Abstract
This paper investigates the application of proposed neural MIMO NARX model to a nonlinear 2-axes pneumatic artificial muscle (PAM) robot arm as to improve its performance in modeling and identification. The contact force variations and nonlinear coupling effects of both joints of the 2-axes PAM robot arm are modeled thoroughly through the novel dynamic inverse neural MIMO NARX model exploiting experimental input-output training data. For the first time, the dynamic neural inverse MIMO NARX Model of the 2-axes PAM robot arm has been investigated. The results show that this proposed dynamic intelligent model trained by Back Propagation learning algorithm yields both of good performance and accuracy. The novel dynamic neural MIMO NARX model proves efficient for modeling and identification not only the 2-axes PAM robot arm but also other nonlinear dynamic systems.
Highlights
Rehabilitation robots up to now begin to be applied for treatment of patients suffering from trauma or stroke
Inverse Neural MIMO NARX model used in this paper is a combination between the Multi-Layer Perceptron Neural Networks (MLPNN) structure and the ARX model
The full connected Multi-Layer Perceptron (MLPNN) network well as the range (4.5 – 5.5) [V] and the shape architecture composes of 3 layers with 5 of PRBS-2 voltage input applied to rotate the 2nd joint of the 2-axes pneumatic artificial muscle (PAM) robot arm is neurons in hidden layer is selected
Summary
Rehabilitation robots up to now begin to be applied for treatment of patients suffering from trauma or stroke. Ahn and Anh in [19] have optimized successfully a pseudo-linear ARX model of the PAM manipulator using genetic algorithm These authors in (Anh et al, 2007)[20] have identified the highly nonlinear 2-axes PAM manipulator based on recurrent neural networks. All intrinsic coupling features of the n-DOF manipulator have not represented in its NN model respectively To overcome this disadvantage, in this paper, a new approach of neural networks, proposed dynamic inverse neural MIMO NARX model, firstly utilized in simultaneous modeling and identification of the nonlinear 2-. The experiment results have demonstrated the feasibility and good performance of the proposed intelligent inverse model which overcomes successfully external and internal disturbances such as contact force variations and highly nonlinear coupling effects of both joints of the 2-axes PAM robot arm.
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