Intelligent Temperature Control System Design Based on Single-Chip Microcomputer

A design method of an intelligent temperature control system based on single-chip microcomputer is presented in this paper. The intelligent temperature control system is divided into four parts: monitor,heater,controlled process and feedback loop. Among them,the temperature detection circuit is designed with the conductivity of water by sensor detection. The optical coupler MOC3041 is used to implement the power control circuit,whose control object is 1 kW electric heater with the 220 V alternating current power; keyboard and display circuit SMC1602A include four buttons and LCD display to achieve human-computer interaction; Based on single-chip system STC89C52,the sensor signal and keyboard set target temperature are compared to the power automatically in order to finish the water temperature control. Through the static and dynamic data testing,the results show that the proposed method provides an effective way to realize the real-time acquisition and control of temperature.

Research of Multiagent Coordination and Cooperation Algorithm

To solve the problem of conflict and deadlock with agents in multiagent system,an algorithm of multiagent coordination and cooperation was proposed. Taking agent in multiagent system as a player,the pursuit problem Markov model was built. The solution was introduced to get the optimal Nash equilibrium by multiagent reinforcement learning. The method of probability and statistics and Bayes formula was used to estimate the policy knowledge of other players. Relative mean deviation method was used to evaluate the confidence degree in order to increase the convergence speed. The simulation results on pursuit problem showed the feasibility and validity of the given algorithm.

Research on Multi-robot Coordination Searching Ignition Sources Approach

For the purpose of study on forecasting forest fire behavior,a probability approach was presented to search ignition sources by multi-robot coordination. Firstly,the environment map is built based on Bayes rules. Then,the probability searching strategy based on the environment map was designed. Every grid of the searching area was assigned searching expectation value, and robots selected the grid with the highest expectation value as its searching target. The simulation results show the search time reduces greatly,which proves the feasibility and validity of the given algorithm under unknown fire condition.

Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography

Analysis of forest canopy hemisphere images is one of the most important methods for measuring forest canopy structure parameters. In this study, our main focus was on using circular image region segmentation, which is the basis of forest canopy hemispherical photography. The boundary of a forest canopy hemisphere image was analyzed via histogram, rectangle, and Fourier descriptors. The image boundary characteristics were defined and obtained based on the following：（1） an edge model that contains three parts, i.e., step, ramp, and roof;（2） boundary points of discontinuity;（3） an edge that has a linear distribution of scattering points. On this basis, we proposed a segmentation method for the circular region in a forest canopy hemisphere image, fitting the circular boundary and computing the center and radius by the least squares method. The method was unrelated to the parameters of the image acquisition device. Hence, this study lays a foundation for automatically adjusting the parameters of high-performance image acquisition devices used in forest canopy hemispherical photography.