High performance controller for drying processes

Abstract

ABSTRACT. This paper proposes a high performance nonlinear fuzzy multi-input-multi-output controller for a drying control process. The highly nonlinear characteristics of drying processes make classical control theory unable to provide the same performance results as it does in more well behaved systems. Advanced control strategies may be used to design temperature, relative humidity and air velocity nonlinear tracking controllers to overcome its highly non-linear dynamics over the whole drying operating conditions. Open-loop experiments were carried out to collect experienced-based knowledge of the process. PID and Fuzzy logic (FLC) real-time-based controllers were designed to perform food drying tests and compared without controllers' retuning. Absolute errors reached by FLC-based controller were 3.71 and 3.93 times lower than PID for temperature and relative humidity, respectively.Keywords: drying, Fuzzy logic controller, PID controller, relative humidity, temperature, air velocity.Controlador de alta performance para processos de secagem RESUMO. Este trabalho propõe um controlador difuso não-linear, de alto desempenho, para o controle do processo de secagem. As características altamente não-lineares dos processos de secagem tornam a teoria de controle clássica incapaz de fornecer os mesmos resultados de desempenho como acontece em sistemas lineares. Estratégias de controle avançado podem ser usadas para projetar controladores não-lineares de temperatura, umidade relativa e velocidade do ar, para superar a sua dinâmica não-linear ao longo de todas as condições operacionais de secagem. Foram realizados ensaios em malha aberta, na instalação experimental de secagem, a fim de conhecer a dinâmica do processo e obter dados para o projeto dos controladores. Foram projetados controladores em tempo real, utilizando-se o controle PID e o controle por Lógica Difusa (FLC,) para realizar testes de controle dos parâmetros de secagem, comparando-se as respostas de ambos os controladores. Os erros absolutos atingidos pelos controladores difusos foram 3,71 e 3,93 vezes menores que os obtidos pelo controle PID, para o controle de temperatura e umidade relativa do ar, respectivamente.Palavras-chave: secagem, controlador difuso, controlador PID, umidade relativa, temperatura, velocidade do ar.

Temperature Control of Heating Zone for Drying Process: Effect of Air Velocity Change

“…Currently, there are many control techniques used for the food drying system such as herb [5], gain [6], codfish [7][8], and fruit [9]. Nafeh et al [5] investigated a temperature control in a PV-Wind medical herb dryer system by using on/off controller that showed the high capability of the proposed technique in controlling the drying temperature.…”

“…Han et al [6] used a model predictive control (MPC) system based on neural network which was designed and tested on two model corn dryers that the control method of the system can be used in drying process control. Boeri et al experimentally investigated the optimized operating drying control for temperature, relative humidity and air velocity parameters by using fuzzy logic approach [7] and also proposed the multiinput-multi-output-based PID and Fuzzy logic (FLC) controller for a drying control process [8]. Geddes [9] implemented an internal model control (IMC) model to the temperature controller for fruit dryer process in which the simulation results showed that IMC controlled system could achieve the requirement of providing offset-free responses at steady state.…”

CONVECTIVE DRYING KINETICS OF YACON (Smallanthus sonchifolius Poepp. Endl.) SLABS AND EVALUATION OF THE DRYER PID TEMPERATURE CONTROL SYSTEM

“…As mentioned above, temperature and air velocity are factors affecting water removal rate during food drying (Boeri et al, 2013). Therefore, the control of these factors is very important in drying, as the desired moisture content of the food will be achieved if the temperature and air velocity are appropriate.…”