| Summary: | 碩士 === 國立臺北科技大學 === 電機工程系所 === 96 === The objective of this thesis is to propose a modified ant colony algorithm and apply it to fuzzy flow control. When executing the conventional ant algorithm to search the optima for the objective function, the convergence is slow during initial stage. The algorithm must detect the environment in the unknown space thoroughly. If the complexity of the space can be reduced, the searching efficiency is thus increased. To meet this requirement, this thesis adopts the area restricted concept to partition into the searching space.
Moreover, the conventional ant colony algorithm is suitable for solving a TSP-like problem. The main concern of the algorithm is different from that of designing a controller. To emphasize the characteristic of the proposed method, numerical examples are given via PID controller design. While tuning the proportional, integral, and derivative parameters, the conventional algorithm uses the same value to update the pheromone. It is not reasonable because different parameter sensitivity results in different control result. To solve this problem, the proposed method assigns different update coefficients according to the parameter sensitivity. In addition, based on Control System Transfer Protocol (CSTP), this thesis uses the proposed algorithm to regulate the scaling factors of the fuzzy controller for the Internet flow control problem.
Finally, this thesis utilizes MATLAB and NS2 software as a simulation platform to fulfill the PID controller and network flow control design, respectively. From the simulation results, it could be found that the area-restricted ant colony optimization algorithm has better performance and can reduce the variation of the transmission delay.
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