Committee: 

Dr. F. Zhang, Advisor    

Dr. Coogan, Chair

Dr. Zhou

Abstract:

The objective of the proposed research is developing a novel contention-resolving model predictive controller to co-design optimal priorities and control laws which minimize the overall performance degradation caused by contentions in coupled control systems with constrained resources. The co-design problem is formulated as a mixed integer optimization problem with a very large search space, rendering difficulty in computing the optimal solution. To solve the problem, the proposed contention-resolving model predictive control algorithm can dynamically assign priorities and compute an optimal control. The priority assignment can be determined using a sample-based approach without excessive demand on computing resources and optimal controls can be computed iteratively following the order of the assigned priorities. The proposed contention-resolving model predictive control can be proved to find the optimal solution. The effectiveness of the proposed method will be verified through both simulations and experiments considering multiple practical applications.