针对移动机器人面临环境的复杂性和不确定性，传统控制算法已经无法精确地避开障碍物，找到一条最优路径来完成相应的任务。针对这个问题，本文提出了一种改进的智能控制算法——参数自整定模糊逻辑控制算法，通过利用MATLAB编程，对模糊变量及模糊控制器进行设计，在随机的环境中对模糊控制器的相关参数进行自动校正，使其不受外界环境的影响，还可以精确地避开相应的障碍物，保证机器人能够准确地到达目标点，在此基础上可以得到一条最优路径。这种智能算法有效地解决了目前移动机器人所面临的主要问题，同时还可使控制系统保持较好的性能，实验结果表明该方法的优越性和可行性。 In view of the complexity and uncertainty of the mobile robot’s environment, traditional control algorithms have been unable to accurately avoid obstacles and find an optimal path to complete the corresponding task. Aiming at this problem, this paper proposes an improved intelligent control algorithm—parameter self-tuning fuzzy logic control algorithm. By using MATLAB programming, the fuzzy variables and fuzzy controllers are designed. The parameters are automatically corrected so that they are not affected by the external environment, and the corresponding obstacles can be accurately avoided to ensure that the robot can accurately reach the target point. Based on this, an optimal path can be obtained. This intelligent algorithm effectively solves the main problems currently faced by mobile robots, and at the same time can keep the control system with good performance. Experimental results show the superiority and feasibility of the method.
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机译：针对移动机器人面临环境的复杂性和不确定性，传统控制算法已经无法精确地避开障碍物，找到一条最优路径来完成相应的任务。针对这个问题，本文提出了一种改进的智能控制算法——参数自整定模糊逻辑控制算法，通过利用MATLAB编程，对模糊变量及模糊控制器进行设计，在随机的环境中对模糊控制器的相关参数进行自动校正，使其不受外界环境的影响，还可以精确地避开相应的障碍物，保证机器人能够准确地到达目标点，在此基础上可以得到一条最优路径。这种智能算法有效地解决了目前移动机器人所面临的主要问题，同时还可使控制系统保持较好的性能，实验结果表明该方法的优越性和可行性。 In view of the complexity and uncertainty of the mobile robot’s environment, traditional control algorithms have been unable to accurately avoid obstacles and find an optimal path to complete the corresponding task. Aiming at this problem, this paper proposes an improved intelligent control algorithm—parameter self-tuning fuzzy logic control algorithm. By using MATLAB programming, the fuzzy variables and fuzzy controllers are designed. The parameters are automatically corrected so that they are not affected by the external environment, and the corresponding obstacles can be accurately avoided to ensure that the robot can accurately reach the target point. Based on this, an optimal path can be obtained. This intelligent algorithm effectively solves the main problems currently faced by mobile robots, and at the same time can keep the control system with good performance. Experimental results show the superiority and feasibility of the method.
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