scholarly journals PID Algorithm and Fuzzy Control Algorithm in Step-less Speed Adjusting System Control with PLC

2012 ◽  
Author(s):  
Yaolin Zhao ◽  
Dapeng Xing
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
System Control ◽  
Pid Algorithm ◽  
Fuzzy Control Algorithm

Development of Dedicated Controller for HVAC

2012 ◽  
Vol 430-432 ◽  
pp. 1472-1476
Author(s):  
Jin Ming Yang ◽  
Yi Lin
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Strategies ◽  
Control Software ◽  
Interface Circuits ◽  
Pid Algorithm ◽  
Hardware Interface ◽  
Hvac Control ◽  
Fuzzy Control Algorithm

This article describes the development of a dedicated controller for HVAC control, and introduces the hardware interface circuits about some main chip on controller. In addition, the article also explains composition and principle about control software applied to the controller, further more points out that the fuzzy control algorithm is more reasonable than the PID algorithm for most HVAC control and dedicated control strategies play an important role for HVAC control.

PID Parameter Setting Based on Fuzzy Control Algorithm and its Application in the Temperature Control System of Airplane

2012 ◽  
Vol 588-589 ◽  
pp. 1503-1506
Author(s):  
Fang Ding ◽  
Tao Ma
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Control Method ◽  
Fuzzy Controller ◽  
Temperature Control System ◽  
System Control ◽  
Control Effect ◽  
Fuzzy Control Algorithm

This Temperature control system of aircraft cabin is a complex system with nonlinear, time-varying, model inaccurate and work environment uncertain. According to the system control requirements, the fuzzy controller with the characteristic of fast response speed, good stability and strong resistance to interference is used in the study. The system error is adjusted constantly by using fuzzy control algorithm and simulation study is conducted in the software Matlab. The results are showed that control effect of control method used in this study is better than the traditional PID control method, and dynamic performance, steady state accuracy and robustness of system is effectively improved.

The Research on Vehicle Anti-Braking System Control Algorithm Based on Immune PID Control

2012 ◽  
Vol 580 ◽  
pp. 189-193
Author(s):  
Ke Rong Jiang ◽  
Bo Lin Dong
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Dynamic Mode ◽  
System Control ◽  
Stabilization Time ◽  
Braking System ◽  
Braking Distance ◽  
System Output ◽  
Fuzzy Control Algorithm

Because the classic PID control doesn’t satisfy the demand of automobile ABS in all conditions and it is short of an ability of identifying road surface, fuzzy control is short of an ability of remove systemic stable error and it doesn’t make automobiles keep higher control precisions. a dynamic mode of the wheels is built when an automobile is braking at first, aiming at automobile ABS, a immune PID control algorithm based on classic PID is presented and used in automobile ABS system. Compared with the classic PID control algorithm and fuzzy control algorithm, the simulation result shows that the immune PID control algorithm has a shorter stabilization time, a smaller excess of system output, fewer response time and shorter braking distance, it is superior to the classic PID control algorithm and fuzzy control algorithm. The immune PID control algorithm has a higher application value.

Space robot motion path planning based on fuzzy control algorithm

2021 ◽  
pp. 1-8
Author(s):  
Baoyu Shi ◽  
Hongtao Wu
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Space Robot ◽  
Robot Motion ◽  
Robot Path Planning ◽  
Behavior Based ◽  
Fuzzy Control Algorithm ◽  
Robot Path

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

Profile Measurement of a Curved Workpiece by the Fuzzy Control of Sensor Positioning

1999 ◽  
Author(s):  
Masatake Shiraishi ◽  
Gongjun Yang
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Experimental Results ◽  
Measuring System ◽  
Displacement Sensor ◽  
Profile Measurement ◽  
Laser Displacement Sensor ◽  
Inclination Angles ◽  
Fuzzy Control Algorithm ◽  
Sensor Positioning

Abstract A laser displacement sensor which has a resolution of 0.5 μm was used to determine the measurement of a curved workpiece profile in turning. This sensor is attached to a specially designed stage and is operated by three motors which are controlled by a fuzzy control algorithm. The experimental results show that the measuring system can be applied to workpieces having inclination angles of up to around 45°. The proposed measuring system has a practical measuring accuracy to within ten micrometers.

scholarly journals Fault Location Measurement of Sensor Nodes based on Fuzzy Control Algorithm

2021 ◽  
Author(s):  
Nuo Yu
Keyword(s):  
Fuzzy Control ◽  
Measurement Method ◽  
Control Algorithm ◽  
Fault Location ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Cluster Member ◽  
Cluster Heads ◽  
Fuzzy Control Algorithm ◽  
Location Measurement

Abstract Aiming at the problems of the traditional fault location measurement method for sensor nodes, such as more energy consumption and longer measurement time, a fault location measurement method for sensor nodes based on fuzzy control algorithm is designed and proposed. First of all, the fuzzy control algorithm is analyzed; then the clustering based on cluster head diagnosis is carried out for the network, that is, the nodes that meet the cluster head conditions and are set as normal cluster heads are selected as cluster heads. Finally, combined with the fuzzy control algorithm, the fault location of each cluster member node is measured directly by cluster head nodes. The simulation results show that the proposed method has good performance.

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