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Uncertainty-Robust Design of Interval Type-2 Fuzzy Logic Controller for Delta Parallel Robot

机译:Delta并联机器人区间2型模糊逻辑控制器的不确定鲁棒设计。

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Type-2 Fuzzy Logic Controllers (T2 FLCs) have been recently applied in many engineering areas. While understanding the control potentials of T2 FLCs can still be considered an open question researchers, commonly claim superiority of T2 FLCs based on a limited exploration of the space of design parameters. The contribution of this work is based on a problem-driven design of uncertainty-robust Interval T2 (IT2) FLCs. The presented methodology starts with a baseline optimized T1 FLC. Next, a group of IT2 FLCs is designed using partially dependent approach by symmetrically blurring the membership functions around the original T1 fuzzy sets. This constrained design space allows for its systematic exploration and analysis. The performance of the designed controllers was evaluated on delta parallel robot hardware under two kinds of commonly encountered uncertainties: i) sensory noise and ii) uncertain system parameters. The experimental results showed that IT2 FLCs provide improved control performance against T1 FLCs when appropriate design of IT2 fuzzy sets is performed. In addition, it was demonstrated that excessive amount of “type-2 fuzziness” in the IT2 FLC design leads to rapid performance degradation.
机译:Type-2模糊逻辑控制器(T2 FLC)最近已在许多工程领域中应用。尽管了解T2 FLC的控制潜力仍然可以看作是一个开放问题的研究人员,但他们通常基于对设计参数空间的有限探索而声称T2 FLC具有优越性。这项工作的贡献是基于不确定性强的区间T2(IT2)FLC的问题驱动设计。提出的方法从基线优化的T1 FLC开始。接下来,通过部分模糊围绕原始T1模糊集的隶属函数,使用部分依赖的方法设计一组IT2 FLC。这种受限的设计空间允许对其进行系统的探索和分析。在两种常见的不确定性条件下,在增量并行机器人硬件上评估了所设计控制器的性能:i)感官噪声和ii)不确定的系统参数。实验结果表明,通过对IT2模糊集进行适当的设计,IT2 FLC可以提供相对于T1 FLC更好的控制性能。此外,事实证明,IT2 FLC设计中过多的“ 2型模糊性”会导致性能快速下降。

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