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Implementation and study of a novel approach to control adaptive cooperative robot using fuzzy rules
International Journal of Information Technology Pub Date : 2020-04-25 , DOI: 10.1007/s41870-020-00459-z
Ganesh Enthrakandi Narasimhan , J. Bettyjane

The function of an Independent Robot has demanding conflicts and a perfect balance is required to minimize the conflicts along with a degree of capability. This paper talks about two co-operating mobile robots with a multilayer control system which utilizes Boolean logic to enable the significance of a relative behaviour. Therefore the fuzzy system takes its role as an arbiter that has the ability to control conflicting behaviours. This makes the robots to perfectly move on the near enabled minimum area. The array of vectors has been changed by the adaptive mechanism originated from the online analysis of the fuzzy rule. The strategy of the neural dynamics is employed here which has a control system as an unstable structure and study the system and its adaptability through phase stressed condition. This process is achieved by Suppression rules using Fuzzy Technique which allows the system to move in a steady state. This paper proves that the robots present in the unstructured environment enable an unstable state to a stable condition that increase the probability of Robots reaching its desired stability goal. A model is created using Matlab tool and simulation are performed in Matlab Simulink model. The novelty of work is controlling the robots in uncontrolled environment and also in multitasking environment.



中文翻译:

一种基于模糊规则的自适应机器人控制新方法的实现与研究

独立机器人的功能存在苛刻的冲突,因此需要完美的平衡,以最大程度地减少冲突以及一定程度的能力。本文讨论了两个具有多层控制系统的协作移动机器人,该系统利用布尔逻辑来实现相对行为的重要性。因此,模糊系统起着仲裁员的作用,它具有控制冲突行为的能力。这使机器人可以在接近启用的最小区域上完美移动。向量数组已通过源自模糊规则在线分析的自适应机制进行了更改。这里采用神经动力学策略,该策略具有作为不稳定结构的控制系统,并通过相应力条件研究该系统及其适应性。此过程是通过使用模糊技术的抑制规则来实现的,该规则允许系统在稳定状态下移动。本文证明了存在于非结构化环境中的机器人可以使不稳定状态变为稳定状态,从而增加了机器人达到其所需稳定目标的可能性。使用Matlab工具创建模型,并在Matlab Simulink模型中进行仿真。工作的新颖性在于在不受控制的环境以及多任务环境中控制机器人。使用Matlab工具创建模型,并在Matlab Simulink模型中进行仿真。工作的新颖性在于在不受控制的环境以及多任务环境中控制机器人。使用Matlab工具创建模型,并在Matlab Simulink模型中进行仿真。工作的新颖性在于在不受控制的环境以及多任务环境中控制机器人。

更新日期:2020-04-25
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