Adaptive PID control system for an autonomous underwater vehicle

The control system of an autonomous underwater vehicle （AUV） is introduced. According to control requirements of the AUV, a simple but practical adaptive PID control method is designed The semi-physical simulation is done to test the feasibility of the control system. The neural network idea and the structure of PID controller are referred to design the adaptive PID controller. An intelligent integral is introduced to improve control precision. Compaed with traditional PID con- trollers, the adaptive PID controller has simple structure, good online adjusting ability, fast convergence and good robustness. The simulation experiments also show that the adaptive PID control system has high precision and fine antijamming ability.

Application of Fuzzy-PID Control System in Full-Mechanized Coal Face

The control system, which includes structure, the composition of software and hardware, the form of PID control system and its systematic closed-loop, was used in No.4236 full-mechanized coal face of Xinlongzhuang mine. The typical fuzzy PID control system structure was investigated, and a simplified fuzzy PID control system was taken the place of the complex three-dimension fuzzy controller. Based on the parameter relation between fuzzy controller and normal PID controller, a common method of parameter adjustment of PID controller was summed up and the computer simulation was realized. This system can overcome the problems of large delay, nonlinear, poor running en- vironment and great load change in the full-mechanized coal face. The simulating investigation indicates that the de- signing method of fuzzy controller is simple and feasible.

Optimizing PID controller parameters for robust automatic voltage regulator system through indirect design approach-2

Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.

Adaptive Nonlinear PID Control and Rule-Based Compensation for Systems with Backlash

The control of dynamic nonlinear systems with unknown backlash was considered. By using an efficient approach to estimate the unknown backlash parameters, a rule? based backlash compensator was presented for canceling the effect of backlash. Adaptive nonlinear PID controller together with rule? based backlash compensator was developed and a satisfactory tracking performance was achieved. Simulation results demonstrated the effectiveness of the proposed method.

Experimental Comparison Between PID Control and Friction Compensation Control for a Class of Nonlinear System with Friction

A point to? point positioning control of systems with highly nonlinear frictions is studied. In view of variable frictions caused by the changes of load torque, an experimental comparison was made between the valve? controlled hydraulic motor servo system with PID control and that with friction compensation control. Experimental results show that the gross steady errors are caused by frictions when the system is controlled by the conventional proportional control algorithm. Although the errors can be reduced by introducing the integral control, the limit cycle oscillation and the long setting time are caused. The positioning error for a constant load torque can be eliminated by using fixed friction compensation, but poor positioning accuracy is caused by the same fixed friction compensation when the load torques varies greatly. The dynamic friction compensation based on the error and change in error measurements can significantly improve the position precision in a broad range of the changes of load torque.

基于模糊PID控制的拖拉机遥控转向系统研究

由于拖拉机实际作业环境较为恶劣,为保证驾驶员的安全,提出了一种拖拉机遥控转向系统的设计方案。首先,对拖拉机现有的液压转向系统进行了分析,并提出了遥控转向系统的结构设计和控制策略设计;然后,通过AMEsim和Simulink分别搭建了遥控转向系统的液压部分模型和模糊PID控制器并进行了联合仿真实验。实验结果表明:设计的遥控转向系统能够实现拖拉机的转向,模糊PID控制器相对于常规PID控制器的控制效果更好,阶跃响应时间由1.49 s缩短到1.07 s,正弦跟踪响应最大误差由0.028 m缩短到0.015 m,抗干扰性也更强。

PID Controller Optimization by GA and Its Performances on the Electro-hydraulic Servo Control System

A proportional integral derivative （PID） controller is designed and attached to electro-hydraulic servo actuator system （EHSAS） to control the angular position of the rotary actuator which control the movable surface of space vehicles. The PID gain parameters are optimized by the genetic algorithm （GA）. The controller is verified on the new state-space model of servo-valves attached to the physical rotary actuator by SIMULINK program. The controller and the state-space model are verified experimentally. Simulation and experimental results verify the effectiveness of the PID controller adaptive by GA to control the angular position of the rotary actuator as compared with the classical PID controller and the compensator controller.

Design of PID controller with incomplete derivation based on ant system algorithm

A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.

Nonlinear system PID-type multi-step predictive control

A compound neural network was constructed during the process of identification and multi-step prediction. Under the PID-type long-range predictive cost function, the control signal was calculated based on gradient algorithm. The nonlinear controller’s structure was similar to the conventional PID controller. The parameters of this controller were tuned by using a local recurrent neural network on-line. The controller has a better effect than the conventional PID controller. Simulation study shows the effectiveness and good performance.

PID Control of Planar Nonlinear Uncertain Systems in the Presence of Actuator Saturation

This paper investigates PID control design for a class of planar nonlinear uncertain systems in the presence of actuator saturation.Based on the bounds on the growth rates of the nonlinear uncertain function in the system model,the system is placed in a linear differential inclusion.Each vertex system of the linear differential inclusion is a linear system subject to actuator saturation.By placing the saturated PID control into a convex hull formed by the PID controller and an auxiliary linear feedback law,we establish conditions under which an ellipsoid is contractively invariant and hence is an estimate of the domain of attraction of the equilibrium point of the closed-loop system.The equilibrium point corresponds to the desired set point for the system output.Thus,the location of the equilibrium point and the size of the domain of attraction determine,respectively,the set point that the output can achieve and the range of initial conditions from which this set point can be reached.Based on these conditions,the feasible set points can be determined and the design of the PID control law that stabilizes the nonlinear uncertain system at a feasible set point with a large domain of attraction can then be formulated and solved as a constrained optimization problem with constraints in the form of linear matrix inequalities(LMIs).Application of the proposed design to a magnetic suspension system illustrates the design process and the performance of the resulting PID control law.

Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.

Design and Experimental Evaluation of PID Controller for Digital Electro-Pneumatic Cabin Pressure Control System

The performance of the designed digital electro-pneumatic cabin pressure control system for the cabin pressure schedule of transport aircraft is investigated.For the purpose of this study,an experimental setup consisting of a simulated hermetic cabin and altitude simulation chamber is configured for cabin pressure control system operation.A series of experimental tests are executed to evaluate the performance of the cabin pressure control system.The parameters of the PID controller are optimized.In the optimization process,the variation regularity of the rate of cabin pressure change under various conditions is considered.An approach to prioritize the control of the rate of change of cabin pressure based on the flight status model is proposed and verified experimentally.The experimental results indicate that the proposed approach can be adopted for the designed digital electro-pneumatic cabin pressure control system to obtain a better cabin pressure schedule and rate of cabin pressure change.

Genetic Optimization Algorithm of PID Decoupling Control for VAV Air-Conditioning System

Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multivariable decoupling PID controller is designed for VAV air-conditioning system. Diagonal matrix decoupling method is employed to eliminate the coupling between the loop of supply air temperature and that of thermal-space air temperature. The PID controller parameters are optimized by means of an improved genetic algorithm in floating point representations to obtain better performance. The population in the improved genetic algorithm mutates before crossover, which is helpful for the convergence. Additionally the micro mutation algorithm is proposed and applied to improve the convergence during the later evolution. To search the best parameters, the optimized parameters ranges should be amplified 10 times the initial ideal parameters. The simulation and experiment results show that the decoupling control system is effective and feasible. The method can overcome the strong coupling feature of the system and has shorter governing time and less over-shoot than non-optimization PID control.

Design and Implementation of Digital Fractional Order PID Controller Using Optimal Pole-Zero Approximation Method for Magnetic Levitation System

The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.

Application of PID Controller Based on BP Neural Network in Export Steam’s Temperature Control System

By combining the Back-Propagation （BP） neural network with conventional proportional Integral Derivative （PID） controller, a new temperature control strategy of the export steam in supercritical electric power plant is put forward. This scheme can effectively overcome the large time delay, inertia of the export steam and the influencee of object in varying operational parameters. Thus excellent control quality is obtaitud. The present paper describes the development and application of neural network based controller to control the temperature of the boiler＇s export steam. Through simulation in various situations, it validates that the control quality of this control system is apparently superior to the conventional PID control system.

Tracking Control of Multi-Agent Systems Using a Networked Predictive PID Tracking Scheme

With the rapid development of network technology and control technology,a networked multi-agent control system is a key direction of modern industrial control systems,such as industrial Internet systems.This paper studies the tracking control problem of networked multi-agent systems with communication constraints,where each agent has no information on the dynamics of other agents except their outputs.A networked predictive proportional integral derivative(PPID)tracking scheme is proposed to achieve the desired tracking performance,compensate actively for communication delays,and simplify implementation in a distributed manner.This scheme combines the past,present and predictive information of neighbour agents to form a tracking error signal for each agent,and applies the proportional,integral,and derivative of the agent tracking error signal to control each individual agent.The criteria of the stability and output tracking consensus of multi-agent systems with the networked PPID tracking scheme are derived through detailed analysis on the closed-loop systems.The effectiveness of the networked PPID tracking scheme is illustrated via an example.

Intelligent PID Control Method for Quadrotor UAV with Serial Humanoid Intelligence

Quadrotor unmanned aerial vehicles(UAVs)are widely used in inspection,agriculture,express delivery,and other fields owing to their low cost and high flexibility.However,the current UAV control system has shortcomings such as poor control accuracy and weak anti-interference ability to a certain extent.To address the control problem of a four-rotor UAV,we propose a method to enhance the controller’s accuracy by considering underactuated dynamics,nonlinearities,and external disturbances.A mathematical model is constructed based on the flight principles of the quadrotor UAV.We develop a control algorithm that combines humanoid intelligence with a cascade Proportional-Integral-Derivative(PID)approach.This algorithm incorporates the rate of change of the error into the inputs of the cascade PID controller,uses both the error and its rate of change as characteristic variables of the UAV’s control system,and employs a hyperbolic tangent function to improve the outer-loop control.The result is a double closed-loop intelligent PID(DCLIPID)control algorithm.Through MATLAB numerical simulation tests,it is found that the DCLIPID algorithm reduces the rise time by 0.5 s and the number of oscillations by 2 times compared to the string PID algorithm when a unit step signal is used as input.A UAV flight test was designed for comparison with the serial PID algorithm,and it was found that when the UAV planned the trajectory autonomously,the errors in the X-,Y-,and Z-directions were reduced by 0.22,0.21,and 0.31 m,respectively.Under the interference environment of artificial wind about 3.6 m·s^(-1),the UAV hovering error in X-,Y-,and Z-directions are 0.24,0.42,and 0.27 m,respectively.The simulation and experimental results show that the control method of humanoid intelligence and cascade PID can improve the real-time,control accuracy and anti-interference ability of the UAV,and the method has a certain reference value for the research in the field of UAV control.

Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

Turbine speed control system based on a fuzzy-PID

The flexibility demand of marine nuclear power plant is very high,the multiple parameters of the marine nuclear power plant with the once-through steam generator are strongly coupled,and the normal PID control of the turbine speed can't meet the control demand.This paper introduces a turbine speed Fuzzy-PID controller to coordinately control the steam pressure and thus realize the demand for quick tracking and steady state control over the turbine speed by using the Fuzzy control's quick dynamic response and PID control's steady state performance.The simulation shows the improvement of the response time and steady state performance of the control system.

A PID Tuning Approach for Inertial Systems Performance Optimization

In the practice of control the industrial processes, proportional-integral-derivative controller remains pivotal due to its simple structure and system performance-oriented tuning process. In this paper are presented two approaches for synthesis the proportional-integral-derivative controller to the models of objects with inertia, that offer the procedure of system performance optimization based on maximum stability degree criterion. The proposed algorithms of system performance optimization were elaborated for model of objects with inertia second and third order and offer simple analytical expressions for tuning the PID controller. Validation and verification are conducted through computer simulations using MATLAB, demonstrating successful performance optimization and showcasing the effectiveness PID controllers’ tuning. The proposed approaches contribute insights to the field of control, offering a pathway for optimizing the performance of second and third-order inertial systems through robust controller synthesis.