The prevention, reduction and rescue of the disasters, which are concerned with the life and property safety of the people, are important parts of the national public safety. In extremely dangerous and poor post-disaster environments, the rescue robots are important aids which can assist the rescue personnel to do the rescue and search works. Now, the rescue robots can not only be used in city rescue, fire rescue, mine rescue, environmental and protection, but also have a good application background at the national defense, military and planet detection. This thesis is focused on the researches of control system design and servo control methods for coal mine rescue robot which are aimed to solve the problems of control system design and servo control during the design of a specified coal mine rescue robot. The thesis has been supported by the projects which belong to the field of relief and rescue operation dangerous robot technology in the National Key Foundation R&D Projects. Firstly, a kind of CAN-bus based distributed hardware architecture for the control system of the rescue robot is systematically presented for the coal mine rescue robots. At last, take the integrated temperature and humidity sensor as example, the architectures and design flows of software of the temperature and humidity sensor and carbon monoxide sensor which are designed for the coal mine rescue robot are introduced briefly. Secondly, a DSP and FPGA based reconfigurable multiple DC motors controller is designed to fit the Special working environment and high needs of flexibility and reliability of the coal mine rescue robot, and the software design flow are also analyzed. With the IPM which is specified selected, the controller can meet the needs of miniaturization and reliability of the control system of the coal mine rescue robot. At the same time, the reconfigurable features of hardware make the controller can be used in many occasions. Thirdly, to solve problem of the PID parameters optimization during the design of multiple DC motor controller, an improved adaptive genetic algorithm is proposed. Compared with the existing two kinds of adaptive genetic algorithm, the new adaptive genetic algorithm can decide crossover probability and mutation probability by the population itself, then, the user don’t need to select the crossover probability and mutation probability. Through the MATLAB simulation, the improved adaptive genetic algorithm can solve the problems of PID parame...
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