The merit of inner loop of electro-optical tracking (EOT) servo system which consists of the current loop and the velocity loop direct determines the performance of EOT system. For improving the performance of EOT system with large inertia load and nonlinear friction, it is necessary to establish the mathematics model of inner loop in frequency domain and tune the parameters of the regulator to regulate the inner loop as desired model. An algorithm based on MATLAB plot the BODE diagraph of system with input/output data of system is proposed in this paper. The modeling approach that plots the asymptote for BODE diagraph and establishes the mathematics model in frequency domain is introduced. It can avoid the nonlinear friction and depict the main characteristic of system. On the basis of the mainly mathematics model in frequency domain, a novel method to tune the parameters of the regulator is presented. The principle of method is to set up the desired model and establish the equation to solve the parameters of regulator based on the consistency of frequency response. The experiment result shows that the modeling approach has some practicability and the regulator with parameters tuned by the novel method can improve the performance of the inner loop.

This paper presents a novel simple, but efficient robot path planning algorithm, which plans the obstacleavoidance path according to map information, makes robots reach the target. In the paper, the actual environment is discretized into a topologically organized map consisting of targets, obstacles and free spaces. We quantify the road roughness, which affects the motion of robots to the degree of pass convenience with a special mathematical model, and introduced into the model for path planning. Targets propagate the socalled "vector-distance" to whole workspace through free-space grid points in a special direction. Because the distance propagating in this way has direction and size, it is called "vector-distance", which is constrained by the motion of nonholonomic mobile robot. So the path obtained by this algorithm is the optimal path suitable to the motion of nonholonomic mobile robot. This model is characterized by high computational efficiency, small storage cost and perfectly simulating the actual map. This algorithm can be conveniently used in practice.

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