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Aiming at the problem of slow speed in image matching,anti-interference difference and relatively poor ability to resist deformation,proposed a fast image matching method based on artificial fish swarm algorithm (AFSA). In the same test environment,Compared with the image matching method based on particle swarm optimization (PSO) algorithm and found,the method is superior to image matching method based on particle swarm optimization,in matching speed and noise resistance ability and deformation resistance ability has a marked improvement.

The optimal design approach of the PID controller was proposed in this paper, based on Artificial Fish Swarm Algorithm (AFSA) for the matter of the optimization of the brushless DC motor controller. In the experiment, through the analysis of the basic principles of artificial fish swarm algorithm, appropriate performance index was selected as fitness function, specific design procedures were given to optimize parameters of PID controller, The experimental results indicate that: Artificial Fish Swarm Algorithm optimized PID controller enables the brushless DC motor speed control system response faster, small overshoot, effectively improve the dynamic performance of a brushless DC motor control system.