The artificial potential field method has been extensively used in mobile robot path planning for its characteristics of simpleness, high efficiency, and smooth path. In this paper, to solve the problem of local minima in traditional artificial potential field method, A modified form of repulsion function is proposed. A detour force is added to the repulsion function, the problem of local minima can be solved effectively. In the end, with the help of Matlab software simulating, the result shows that this method is simple and effective.

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The purpose of this paper is to suggest and examine a control system with a fuzzy controller and a fuzzy-PID controller to solve the problem of mobile robot path planning. The environment information about obstacles and the goal has been detected by using sensors. The system divides environment situations into two types the obstacle mode and non-obstacle mode. In view of the oscillation problem existing in fuzzy control when there is no obstacle, this paper proposes that the fuzzy control is used for the obstacle mode and the fuzzy adaptive PID control is used for the non-obstacle mode. The robot performs the real-time planning choice by path planning selector, and the control system is simulated by Matlab software. The simulation result shows that the control strategy has the characteristics of faster response, better real-time performance and achieves a better path from the start point to the target point.

In the complex heating systems, higher order, large inertia, large delay and uncertainty typically exist. This work introduces generalized predictive PID control algorithm to adjust the system. The purpose of the control algorithm is to achieve a steady state in a shorter time. On the basis of analyzing PID control algorithm and Generalized Predictive Control (GPC), configuring a given performance function index control-weighted sequences to GPC control. Derived form of generalized predictive control algorithm with PID. The Matlab simulation shows that using generalized predictive PID control algorithm can produce better results in shorter time than simple using PID or GPC in the heating system.