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.

Design of an integer order proportional–integral/proportional–integral–derivative controller based on model parameters of a certain class of fractional order systems

2018 ◽  
Vol 233 (3) ◽  
pp. 320-334 ◽  
Author(s):  
Erhan Yumuk ◽  
Müjde Güzelkaya ◽  
İbrahim Eksin
Keyword(s):  
Fractional Order ◽  
Design Parameter ◽  
Design Methodology ◽  
Model Parameters ◽  
Proportional Integral Derivative ◽  
Level Control ◽  
Proportional Integral Derivative Controller ◽  
Integer Order ◽  
Proportional Integral ◽  
Order Pole

In this study, we deal with systems that can be represented by single fractional order pole models and propose an integer order proportional–integral/proportional–integral–derivative controller design methodology for this class. The basic principle or backbone of the design methodology of the proposed controller relies on using the inverse of the fractional model and then approximating this fractional controller transfer function by a low integer order model using Oustaloup filter. The emerging integer order controller reveals itself either in pre-filtered proportional–integral or proportional–integral–derivative form by emphasizing on the dominancy concept of pole-zero configuration. Parameters of the proposed controllers depend on the parameters of the single fractional order pole model and the only free design parameter left is the overall controller gain. This free design parameter is determined via some approximating functions relying on an optimization procedure. Simulation results show that the proposed controller exhibits either satisfactory or better results with respect to some performance indices and time domain criteria when they are compared to classical integer order proportional–integral–derivative and fractional order proportional–integral–derivative controllers. Moreover, the proposed controller is applied to real-time liquid level control system. The application results show that the proposed controller outperforms the other controllers.

scholarly journals Hybrid control technique for minimizing the torque ripple of brushless direct current motor

2018 ◽  
Vol 51 (7-8) ◽  
pp. 321-335 ◽  
Author(s):  
K Prathibanandhi ◽  
R Ramesh
Keyword(s):  
Fractional Order ◽  
Direct Current ◽  
Hybrid Technique ◽  
Proportional Integral Derivative ◽  
Inference System ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Direct Current Motor ◽  
Torque Ripples ◽  
Brushless Direct Current Motor

This paper presented the brushless direct current motor torque ripple reduction based on the speed and torque control using hybrid technique. The dynamic behavior of the brushless direct current motor is analyzed in terms of the parameters such as the speed, current, back electromotive force and torque. Based on the parameters, the motor speed is controlled and minimized the torque ripples. For controlling the speed of the brushless direct current motor is utilized the fractional-order proportional–integral–derivative controller for generating the optimal control pulses. With the use of fractional-order proportional–integral–derivative controller, the optimal gain parameters are needed to reduce the torque ripples and control the speed of brushless direct current motor. By utilizing the hybrid technique, the gain parameters are utilized to analyze the optimal gain parameters of fractional-order proportional–integral–derivative controller. The hybrid technique is the combination of adaptive neuro-fuzzy inference system with firefly algorithm. The proposed strategy is simple in structure and robust to reduce the complexities of the mathematical computations. Initially, the nature inspired optimization algorithm of firefly algorithm is analyzed for finding the error function. In addition, the efficient adaptive neuro-fuzzy inference system controller which becomes an integrated method of approach is performed to control the error functions in order to yields excellent optimized gain values. After that, the control signals are applied to the input of voltage source converter of brushless direct current motor. With this control strategy, the harmonics and torque ripples are minimized. Based on the proposed control strategy, the speed and torque performance is analyzed. The effectiveness of the proposed technique is implemented in MATLAB/Simulink platform and evaluates their performance. The performance analysis of the proposed method is demonstrated and contrasted with the existing techniques such as bat algorithm, particle swarm optimization algorithm and ant–lion optimizer algorithm with fractional-order proportional–integral–derivative controller techniques.

Fractional order Proportional-Integral-Derivative Controller parameter selection based on iterative feedback tuning. Case study: Ball Levitation system

2017 ◽  
Vol 40 (6) ◽  
pp. 1776-1787 ◽  
Author(s):  
Mohsen Rezaei Estakhrouiyeh ◽  
Aliakbar Gharaveisi ◽  
Mohammadali Vali
Keyword(s):  
Fractional Order ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Fractional Order Calculus ◽  
Proportional Integral ◽  
Levitation System ◽  
Fractional Order Controller ◽  
Hardware In Loop ◽  
Iterative Feedback

In the present research, Iterative Feedback Tuning (IFT) algorithm is employed to tune a type of fractional order Proportional-Integral-Derivative (PID) [Formula: see text] controller. For this purpose, fractional order calculus is introduced and some important principles are represented. Then, IFT algorithm is presented in a general form. Following it, IFT algorithm is derived to tune the specific type of PID. The relevant update law is calculated for the fractional order controller. Finally, the proposed algorithm is tested on a Hardware in Loop (HIL) system, that is, Ball Levitation (BL) system, and the efficiency of the proposed method is verified via experiments.

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.

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