Inverse Control of Cable-driven Parallel Mechanism Using Type-2 Fuzzy Neural Network
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摘要: 由于建立精确数学模型的困难以及控制过程中各种不确定性的存在, 柔索驱动并联机构的水平调节具有一定的难度. 针对该问题, 提出了一种基于二型模糊神经网络的逆控制方案. 该控制方案中的二型模糊神经网络实现了对水平调节过程逆动态的逼近以及对各种不确定性的处理. 采用迭代最小二乘算法对二型模糊神经网络区间权重进行了优化. 最后, 将基于二型模糊神经网络的逆控制方案在实际的控制对象上进行了实验, 并与其相对应的基于一型模糊神经网络的逆控制方案进行了比较. 实验结果表明所提出的控制方案是有效的且采用二型模糊神经网络时能获得更好的控制效果.Abstract: The level adjustment of cable-driven parallel mechanism is challenging due to the difficulty in obtaining an accurate mathematical model and the fact that different sources of uncertainties exist in the adjustment process. This paper presents a type-2 fuzzy neural network (T2FNN) based inverse control scheme for the level adjustment process. The T2FNN, whose consequent interval weights are trained by the iterative least squares estimation method, is used to approximate the inverse dynamics of the process and to handle uncertainties. Finally, the proposed control scheme and its counterpart --- type-1 fuzzy neural network based inverse control scheme --- are compared and implemented for leveling the cable-driven parallel mechanism.
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Key words:
- Inverse control /
- type-2 fuzzy logic /
- neural network /
- parallel mechanism
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