Laser Beam Pointing Control With Piezoelectric Actuator Model Learning
IEEE Transactions on Systems, Man, and Cybernetics(2020)
摘要
The inherent hysteresis property of piezoelectric actuator (PEA) brings challenges to its modeling and control. This paper proposes a model learning method that is suitable for both forward and inverse PEA models. The hysteresis property is learned based on least squares support vector machines (LS-SVMs). A larger dataset is used for training LS-SVM to guarantee a good generalization performance. Support vectors pruning is utilized to reduce the model complexity. The rate-dependent property of PEA is identified as a linear dynamic submodel. Moreover, a pointing control system with two dual-PEA-axis steering mirrors is developed, which can regulate the 4-degree-of-freedom pose of a laser beam. The coordinated control of four PEAs is realized based on the Jacobian matrix. The learned inverse PEA models are used for the feedforward compensation of each PEA’s nonlinearity. A series of experiments were conducted to evaluate the proposed method’s effectiveness.
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关键词
Laser beams,Hysteresis,Laser modes,Training,Control systems,Computational modeling,Support vector machines
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