KENDALI MODEL PREDIKTIF TERDISTRIBUSI BERBASIS TEORI PERMAINAN DINAMIS KOOPERATIF - , SUTRISNO; , Dr. Salmah, M.Si ([Yogyakarta] : Universitas Gadjah Mada, 2012)
Systemwide control problem is a problem that contains several subsystems and involving interaction each other. Model Predictive Control (MPC) is an optimal control technique that calculate the optimal control action by makes the state and input prediction along horizon, then apply the first element of the optimal control sequence that calculated using optimization technique. The classic MPC (only for single system) can be applied for systemwide using decentralized or centralized approach, but the decentralized approach ignoring the interaction, so it can made the bad performance, whereas the centralized approach is not flexible and involving the large scale computation. To handle these problems, MPC can be applied for each subsystem using distributed approach. Distributed MPC is based on cooperative dynamic game theory, where the subsystems is reputed as players, then this problem solved by finding the Pareto solution (Feasible-Cooperation-MPC), that continued by finding the Nash-Bargaining solution (Nash-Bargaining-MPC), namely the Pareto solution that determined according to the disagreement point of players. The Pareto and Nash-Bargaining solution was determined using weighting of objective functions. We can prove that distributed MPC gives equilibrium point 0 is asymptotical stable. Distributed MPC was applied to control an irrigation canal that has 5 subsystems and involves a branch. This study case was simulated using MATLAB to illustrate the performance of this control technique. From the results, the Nash-Bargaining- MPC with the proportional weighting to the control load gives the fewest total cost.