Fuzzy Logic Control in Autonomous Robotics:
نویسندگان
چکیده
Autonomous robot systems require complex control systems. Fuzzy Logic, a mathematical system developed by Professor Lotfi Zadeh, helps to reduce the complexity of modeling nonlinear problems. In the 1990s, Motorola developed the MC68HC12 microcontroller with native Fuzzy Logic instructions. This research determined the effectiveness of the MC68HC12’s Fuzzy Logic instructions for robotic control. This research involved designing a robotic platform using the MC68HC12 and testing binary logic control systems against Fuzzy Logic control systems. The research analyzed the two systems using four criteria: (1) the size of memory required to develop the control system, (2) the ease of writing the control software, (3) how well the control system managed the functions of the robot, and (4) the overall processing power of the system. The results showed that Fuzzy Logic uses less memory than binary logic and is much easier to design, although more difficult to program initially. Fuzzy Logic can control more functions of the robot and has greater processing capabilities. The power, ease of use, and small size of Fuzzy Logic instructions make Fuzzy Logic a practical solution to autonomous robotic control systems.
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