Hydraulic power and other kinds of disturbance in a linear motor-direct drive actuator (LM-DDA) have a great impact on the\nperformance of the system. A mathematical model of the LM-DDA system is established and a double-loop control system is\npresented. An extended state observer (ESO) with switched gain was utilized to estimate the influence of the hydraulic power and\nother load disturbances. Meanwhile, Radial Basis Function (RBF) neural network was utilized to optimize the parameters in this\nintelligent controller. The results of the dynamic tests demonstrate the performance with rapid response and improved accuracy\ncould be attained by the proposed control scheme.
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