SYSTEM IDENTIFICATION AND CONTROL USING SINGULAR VALVE DECOMPOSITION SYSTOLIC ARRAYS

CURRENTLY AVAILABLE ALGORITHMS FOR SYSTEM IDENTIFICATION AND CONTROL ARE NOT COMPLETELY RELIABLE FOR AUTOMATIC IMPLEMENTATION ON MICROPROCESSORS IN REAL TIME. A NEW CLASS OF ALGORITHMS BASED UPON A GENERALIZED SINGULAR VALUE DECOMPOSITION IS BEING CONSIDERED FOR SYSTEM IDENTIFICATION, STATISTICAL MODEL ORDER DETERMINATION, MODEL ORDER REDUCTION, AND PREDICTIVE CONTROL. IN THIS APPROACH, THE ALGORITHMS ARE COMPUTATIONALLY STABLE AND NUMERICALLY ACCURATE AND CANBE IMPLEMENTED ON SYSTOLIC ARRAY PROCESSORS USING RECENTLY DEVELOPED ALGORITHMS RESULTING IN A CONSIDERABLE SPEEDUP. THIS APPROACH IS BASED UPON A RECENT GENERALIZED CANONICAL VARIATE ANALYSIS METHOD FOR DETERMINING THE OPTIMAL STATE OF A RESTRICTED ORDER IN SYSTEM IDENTIFICATION, REDUCED ORDER STOCHASTIC FILTERING, AND MODEL PREDICTIVE CONTROL. THIS PERMITS A UNIFIED APPROACH TO THE SOLUTION OF THESE PROBLEMS FROM THE VIEWPOINTS OF A PREDICTION PROBLEM AS WELL AS AN APPROXIMATION PROBLEM. THIS INVESTIGATION, IF SUCCESSFUL, WOULDBENEFIT DEFENSE SYSTEMS THAT REQUIRE ONLINE ADAPTIVE CONTROL INCLUDINGFLUTTER SUPPRESSION, FAILURE DETECTION, CONTROL OF LARGE SPACE STRUCTURES, AND TARGET DETECTION AND TRACKING. COMMERICAL APPLICATIONS INCLUDE CHEMICAL PROCESS CONTROL, CONTROL AND IDENTIFICATION OF POWER PLANTS, AND ADAPTIVE CONTROL IN INDUSTRIAL MANUFACTURING AND ROBOTICS.