Fuzzy adaptive PID control on hydraulic servo system of quadruped robot

Quadruped robot driven by high power density hydraulic device works in unstructured en- vironment. With variable load and various external disturbance, the hydraulic servo system has fea- tures such as nonlinear, time-varying parameters. Traditional control method has some limitation. In order to help the hydraulic servo system of the quadruped robot to adapt to harsh environments, and to obtain high control quality and control precision, an incremental fuzzy adaptive PID controller based on position feedback is designed to solve the related technical problems. Matlab/Simulink sim- ulation and experimental results show that the incremental fuzzy adaptive PID controller improves the dynamic performance of the system, enhances the respond speed and precision of the hydraulic ser- vo system, and has some theory significance and practical value.

New Asymmetric Fuzzy PID Control for Pneumatic Position Control System

A fuzzy control algorithm of asymmetric fuzzy strategy is introduced for a servo-pneumatic position system. It can effectively solve the difficult problems of single rod low friction cylinders, which are mainly caused by asymmetric structures and different friction characteristics in two directions. On the basis of this algorithm, a traditional PID control is used to improve dynamic performance. Furthermore, a new asymmetric fuzzy PID control with α factor is advanced to improve the self-adaptability and robustness of the system. Both the theoretical analyses and experimental results prove that, with this control strategy, the dynamic performance of the system can be greatly improved. The system using this control algorithm has strong robustness and it obtains desired overshoot and repeatability in both transient and steady-state responses.

Grey Prediction Fuzzy Control of the Target Tracking System in a Robot Weapon

Grey modeling can be used to predict the behavioral development of a system and find out the lead control values of the system. By using fuzzy inference, PID parameters can be adjusted on line by the fuzzy controller with PID parameters self-tuning. According to the characteristics of target tracking system in a robot weapon, grey prediction theory and fuzzy PID control ideas are combined. A grey prediction mathematical model is constructed and a fuzzy PID controller with grey prediction was developed. Simulation result shows fuzzy PID control algorithm with grey prediction is an efficient method that can improve the control equality and robustness of traditional PID control and fuzzy PID control, and has much better performance for target tracking.

Design of Greenhouse Environment Control System Based on Internet of Things

There are some disadvantages, such as complicated wiring, high cost, poor monitoring flexibility, low accuracy and high energy consumption in traditional greenhouse environment monitoring system which based on previous wireless sensor networks （WSN）. Aiming at these problems, a greenhouse environmental parameter monitoring system had been designed based on internet of things technology in this paper. A set of control system with good robustness, strong adaptive ability and small overshoot was set up by combining the fuzzy proportion-integral-derivative （PID） control. The system was composed of a number of independent greenhouse monitoring systems. The server could provide remote monitoring access management services after the collected data were transmitted. The data transmission part of greenhouse was based on ZigBee networking protocol. And the data were sent to intelligent system via gateway connected to the internet. Compared to the classical PID control and fuzzy control, the fuzzy PID control could quickly and accurately adjust the corresponding parameters to the set target. The overshoot was also relatively small. The simulation results showed that the amount of overshoot was reduced 20% compared with classical PID control.

Research on Intelligent Control System of Thermal Print Head Based on Field Programmable Gate Array

Thermal print head heating real-time temperature fluctuations are too large,often causing damage to the print head heating point,resulting in poor print quality and unsatisfactory print results.Therefore,to improve the stability of the thermal print head during printing,and at the same time to solve the inefficiency of the traditional single-chip microcomputer control of the thermal print head heating method,a field programmable gate array-based thermal print head heating control method is proposed.To control the core,the intelligent fuzzy Proportional-Integral-Differential(PID)control algorithm is used to ensure that the temperature of the print head can be stabilized quickly.Through simulation and experimental verification,it is shown that the intelligent fuzzy PID control algorithm greatly improves the temperature stabilization effect,and the time required to reach stability short not only improve the printing accuracy but also extend the life of the print head.

Smith Prediction Monitor AGC System Based on Fuzzy Self-Tuning PID Control

In accordance with the feature of pure delay in monitor AGC system for cold rolling mill, a new fuzzy selftuning PID Smith prediction controller is developed. The position control model is deduced based on a single stand cold rolling mill, and the fuzzy controller for monitor AGC system is designed. The analysis of dynamic performance for traditional PID Smith prediction controller and fuzzy self-tuning PID Smith prediction controller is done by MAT- LAB toolbox. The simulation results show that fuzzy self-tuning PID Smith controller has stronger robustness, faster response and higher static accuracy than traditional PID Smith controller.

A fuzzy PID-controlled SMA actuator for a two-DOF joint

Shape memory alloy （SMA） actuator is a potential advanced component for servo- systems of aerospace vehicles and aircraft. This paper presents a joint with two degrees of freedom （DOF） and a mobility range close to ±60° when driven by SMA triple wires. The fuzzy proportional-integral-derivative （PID）-controlled actuator drive was designed using antagonistic SMA triple wires, and the resistance feedback signal made a closed loop. Experiments showed that, with the driving responding frequency increasing, the overstress became harder to be avoided at the position under the maximum friction force. Furthermore, the hysteresis gap between the heating and cooling paths of the strain-to-resistance curve expanded under this condition. A fuzzy logic control was considered as a solution, and the curves of the wires were then modeled by fitting polynomials so that the measured resistance was used directly to determine the control signal. Accurate control was demonstrated through the step response, and the experimental results showed that under the fuzzy PID-control program, the mean absolute error （MAE） of the rotation angle was about 3.147°. In addition, the investigation of the external interference to the system proved the controllable maximum output.

A Fuzzy PID Algorithm for a Novel Miniature Spherical Robots with Three-dimensional Underwater Motion Control

We proposed and developed a small bionic amphibious spherical robot system for tasks such as coastal environment monitoring and offshore autonomous search and rescue.Our third-generation bionic small amphibious spherical robots have many disadvantages,such as the lack of maneuverability and a small operating range.It is difficult to accomplish underwater autonomous motion control with these robots.Therefore,we proposed a fourth-generation amphibious spherical robot.However,the amphibious spherical robot developed in this project has a small and compact design,with limited sensors and external sensing options.This means that the robot has weak external information collection capabilities.We need to make the real time operation of the robot's underwater motion control system more reliable.In this paper,we mainly used a fuzzy Proportional-Integral-Derivative(PID)control algorithm to design an underwater motion control system for a novel robot.Moreover,we compared PID with fuzzy PID control methods by carrying out experiments on heading and turning bow motions to verify that the fuzzy PID is more robust and exhibits good dynamic performance.We also carried out experiments on the three-dimensional(3D)motion control to validate the design of the underwater motion control system.

Research on Suspension Gravity Compensation System of Lunar Rover with Magnetic Levitation Servo

In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation method of lunar rover based on the combination of active suspension and active position following of magnetic levitation is proposed,and the overall design is carried out.The dynamic model of the suspension module of microgravity compensation system was established,and the decoupling control between the constant force component and the position servo component was analyzed and verified.The constant tension control was achieved by using hybrid force/position control.The position following control was realized by using fuzzy adaptive PID(proportional⁃integral⁃differential)control.The stable suspension control was realized based on the principle of force balance.The simulation results show that the compensation accuracy of constant tension could reach more than 95%,the position deviation was less than 5 mm,the position deviation angle was less than 0.025°,and the air gap recovered stability within 0.1 s.The gravity compensation system has excellent dynamic performance and can meet the requirements of microgravity simulation experiment of lunar rover.

Application of a simplified Grey Wolf optimization technique for adaptive fuzzy PID controller design for frequency regulation of a distributed power generation system

A Simplified Grey Wolf Optimizer(SGWO)is suggested for resolving optimization tasks.The simplification in the original Grey Wolf Optimizer(GWO)method is introduced by ignoring the worst category wolves while giving priority to the better wolves during the search process.The advantage of the presented SGWO over GWO is a better solution taking less execution time and is demonstrated by taking unimodal,multimodal,and fixed dimension test functions.The results are also contrasted to the Gravitational Search Algorithm,the Particle Swarm Optimization,and the Sine Cosine Algorithm and this shows the superiority of the proposed SGWO technique.Practical application in a Distributed Power Generation System(DPGS)with energy storage is then considered by designing an Adaptive Fuzzy PID(AFPID)controller using the suggested SGWO method for frequency control.The DPGS contains renewable generation such as photovoltaic,wind,and storage elements such as battery and flywheel,in addition to plug-in electric vehicles.It is demonstrated that the SGWO method is superior to the GWO method in the optimal controller design task.It is also seen that SGWO based AFPID controller is highly efficacious in regulating the frequency compared to the standard PID controller.A sensitivity study is also performed to examine the impact of the unpredictability in the parameters of the investigated system on system performance.Finally,the novelty of the paper is demonstrated by comparing with the existing publications in an extensively used two-area test system.

Suspending Control Scheme of 8/10 Bearingless SRM Based on Adaptive Fuzzy PID Controller

As a nonlinear,strong coupling and multi-variable system,the drive performance of bearingless switched reluctance motor(BLSRM)is always limited by its complicated electromagnetic properties.Generally,conventional PID methods are used to achieve the basic control requirement in wide industrial applications,however its inherent operating principle limits its use on suspending control of BLSRM.In this paper,the suspending force system,which is separately controlled from torque system,is built based on an adaptive fuzzy PID controller to limit the rotor eccentric displacement with proper generation of radial force.When compared with a system adopted using conventional PID method for suspending force control,the proposed adaptive fuzzy PID method has superior performance in shortening the response time,reducing the maximum eccentric displacement error and higher speed range of operation due to its online self-turning of controller parameters.Both in simulation and experimental cases,comparison of results of the above two methods validates the effectiveness of the adaptive fuzzy PID controller for BLSRM drive system.

Research on stabilizing and tracking control system of tracking and sighting pod

With the coupling among three-axis platform frames of tracking and sighting pod taken into considera- tion, the kinetic equations are set up according to the kinetic characteristic. Moreover, by predigesting the equations, the math model suitable for controller design is gained. An H-infinity controller combining with Kalman filter is designed for stabilizing loop of tracking and sighting pod platform frames. Fuzzy PID controllers corresponding to each tracking loop of three-axis frames are designed. The control system designed in this study, in which the effects of the coupling among frames and parameters variation are taken into consideration, is closer to practical situation. The control system is dynam- ically simulated under the condition of multidisturbance. The simulation results show that the entire stabilization tracking control system has good robustness and high tracking precision, which fulfils the need of stabilizing and tracking control of trackin~ and si^htin~ pod.