no campo da biologia marinha. Ao nível do controlo existe uma lacuna no mercado, entre controladores para aquariofilia demasiado simples e controladores industriais demasiado dispendiosos e complexos. Esta dissertação pretende colmatar essa lacuna através do desenvolvimento de um protótipo de um sistema distribuído microcontrolado para aquisição de dados e controlo de pH que vá ao encontro das necessidades dos investigadores do Centro e que se pretende simples, modular, flexível, económico e expansível no futuro. O foco centra-se no desenvolvimento da instrumentação necessária para as medições de temperatura e pH, e depois no estudo de uma malha de controlo PID utilizando como base um modelo do sistema obtido através de resultados experimentais, para o controlo automático do pH.