Conventional PID Control System Research Articles

Attaining Ultraprecision Machining by Feed Drive System Stability Control with Piezoelectric Preloading Actuators

In this paper, a variable preload force control structure utilizing piezoelectric actuators (PEAs) is proposed for the stability control of the feed drive system. Three PEAs are installed between the two nuts to exert preload force on the ball screw, leading to an elimination or substantial reduction of the backlash, which is the main cause of instability of feed drives. This results in better machining precision throughout the operation process. In addition, the force analysis of the whole preload feed drive system is established. Moreover, the hysteresis of the PEAs is determined with reference to the Prandtl–Ishlinskii (P-I) model. Lastly, the P-I model-based feedforward controller is applied to the feed drive system to improve the resultant machining precision. Based on the modeling and experiments, to demonstrate the efficacy and high-performance of the proposed P-I model-based control algorithm against conventional PID control system, comparative experiments are conducted, showing satisfactory results.

Advanced design and tests of a new electrical control seeding system with genetic algorithm fuzzy control strategy

In the existing soybean breeding and planting machinery, the power source of the metering device adopts the ground wheel transmission method mostly. However, this power transmission method is likely to cause slippage during the planting operation, which will cause problems such as the increase of the missed seeding index and the increase of the coefficient of plant spacing. It is not conducive for scientific researchers to carry out breeding operations. Aiming at this problem, an electronically controlled soybean seeding system is designed, and the power of the seed metering device is derived from the motor. In order to improve the control accuracy of the electronically controlled seeding system, the precise control of the soybean seeding rate is finally realized. The electric drive soybean seeding system adopts closed-loop control, the motor model of the electric drive seeding system is established, and the transfer function of the motor is obtained. PID control based on a genetic algorithm is adopted, and the corresponding parameters are substituted into the control system simulation model established in MATLAB/SIMULINK. Field verification tests have been carried out on the conventional fuzzy PID control system and the electric drive soybean planter of the fuzzy PID control system based on a genetic algorithm. The result showed that the average of the repeat-seeding parameter is 1.30% better than the average of conventional seeding system (1.40%), the average of the miss-seeding parameter is 1.08% better than the average of conventional seeding system (2.09%) and the average of row-spacing variation parameter is 2.79% better than the average of conventional seeding system (2.34%). In conclusion, the new seeding system is robust obviously. Field trial results show that seeding with Genetic Algorithm Fuzzy control is better.

Multi-loop Model Reference Adaptive PID Control for Fault-Tolerance

This study demonstrates application of multi-loop model reference adaptive control (MRAC) structure to enhance fault tolerance performance of closed-loop PID control systems. The proposed multi-loop MRAC-PID structure can transform a conventional PID control system to an adaptive control system by combining an outer adaptation loop that employs MIT rule. This control structure can be used to improvement of fault tolerance and fault detection performance of the existing closed-loop PID control systems. One of the advantages of this structure originates from the reference input shaping technique that allows adaptive control without modifying any coefficients of the existing PID controllers. Numerical and experimental studies are presented to illustrate the application of the multi-loop MRAC-PID control structure for rotor control applications.

Active Current Sharing of a Parallel DC-DC Converters System Using Bat Algorithm Optimized Two-DOF PID Control

This paper presents a current sharing method to actively balance the output currents of a parallel dc–dc converters’ (PDCC) system regarding the demanded power. First, the operating principle of the PDCC system with parallel-connected bidirectional converters is studied. To regulate the output voltage in dc bus and share the output currents of the individual converters, a dual-loop control architecture comprising an outer voltage control loop and multiple inner current control loops is designed based on the automatic master–slave control scheme. Moreover, a feedback-type two-degree-of-freedom proportional-integral-derivative (FB2PID) controller is introduced to obtain the pulse-width modulation control signals for the converters. In order to improve the dynamic response and robustness of the active current-sharing control performances of the FB2PID controlled PDCC system, a bat algorithm (BA)-optimized FB2PID control system is further proposed to concurrently and dynamically optimize the control parameters of the FB2PID controller in the current control loop. Thus, the output current of each converter can be controlled to share the demand power equally in the presence of uncertainties. Finally, the simulation and experimental results reveal that the proposed BA-optimized FB2PID control system outperforms the conventional PID and FB2PID control systems with regard to the voltage regulation and current sharing performances under the time-varying electric load condition.

Forward and Inverse Predictive Model for the Trajectory Tracking Control of a Lower Limb Exoskeleton for Gait Rehabilitation: Simulation modelling analysis

The movement of a lower limb exoskeleton requires a reasonably accurate control method to allow for an effective gait therapy session to transpire. Trajectory tracking is a nontrivial means of passive rehabilitation technique to correct the motion of the patients’ impaired limb. This paper proposes an inverse predictive model that is coupled together with the forward kinematics of the exoskeleton to estimate the behaviour of the system. A conventional PID control system is used to converge the required joint angles based on the desired input from the inverse predictive model. It was demonstrated through the present study, that the inverse predictive model is capable of meeting the trajectory demand with acceptable error tolerance. The findings further suggest the ability of the predictive model of the exoskeleton to predict a correct joint angle command to the system.

PENGENDALIAN KECEPATAN MOTOR BRUSHLESS DC (BLDC) MENGGUNAKAN METODE LOGIKA FUZZY

BLDC motors were operated in many industrial environments, especially flammable industry. Besides, it possessed higher efficiency than induction motors, and smaller dimensions than a conventional direct current motors. Moreover, the absence of brush allowed its treatment became easy and showed almost no noise.Fuzzy logic was used as one of the motor speed controlling methods. The design of fuzzy controllers was done by simulating the output speed based on fuzzy controlling reference in order to obtain optimal control results. Several types of defuzzification used were COA / centroid, bisector, MOM, LOM, and SOM. Transient and calculation methods were used to analyze the ISE design optimization of control. The result showed that defuzzification method was able to follow the speed setting that was provided by COA method.The testing on changes of the speed setting from 1000 rpm to 2000 rpm showed the response characteristics of conventional PID control system with an average value of the rise time (tr) 0.29 second, steady time (ts) 0.9 second, overshoot 8.63%, and the percentage of ISE 98.19%. While results generated on fuzzy control system were average value of rise time (tr) 0.25 second, steady time (ts) 0.27 second, overshoot 0.15% and the percentage of ISE 99.36%. The fuzzy control system which was implemented to set the BLDC motor could improve the performance of conventional PID.

BFA optimization for voltage and frequency control of a stand-alone wind generation unit

A developed control strategy for autonomous wind generation unit is presented. Optimization techniques based on bacteria foraging algorithm and genetic algorithms are used to tune the proposed control parameters. The proposed system mainly consists of induction generator driven by wind turbine, synchronous machine, consumer load, discrete dump load, and gate turn-off thyristor-based power electronics converter. Two control loops are used in this study; the first is to regulate the load bus voltage based on the excitation control of the synchronous machine. The second one simultaneously controls the dump load to absorb excessive power generation, and in turn, regulates the frequency of the proposed power system. The proposed system is tested for turbulent change in wind speed and step change in consumer load. The complete system is modeled and simulated using MATLAB/SIMULINK software package. The performance of the optimized control system is compared with the conventional PID control system. The simulation results show that the optimized control system has good performance as less settling time and less overshoot compared with the case of conventional PID controller.

Flight Evaluation of Fault-tolerant Control System Using Simple Adaptive Control Method

A flight controller based on Simple Adaptive Control (SAC) method was implemented to multipurpose experimental aircraft MuPAL-α developed by JAXA (Japan Aerospace Exploration Agency) to demonstrate the effectiveness of SAC flight controller in the serious fault case where the longitudinal stability was suddenly reduced in the air. A parallel feed-forward compensator was added to make the whole system meet the ASPR (Almost Strictly Positive Real) condition that is necessary for the plant to be stabilized by the SAC controller. In order to represent the fault case in a real flight test, a “pseudo-fault term” was added to the original controller equipped with MuPAL-α. Through numerical simulations, hardware in the loop tests and flight experiments, it was revealed that the SAC could stabilize the aircraft with such a fatal fault while a conventional PID control system could not stabilize the plane.

Smart Control of DC Servo Motor Based on Fussy-PID

Conventional PID control system of Direct Current (DC) servo motor is only suitable for the system which Mathematical models can be precisely expressed [1] And it can’t meet the demand of the nonlinear and time-varying system. In the paper, a control system based on fussy-PID is proposed. The basic algorithm of the fussy-PID is introduced firstly. And then the design of the fussy-PID control system is introduced. The results of the experiments have shown that the fussy-PID control system improved the performance of the DC servo motor..

Fire Water Supply Control System of Petrochemical Enterprises

The petroleum chemical industry in the production process, fire water supply control system can not meet the normal transmission of signal nonlinear, reliability is low. Compared with the conventional fuzzy PID control system of PID water supply system, can be effective for the nonlinear input signal, and faster than the reaction rate of PID control, the more reliable. Application of fuzzy control to the fire water supply system of conventional, enhanced fire system speediness, stability and reliability.

Design of BLDCM Control System with Fuzzy Adaptive Controller

To handle the shortages of conventional PID control, recur to the high-performance digital signal processor, combine the fuzzy self-adaption controller with brushless dc motor control system. The results show the control system structure is simplified and the performances of control system are improved comparing to the conventional PID control, the performance index is better than that in conventional PID control system, so the stability of brushless dc motor operation is strengthened.

Design and Simulation of Fuzzy-PID DC Governor System Based on Mine Hoist

According to the requirement of smooth operation and accurate positioning for DC speed regulating system of mine hoist, a new speed control system that based on double closed-loop of Fuzzy-PID was designed. The best control scheme for mine hoist was also validated by simulation comparison with conventional PID control system in the MATLAB/Simulink. The result showed that the proposal was feasible and had practical value.

Two Degree of Freedom Model Driven PID Control for Unstable Process with Time Delays

PID control systems are the most commonly used control technology in industries. However, there are issues on control performances for the unstable process with time delays. In order to improve the control performances of PID control systems, a new two degree of freedom model driven PID control system is introduced in this paper and it is used to the unstable processes with time delay. The model driven PID control is capable of stabilizing with unstable processes by using PD feedback, regulating quickly for disturbance and tracking quickly to the change of set point. With case studies comparing with conventional PID control systems was done.

Design and Simulation of Fuzzy-PID Vector Control System Based on Mine Hoist

According to the requirement of smooth operation and accurate positioning for AC speed regulating system of mine hoist, a new control system that based on vector control of Fuzzy-PID was designed. The best control scheme for mine hoist was obtained, which was also validated by simulation comparison with conventional PID control system in the MATLAB/Simulink. The result showed that the proposal was feasible and had practical value.

Study on Fuzzy Self-Adaptive PID Control System of Biomass Boiler Drum Water

The paper discusses the features of the Biomass Boiler drum water level. Conventional PID Control System can not reach a satisfaction result in nonlinearity and time different from Biomass Boiler Drum Water Control System. In this study, a kind of fuzzy self-adaptive PID controller is described and this controller is used in biomass boiler’s drum water level control system. Using the simulink tool of MATLAB simulation software to simulate the fuzzy adaptive PID and conventional PID control system, the result of the comparison shows that the fuzzy self-adaptive PID has the strong anti-jamming, flexibility and adaptability as well as the higher control precision in Biomass Boiler Drum Water.

Description and Test of the HFFT Resonant Frequency’s Dynamic Characteristics

In this paper, the running stability, the resonant frequency seeking ability of the novel HFFT (High frequency fatigue tester) control system are introduced. Firstly the HFFT control system model is developed. Secondly the HFFT control system dynamic characteristics is simulated and tested, which includes the dynamic load control loop and the frequency locked loop. Finally a experimental result is shown. Compare to the conventional PID control system, the novel tester’s dynamic characteristics are more preferable.

Direct Feedback Linearization Based Control in Variable Air Volume air-conditioning System

In this paper a state space model of VAV air-conditioning system is developed. It is found that the dynamic model is formulated as nonlinear system. To obtain good control performance, a novel control method, direct feedback linear (DFL) is applied for the nonlinear model of VAV air-conditioning system. Then DFL control system of VAV system is designed and simulated based on SIMLINK. In order to show that the DFL control strategy has better performance than conventional PID control, a comparison has also been made between the performance of conventional PID and the novel control strategy. The results show that DFL control system is better than conventional PID control system in celerity, stability and other aspects.

The application of immune genetic algorithm in main steam temperature of PID control of BP network

In order to overcome the uncertainties, large delay, large inertia and nonlinear property of the main steam temperature controlled object in the power plant, a neural network intelligent PID control system based on immune genetic algorithm and BP neural network is designed. Using the immune genetic algorithm global search optimization ability and good convergence, optimize the weights of the neural network, meanwhile adjusting PID parameters using BP network. The simulation result shows that the system is superior to conventional PID control system in the control of quality and robustness.

냉각 프로세서의 모델규명 및 선행미분형 2 자유도 PID 유량 제어 알고리즘에 관한 연구

This study focuses on model identification and a 2-DOF PID control algorithm for cooling processes; a pneumatic butterfly-type control valve is used for this purpose. The mathematical model is a transfer function composed of a time delay and a second-order delay system. The control valve is identified as a first-order delay system with a time delay and included in the controlled plant. From the experimental data sets for a demo plant, the model parameters are identified, and the 2-DOF PID control gains are analytically derived by Kitamori's method. We show via a computer simulation and an experimental test that the performance of the proposed 2-DOF PID control system is better than that of a conventional 1-DOF PID control system.

Design of Compound Fuzzy Controller for Multivariable Systems

The PID controllers can be seen in lots of fields, but some complex control system cannot be controlled to achieve a desired performance index. A design method of the fuzzy PID controller that is based on the fuzzy tuning rules and formed by integrating two above control ideas is proposed in this paper. The design procedure about fuzzy PID control can be divided two steps: the first step is to build the fuzzy tuning rules by analysis, and to obtain the parameters of PID controller by reasoning, and then the control action can be determined by the PID control law. The simulation results and the practical control effects show that the compound fuzzy PID controller has better performance than that of the conventional PID control system and meet the practical demands.