MODEL PREDICTIVE CONTROL (MPC) OF INJECTION MOLDING MACHINES

THE INJECTION MOLDING MACHINE CAN BE VIEWED AS A HIGHLY COUPLED NONLINEAR TIME VARYING SYSTEM. MODERN MULTIVARIABLECONTROL IN CONJUNCTION WITH NONLINEAR IDENTIFICATION METHODSARE APPLICABLE TO SUCH A SYSTEM, AND ARE FAR MORE ADVANCED THAN THE CONTROL METHODS USED TODAY BY THE INJECTION MOLDINGINDUSTRY. THE RESEARCH PROPOSED HERE IS TO APPLY MODEL PREDICTIVE CONTROL (MPC) TO THIS NONLINEAR BATCH PROCESS. THE EFFORT WILL INVOLVE (1) MODELING OF THE INJECTION MOLDING PROCESS USING A POWERFUL NONLINEAR TECHNIQUE CALLED THE GROUP METHOD OF DATA HANDLING, AND (2) APPLYING THE DETERMINED DYNAMICS MODEL TO THE CONTROL OF THE MACHINE. THE ULTIMATE OUTPUT FROM THIS EFFORT (PHASE I-II) IS TO DEVELOP OFF LINE NUMERICAL METHODS TO INFER MODEL CHARACTERISTICS AND TO DOWNLOAD THE MODEL DESCRIPTION TO REAL-TIME MICROPROCESSOR ALGORITHMS FOR CONTROL OF THE MOLDING MACHINES SUB-SYSTEMS. IT IS EXPECTED THAT THE APPLICATION OF ADVANCED CONTROL TECHNIQUES TO THE INJECTION MOLDING MACHINE CAN SIGNIFICANTLY REDUCE THE CYCLE TIME REQUIRED TO GENERATE QUALITY PARTS. FUTHERMORE, THE TECHNIQUES DEVELOPED WILL BE APPLICABLE TO OTHER BATCH MANUFACTURING PROCESSES.