Ivan Carlos Franco

Nonlinear System Identification of a Refrigeration System

Applications of advanced control algorithms are important in the refrigeration field to achieve low-energy costs and accurate set-point tracking. However, the designing and tuning of control systems depend on dynamic mathematical models. Approaches like analytical modeling can be time-consuming because they usually lead to a large number of differential equations with unknown parameters. In this work, the application of system identification with the fast recursive orthogonal least square (FROLS) algorithm is proposed as an alternative to analytical modeling to develop a process dynamic model. The evaporating temperature (EVT), condensing temperature (CDT) and useful superheat (USH) are the outputs of interest for this system; covariance analysis of the candidate inputs shows that the model should be single-input–single-output (SISO). Good simulation results are obtained with two different validation data, with average output errors of 0.0343 (EVT model), 0.0079 (CDT model) and 0.1578 (USH model) for one of the datasets, showing that this algorithm is a valid alternative for modeling refrigeration systems.

An Adaptive Fuzzy Feedforward-Feedback Control System Applied to a Saccharification Process

Abstract In industrial bioprocess control, disturbance sources typically influences process variable regulation. These disturbances may reduce a system control performance or even affect the final bioproduct quality. Therefore, feedforward control is desired because it anticipates the effects caused by these disturbances in an attempt to keep the process variable at the setpoint value. However, designing a feedforward control law requires process modeling, which can be a tough task when dealing with bioprocesses that are intrinsically nonlinear and multivariable systems. Thus, an adaptive feedforward control law or other advanced control system is needed for satisfactory disturbance rejection. For this reason, a general fuzzy feedforward control system is proposed in this paper to replace the classical feedforward control, making it easier to implement the feedforward control action by avoiding nonlinear and multivariable process modeling. The adaptive fuzzy feedforward-feedback (A4FB) system was applied to a product concentration control loop in an enzymatic reactor, to reject disturbances caused by variations in the substrate and enzymatic solutions feed concentration. The results showed that the A4FB controller rejected much more disturbance effects than classical feedforward control law, demonstrating its advantage, supported by not only its simple implementation, but also its improved disturbance rejection.

Orthogonal Least Square Based Non-Linear System Identification of a Refrigeration System

Chillers are important part of several processes in the Chemical, Petro-Chemical, Pharmaceutical, Beverage and Food industries. Controlling these processes at an advantageous operating point is essential to achieve high productivity and profitability. Ultimately control system design and controller tuning depend on accurate process knowledge in the form of dynamic mathematical models. But attempts to develop analytical models often stumble upon problems such as unknown physical parameters. In this work, system identification, an established modeling technique, is used to build a non-linear dynamic model of a chiller from raw Input-Output data. Two dynamic nonlinear stochastic models where obtained, one more compact and the other with more terms but more precise, showing good simulation results and average prediction errors between 3.65%-5.23%.

Fuzzy Multivariable Control Strategy Applied to a Refrigeration System

Abstract The refrigeration process involves complex systems exhibiting nonlinearities and coupled behavior, so this paper aims to evaluate the comparative performance of a multivariable fuzzy logic-based control system and a classic multi loop PID. The process variables were the temperature of the secondary fluid (propylene glycol) outlet and the evaporating temperature. The manipulated variables were the compressor frequency speed and the pump frequency speed. Aspen Plus and Aspen Dynamics simulators were used to simulate the experimental prototype. The model was previously validated and linked with MATLAB software, where the controllers were implemented. Tuning of the fuzzy controller was performed through the membership functions and gains adjustments. The tuning of the multi loop PID controller was performed using the Ziegler-Nichols method and then a fine tuning was carried out. In order to fairly compare energy consumption and control effort, the tune of PID-based strategy was finished when similar values of Integral of Squared Error were achieved. Thus, very similar behavior for the process variables in both controllers. On the other hand, a great improvement in the control effort and energy saving was observed when the multivariable fuzzy controller was used in comparison to classic PID. The energy consumption was reduced by 25 % and the control effort by 96 % when the proposed strategy was used.

Utilização do protocolo de comunicação OLE for Process Control em processos industriais DOI: 10.5585/exacta.v8i3.2431

Neste artigo, propõe-se a utilização de um software matemático juntamente com o protocolo OLE for Process Control (OPC) para o desenvolvimento de sistemas de controle em processos industriais, transformando o software matemático em um sistema supervisório capaz não somente de monitorar o processo, mas também de desenvolver e implementar algoritmos de controle inteligente. Um estudo foi então realizado sobre a confiabilidade da comunicação OPC entre o software matemático, o Controlador Lógico Programável (CLP) e um sistema de refrigeração industrial. Nesta pesquisa, constatou-se que a comunicação é adequada para a aplicação, pois o software matemático utilizado na comunicação entre o CLP e o sistema de refrigeração apresentou boa confiabilidade referente à qualidade do sinal de comunicação, além de tempo real de comunicação. Conclui-se, portanto que essa forma de comunicação é uma potente ferramenta para o monitoramento, o desenvolvimento e a implementação de controladores avançados.