Self-adapting control structure for active damping of the servomechanism residual vibration

D. Lindr, Sevil A. Ahmed
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Abstract

This paper describes an approach that leads to increased robustness of the model based active damping control (so called SEM) structure against servomechanism residual frequency variation due to changing the parameters of the servomechanism (such as length of the crane rope or weight of carried load). SEM control structure uses the mathematical model of the servomechanism to generate the final active damping correction signal. This type of control structures typically suffer from the high dependency on compliance mathematical model with real physical system of the servomechanism. The compliance has a major effect on the effectiveness of active damping but also to the inherent stability of control system. Otherwise, the mathematical model does not produce the correct frequency of residual vibration and because of this can hardly damp the real servomechanism vibration. This is why we focus on self-adaptation of the active adaptation of mathematical model parameters using an artificial intelligence technique such as fuzzy logic. Fuzzy systems are widely used in modelling of unknown and dynamically changing parameters likewise in uncertainty compensation. Fuzzy modelling approach of certain parameter of the servomechanism model is going to be presented and validated.
主动阻尼伺服机构残余振动的自适应控制结构
本文描述了一种方法,该方法可以提高基于模型的主动阻尼控制(所谓的SEM)结构对由于改变伺服机构参数(如起重机绳的长度或负载重量)而导致的伺服机构剩余频率变化的鲁棒性。SEM控制结构利用伺服机构的数学模型产生最终的主动阻尼修正信号。这类控制结构的特点是高度依赖于伺服机构真实物理系统的顺应性数学模型。柔度不仅对主动阻尼的有效性有重要影响,而且对控制系统的固有稳定性也有重要影响。否则,数学模型不能产生正确的残余振动频率,因此很难抑制伺服机构的实际振动。这就是为什么我们关注使用模糊逻辑等人工智能技术对数学模型参数进行主动自适应的原因。模糊系统广泛应用于未知和动态变化参数的建模和不确定性补偿。提出并验证了伺服机构模型某些参数的模糊建模方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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