scholarly journals Motion Control and Implementation for an AC Servomotor System

2007 ◽  
Vol 2007 ◽  
pp. 1-6 ◽  
Author(s):  
L. Canan Dülger ◽  
Ali Kireçci
Keyword(s):  
Mathematical Model ◽  
Dynamic Behavior ◽  
Motion Control ◽  
Trajectory Tracking ◽  
Pid Controller ◽  
Experimental Validation ◽  
Experimental Setup ◽  
Tracking Problem ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller

This paper presents a study on trajectory tracking problem for an AC synchronous servomotor. A mathematical model for the system including AC synchronous servomotor, gearbox, and a load is developed to examine the systems dynamic behavior. The system is controlled by a traditional PID (proportional + integral + derivative) controller. The required values for the controller settings are found experimentally. Different motion profiles are designed, and trapezoidal ones are implemented. Thus, the experimental validation of the model is achieved using the experimental setup. The simulation and experimental results are presented. The tracking performance of an AC servomotor system is illustrated with proposed PID controller.

A Multi-Resolution PID Controller Based on the Wavelet Transform

2012 ◽  
Vol 472-475 ◽  
pp. 632-636 ◽  
Author(s):  
Cun Zhi Yao ◽  
Gui Xiang Zhang
Keyword(s):  
Control System ◽  
Wavelet Transform ◽  
Pid Controller ◽  
Control Design ◽  
Cumulative Effect ◽  
Measurement Noise ◽  
Time Varying ◽  
Error Signal ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller

The non-linear and time-varying natures of the process together with the large disturbances of several types are the key challenge for the control design. A controller based on multi- resolution decomposition using wavelets is presented in the paper. The wavelet is used to decompose the error signal into signals at different scales.These signals are then used to compensate for the uncertainties in the plant.The controller is similar to proportional integral derivative controller in principle and application. the output from this control system represents the cumulative effect of uncertainties such as measurement noise, frictional variations and external torque disturbances which manifest at different scales. This controller better solves the nonlinear and time-varying togetther with the great disturbance.

Active Force Control Applied to Spray Boom Structure

2013 ◽  
Vol 315 ◽  
pp. 616-620 ◽  
Author(s):  
Mona Tahmasebi ◽  
Roslan Abdul Rahman ◽  
Musa Mailah ◽  
Mohammad Gohari
Keyword(s):  
Pid Control ◽  
Force Control ◽  
High Frequency ◽  
Pid Controller ◽  
Active Force ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Active Force Control ◽  
Simulation Results ◽  
Vertical Vibrations

Distribution pattern of spray boom in fields is affected by several parameters which one of the important reasons is horizontal and vertical vibrations because of unevenness surfaces. Spray boom movements lead to decrease of spread efficiency and crop yield. Generally, active suspension is employed to control and attenuate the vibration of sprayer booms because these suspensions reduce the high frequency vibration of spray booms thanks to irregularities soil. In this research, a proportional-integral-derivative controller with active force control is used to remove undesired rolling of spray boom. Simulation results depict that the proposed scheme is more effective and accurate than PID control only scheme. The AFC based scheme shows the robustness and accuracy compared to the PID controller.

Study and Realization of a Prototype Octocopter System with PID Controller

2018 ◽  
Vol 10 (4) ◽  
Author(s):  
Saidi Hemza ◽  
Djebri Boualem
Keyword(s):  
Dynamic Model ◽  
Pid Controller ◽  
External Environment ◽  
Lagrangian Model ◽  
System Dynamic Model ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Euler Model ◽  
Electrical Components

In this work, the mechanical and electrical components are designed and realised for an octocopter. The designed system dynamic model is supported with Euler-Lagrangian model and Newton-Euler model respectively for the rotational and transnational movements of the drone. The prototype octocopter is also equipped with a proportional integral derivative controller to feedback both location and respond to the external environment.

Fractional order based trajectory tracking control of an ankle rehabilitation robot

2016 ◽  
Vol 40 (2) ◽  
pp. 550-564 ◽  
Author(s):  
Mustafa Sinasi Ayas ◽  
Ismail Hakki Altas ◽  
Erdinc Sahin
Keyword(s):  
Fractional Order ◽  
Trajectory Tracking ◽  
Human Robot Interaction ◽  
Rehabilitation Robot ◽  
Proportional Integral Derivative ◽  
External Disturbances ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Rehabilitation Robots ◽  
Ankle Rehabilitation

Human–robot interaction is inherently available and used actively in ankle rehabilitation robots. This interaction causes disturbances to be counteracted on the rehabilitation robots in order to reduce the side effects. This paper presents a fractional order proportional–integral–derivative controller to improve the trajectory tracking ability of a developed 2-degree of freedom parallel ankle rehabilitation robot subject to external disturbances. The parameters of the controller are optimally tuned by using both the cuckoo search algorithm and the particle swarm optimization algorithm. A traditional proportional–integral–derivative controller, which is also tuned using both of the algorithms, is designed to test the performance of the fractional order proportional–integral–derivative controller. The experimental results show that the optimally tuned FOPID controller improves the tracking performance of the ankle rehabilitation robot subject to external disturbances significantly and decreases the steady-state tracking errors compared to the optimally tuned PID controller.

An application of Newton-like algorithm for H∞ proportional–integral–derivative controller synthesis of seesaw-cart system

2021 ◽  
pp. 014233122110638
Author(s):  
Vladimir Milic ◽  
Srecko Arandia-Kresic ◽  
Mihael Lobrovic
Keyword(s):  
Pid Controller ◽  
Optimality Criterion ◽  
Controller Synthesis ◽  
Laboratory Model ◽  
Linear Matrix ◽  
Proportional Integral Derivative ◽  
Backpropagation Algorithm ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Standard Linear

This paper is concerned with the synthesis of proportional–integral–derivative (PID) controller according to the [Formula: see text] optimality criterion for seesaw-cart system. The equations of dynamics are obtained through modelling a seesaw-cart system actuated by direct-current motor via rack and pinion mechanism using the Euler–Lagrange approach. The obtained model is linearised and synthesis of the PID controller for linear model is performed. An algorithm based on the sub-gradient method, the Newton method, the self-adapting backpropagation algorithm and the Adams method is proposed to calculate the PID controller gains. The proposed control strategy is tested and compared with standard linear matrix inequality (LMI)-based method on computer simulations and experimentally on a laboratory model.

High order differential feedback controller design and implementation for a Stewart platform

2019 ◽  
Vol 26 (11-12) ◽  
pp. 976-988 ◽  
Author(s):  
Mustafa S Ayas ◽  
Erdinc Sahin ◽  
Ismail H Altas
Keyword(s):  
Trajectory Tracking ◽  
Absolute Error ◽  
Parallel Manipulators ◽  
Stewart Platform ◽  
High Order ◽  
Feedback Controller ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Reference Trajectories

Stewart platform or other parallel manipulators with a Stewart structure are commonly used in flight simulators, surgical operations, medical rehabilitation processes, machine tools, industrial applications, etc. Therefore, researchers have paid attention to position control of these manipulators in addition to their design and development process. In this study, a developed Stewart platform and its inverse kinematic analysis are presented first. Then, a model-free control scheme called a high order differential feedback controller scheme is designed for the Stewart platform in order to improve its trajectory tracking performance and robustness against to different reference trajectories. Real-time trajectory tracking experiments with varied reference trajectories are carried out to show the robustness and effectiveness of the high order differential feedback controller scheme compared to the traditional proportional–integral–derivative controller of which the parameters are optimally tuned. The obtained visual trajectory tracking results and numerical performance results based on error-based performance measurement metrics such as integral of absolute error, integral of squared error, and integral of time-weighted absolute error are provided for both the proposed high order differential feedback controller scheme and the optimal tuned proportional–integral–derivative controller. Experimental results show that the proposed high order differential feedback controller scheme is more robust than the proportional–integral–derivative controller. Furthermore, the high order differential feedback controller scheme has superiority in both transient and steady-state responses and even the parameters of the proportional–integral–derivative controller are optimally tuned.

scholarly journals Optimally Tuned PID Controller of A DC Motor System using Bacterial Foraging Algorithm

2018 ◽  
Vol 8 (02) ◽  
Author(s):  
Rashid Alzuabi
Keyword(s):  
Pid Controller ◽  
Motor System ◽  
Dc Motor ◽  
System Response ◽  
Proportional Integral Derivative ◽  
Close Loop System ◽  
System Description ◽  
Proportional Integral Derivative Controller ◽  
Bacterial Foraging ◽  
Bacterial Foraging Algorithm

This paper presents an exercise in applying the bacterial foraging algorithm (BFA) optimisation method on a proportional—integral-derivative controller (PID) of a DC motor circuit. The paper presents the system description of the DC motor transfer function and the simulation of the close loop system using MATLAB. The BFA algorithm is described and discussed with the simulation results presented to illustrate the enhancement of the system response that in result enhances the operation of the DC motor system.

scholarly journals Optimized LQR-PID Controller Using Squirrel Search Algorithm for Trajectory Tracking of a 6-DoF Parallel Manipulator

2021 ◽  
Author(s):  
Chandan Choubey ◽  
Jyoti Ohri
Keyword(s):  
Trajectory Tracking ◽  
Pid Controller ◽  
Parallel Manipulator ◽  
Search Algorithm ◽  
Linear Quadratic Regulator ◽  
Absolute Error ◽  
Minimal Cost ◽  
Proportional Integral Derivative ◽  
Linear Quadratic ◽  
Mean Velocity

Abstract In 6 Degree of Freedom (DOF) parallel manipulator, trajectory tracking is one of the main challenges. To obtain the desired trajectory, the DC motor needs to generate optimal torque. So to obtain optimal torque, an optimized Linear Quadratic Regulator-Proportional–Integral–Derivative (LQR-PID) controller is presented in this paper. For optimizing the Q, R and gain parameters of LQR-PID controller, Squirrel Search Algorithm (SSA) is presented. In this algorithm, minimal cost function of LQR-PID controller is considered as objective function. The SSA based LQR-PID controller leads the motor to generate optimal torque that helps to attain the desired trajectory of 6-DOF parallel manipulator. Results of the work depicts that the SSA based LQR-PID controller achieves the best mean velocity, sum square error (SSE), integral square error (ISE) and integral absolute error (IAE).

Sign in / Sign up

Export Citation Format

Share Document