Title :
A structured PENN controller for a MIMO process
Author :
Ishida, Masaru ; Ohba, Takehiro
Author_Institution :
Res. Lab. of Resources Utilization, Tokyo Inst. of Technol., Yokohama, Japan
Abstract :
This paper presents a neural net controller for a multi-input, multi-output (MIMO) process. This controller is based on the PENN (Policy and Experience driven Neural Network) method and is structured with small controllers for SISO processes. The characteristic feature of this scheme is that these PENN controllers cooperate with each other and search for the best cooperation. The simulation results of a crystal-growth process indicate that the proposed controller has the ability to learn the interactions between control variables
Keywords :
MIMO systems; cooperative systems; genetic algorithms; learning (artificial intelligence); neurocontrollers; process control; search problems; MIMO process control; Policy and Experience Neural Network; SISO process; control variable interactions; cooperative control; crystal-growth process simulation; genetic algorithms; learning; multi-input multi-output process; neural net controller; search; structured PENN controller; Assembly; Control systems; Laboratories; MIMO; Neural networks; Noise reduction; Noise robustness; Process control; Steady-state; Timing;
Conference_Titel :
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-2902-3
DOI :
10.1109/ICEC.1996.542354
