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A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion

机译:一种新颖的自组织PID控制移动机器人运动的方法

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A novel self-organizing fuzzy proportional-integral-derivative (SOF-PID) control system is proposed in this paper. The proposed system consists of a pair of control and reference models, both of which are implemented by a first-order autonomous learning multiple model (ALMMo) neuro-fuzzy system. The SOF-PID controller self-organizes and self-updates the structures and meta-parameters of both the control and reference models during the control process "on the fly". This gives the SOF-PID control system the capability of quickly adapting to entirely new operating environments without a full re-training. Moreover, the SOF-PID control system is free from user- and problem-specific parameters and is entirely data-driven. Simulations and real-world experiments with mobile robots demonstrate the effectiveness and validity of the proposed SOF-PID control system.
机译:本文提出了一种新颖的自组织模糊比例 - 积分衍生物(SOF-PID)控制系统。所提出的系统包括一对控制和参考模型,两者都是由一阶自主学习多型号(ALMMO)神经模糊系统实现的。 SOF-PID控制器在控制过程中自组织和自动更新控制和参考模型的结构和元参数“在飞行”中。这为SOF-PID控制系统提供了快速适应完全新的操作环境的能力,而无需全面重新培训。此外,SOF-PID控制系统没有特定于用户和问题的参数,并且完全是数据驱动的。使用移动机器人的模拟和现实世界实验证明了所提出的SOF-PID控制系统的有效性和有效性。

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