碟形水下机器人的运动控制过程是非常复杂的,涉及到很多影响因素,并且是一个非线性控制过程,其姿态控制过程的系统模型的辨识对于实现机器人精确的控制和不同水文环境的自适应预测控制有着重要意义.因支持向量机( SVM)算法经过严格的数学推导,且在非线性等方面的良好表现,提出了将SVM算法用于碟形水下机器人模型的辨识,并设计了一组基于SVM的多输入多输出系统辨识器,可针对控制量进行姿态变化预测.通过在水池中测试的实验数据进行辨识和预测.实验验证预测的均方差不超过0.004,实验结果验证了该算法对碟形潜水器的姿态运动控制系统的辨识与预测有着良好的效果.%The control of dish-like underwater robot motion is complex. It involves many influencing factors and it' s also a nonlinear control process. The model of attitude motion control is very important for the accurate control and self-adaptive predictive control. SVM algorithm is proposed to apply in indentifing the model of dish-like underwater robot and a set of MIMO identifier based on SVM is designed because the SVM has excellent performance on nonlinear system by strict mathematical derivation. This identifier can predict the attitude change according to control parameters. The identification and prediction performance of the SVM identifier is proved by the experimental data of pool test. The result shows that the MSE is less than 0.004. It verifies that this algorithm has good effect on the identification and prediction of dish-like underwater robot attitude motion control system.
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