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Intelligent/adaptive control strategies for robot manipulators.

机译:机器人操纵器的智能/自适应控制策略。

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The objective of this thesis is to utilize the strategic advantages of intelligent/adaptive control and to develop such a paradigm to handle the complex problems in an expert domain. The two-level hierarchical structure of an intelligent/adaptive control scheme is considered by using robust adaptive controllers and fuzzy-logic rules. In the lower level, precise adaptive force/position controllers with fast convergence and robustness properties are considered where novel robust adaptive controllers with gain dynamics are introduced. In the upper level, the strategic rulebase is exploited to deal with uncertainties. Theoretical aspects of fuzzy-logic controllers are examined and analyzed in terms of stability issues. Guidelines for establishing a stable rulebase in the fuzzy feedback system are introduced. Finally, the quasi-static force control problem is selected as an example of integration of both levels including the manipulator dynamics and the uncertainty in the workspace.
机译:本文的目的是利用智能/自适应控制的战略优势,并开发这种范例来处理专家领域中的复杂问题。通过使用鲁棒的自适应控制器和模糊逻辑规则,考虑了智能/自适应控制方案的两级分层结构。在较低级别,考虑了具有快速收敛性和鲁棒性的精确自适应力/位置控制器,其中引入了具有增益动态特性的新型鲁棒自适应控制器。在高层,利用战略规则库处理不确定性。就稳定性问题,对模糊逻辑控制器的理论方面进行了检查和分析。介绍了在模糊反馈系统中建立稳定规则库的准则。最后,选择准静态力控制问题作为两个级别的集成示例,包括操纵器动力学和工作空间中的不确定性。

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