Title :
Model free predictive control for a nonlinear biological system with intelligent optimization approach
Author :
Mehrjerdi, Mojtaba Zaare ; Amoabediny, G. ; Moshiri, Behzad ; Ashktorab, Arman ; Araabi, B.N.
Author_Institution :
Control & Intell. Process. Center of Excellence, Univ. of Tehran, Tehran, Iran
Abstract :
Today the importance of life science and its related processes are undeniable. Modeling and control of these kind of processes are too complicate because of existence of delay in growth and also nonlinear behavior of micro-organisms. Model predictive control is one of the most popular advanced controlling strategies in this industry, however its dependence on accurate model for predicting future input and output values is limitating. If there is a way that could predict the future values of the process properly, it is possible to overcome to the existing challenges. In this paper we design a model free predictive controller by using a trained recurrent neural network as a predictor for prediction stage at MPC and using GA for solving the associated optimization problem that result the optimal control signal sequence.
Keywords :
biology; control system synthesis; genetic algorithms; microorganisms; neurocontrollers; nonlinear control systems; optimal control; prediction theory; predictive control; recurrent neural nets; GA; MPC; control design; controlling strategy; genetic algorithm; intelligent optimization approach; life science; microorganism; model free predictive controller; nonlinear biological system; optimal control signal sequence; optimization problem; prediction stage; predictor; trained recurrent neural network; Artificial neural networks; Biological cells; Predictive control; Predictive models; Trajectory; Aerated Flask; Biological System; GA; NNMPC;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561318
