Design of Fuzzy Decision Adaptive Optimal Controller for Multi-objective Optimization Problems
Date Issued
2015
Date
2015
Author(s)
Lai, Po-Jen
Abstract
Multi-objective optimization concerns about optimization problems involving more than one objective function to be optimized simultaneously. Conventionally, multi-objective optimization problems are solved by the weighted-sum approach or the genetic algorithm. However, the weighted-sum approach is not able to deal with situations concerning different preference, and the genetic algorithm is hard to use in real-time optimization and control. This thesis proposes the fuzzy decision adaptive optimal control algorithm to solve the multi-objective optimization problem. The objective of optimization is defined to minimize a cost function which is the fuzzy association of many individual cost functions. The fuzzy association can adapt the weight of each individual cost function to changes in the environmental condition or decision making factor. Then, optimization is achieved by implementing the adaptive optimal control algorithm to minimize the cost-to-go until getting a convergent result. The proposed fuzzy decision adaptive optimal control algorithm is verified in the energy management of a fuel-cell hybrid vehicle. It is shown that, by introducing the fuzzy association, the cost function for energy management can adapt to the vehicle speed and the state of charge (SoC) of the energy storage system (ESS). Thus, the optimal energy management strategy will maintain a higher SoC at a lower speed that prepares the ESS to supply power for acceleration. Conversely, the optimal energy management strategy will maintain a lower SoC at a higher speed that prepares the ESS to retrieve regenerated power.
Subjects
Multi-objective optimization
Adaptive optimal control algorithm
Energy management
Type
thesis