विधियों की तुलना करें

	मॉडल प्रेडिक्टिव कंट्रोल	अनुकूली नियंत्रण
क्षेत्र	नियंत्रण सिद्धांत	नियंत्रण सिद्धांत
परिवार	Machine learning	Machine learning
उद्भव वर्ष	1978	1983
प्रवर्तक	Jacques Richalet	Karl J. Astrom
प्रकार	algorithm	algorithm
मौलिक स्रोत	Richalet, J., Rault, A., Testud, J., & Papon, J. (1978). Model predictive heuristic control. Automatica, 14(5), 413-428.	Astrom, K. J., & Wittenmark, B. (1983). Computer-Controlled Systems: Theory and Design. Prentice Hall.
उपनाम	MPC, Receding Horizon Control	Self-Tuning Control, Parameter Estimation Control
संबंधित	5	3
सारांश	Model Predictive Control (MPC) is an advanced control strategy that uses an explicit process model to predict future system behavior over a finite horizon and solves an optimization problem at each control step. First formalized by Richalet et al. in 1978, MPC has become the dominant approach in process control industries, from chemical plants to autonomous vehicles, because it naturally handles constraints and can optimize multiple objectives simultaneously.	Adaptive Control is a control strategy that adjusts controller parameters in real-time based on online system identification to maintain performance despite changing plant dynamics or uncertain parameters. Pioneered by Astrom and Wittenmark, adaptive control enables robust operation in time-varying environments, from aircraft with fuel depletion to industrial systems with aging components.