通过李亚普诺夫稳定理论证明跟踪误差是指数收敛的，仿真结果验证了这种方法的有效性。
It is showed by the Lyapunov stability theorem that the tracking errors converge exponentially. The simulation results illustrate the efficiency of this method.
提出一种基于参考误差的投影算法来训练网络权值，训练后网络输出能逼近期望的前馈力矩，并从理论上证明跟踪误差的收敛性。
The neural network trained by projection algorithm with the reference error is used to approximate the desired feedforward compensation. Convergence of the tracking error is proved.
在一个软件开发测试环境中，跟踪机器被证明是非常困难的，尤其是当机器的数量达到两位数的时候。
In a software development test environment, keeping track of your machines can prove very difficult, particularly when the number of machines reaches the double figures.
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