scholarly journals A NARX Model Reference Adaptive Control Scheme: Improved Disturbance Rejection Fractional-Order PID Control of an Experimental Magnetic Levitation System

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 201
Author(s):  
Hossein Alimohammadi ◽  
Baris Baykant Alagoz ◽  
Aleksei Tepljakov ◽  
Kristina Vassiljeva ◽  
Eduard Petlenkov
Keyword(s):  
Control System ◽  
Disturbance Rejection ◽  
Closed Loop ◽  
Control Structure ◽  
Magnetic Levitation ◽  
Reference Model ◽  
Control Performance ◽  
Control Loops ◽  
Model Reference Adaptive ◽  
Narx Model

Real control systems require robust control performance to deal with unpredictable and altering operating conditions of real-world systems. Improvement of disturbance rejection control performance should be considered as one of the essential control objectives in practical control system design tasks. This study presents a multi-loop Model Reference Adaptive Control (MRAC) scheme that leverages a nonlinear autoregressive neural network with external inputs (NARX) model in as the reference model. Authors observed that the performance of multi-loop MRAC-fractional-order proportional integral derivative (FOPID) control with MIT rule largely depends on the capability of the reference model to represent leading closed-loop dynamics of the experimental ML system. As such, the NARX model is used to represent disturbance-free dynamical behavior of PID control loop. It is remarkable that the obtained reference model is independent of the tuning of other control loops in the control system. The multi-loop MRAC-FOPID control structure detects impacts of disturbance incidents on control performance of the closed-loop FOPID control system and adapts the response of the FOPID control system to reduce the negative effects of the additive input disturbance. This multi-loop control structure deploys two specialized control loops: an inner loop, which is the closed-loop FOPID control system for stability and set-point control, and an outer loop, which involves a NARX reference model and an MIT rule to increase the adaptation ability of the system. Thus, the two-loop MRAC structure allows improvement of disturbance rejection performance without deteriorating precise set-point control and stability characteristics of the FOPID control loop. This is an important benefit of this control structure. To demonstrate disturbance rejection performance improvements of the proposed multi-loop MRAC-FOPID control with NARX model, an experimental study is conducted for disturbance rejection control of magnetic levitation test setup in the laboratory. Simulation and experimental results indicate an improvement of disturbance rejection performance.

Model Reference Adaptive Control Scheme for Retuning Method-Based Fractional-Order PID Control with Disturbance Rejection Applied to Closed-Loop Control of a Magnetic Levitation System

2018 ◽  
Vol 27 (11) ◽  
pp. 1850176 ◽  
Author(s):  
Aleksei Tepljakov ◽  
Baris Baykant Alagoz ◽  
Emmanuel Gonzalez ◽  
Eduard Petlenkov ◽  
Celaleddin Yeroglu
Keyword(s):  
Pid Control ◽  
Disturbance Rejection ◽  
Closed Loop ◽  
Magnetic Levitation ◽  
Control Performance ◽  
Control Loop ◽  
Loop Control ◽  
Disturbance Rejection Control ◽  
Fractional Order Pid ◽  
Model Reference Adaptive

This study demonstrates the utilization of model reference adaptive control (MRAC) for closed-loop fractional-order PID (FOPID) control of a magnetic levitation (ML) system. Design specifications of ML transportation systems require robust performance in the presence of environmental disturbances. Numerical and experimental results demonstrate that incorporation of MRAC and FOPID control can improve the disturbance rejection control performance of ML systems. The proposed multiloop MRAC–FOPID control structure is composed of two hierarchical loops which are working in conjunction to improve robust control performance of the system in case of disturbances and faults. In this multiloop approach, an inner loop performs a regular closed-loop FOPID control, and the outer loop performs MRAC based on Massachusetts Institute of Technology (MIT) rule. These loops are integrated by means of the input-shaping technique and therefore no modification of any parameter of the existing closed-loop control system is necessary. This property provides a straightforward design solution that allows for independent design of each loop. To implement FOPID control of the ML system, a retuning technique is used which allows transforming an existing PID control loop into an FOPID control loop. This paper presents the simulation and experimental results and discusses possible contributions of multiloop MRAC–FOPID structure to disturbance rejection control of the ML system.

Yaw-rate-tracking-based Automated Vehicle Path Following: An MRAC Methodology with A Closed-Loop Reference Model

2021 ◽  
pp. 1-17
Author(s):  
Xingyu Zhou ◽  
Zejiang Wang ◽  
Heran Shen ◽  
Junmin Wang
Keyword(s):  
Closed Loop ◽  
Reference Model ◽  
Path Following ◽  
Control Law ◽  
Hardware In The Loop ◽  
Control Loops ◽  
Path Following Control ◽  
Speed Up ◽  
Vehicle Path ◽  
Model Reference Adaptive

Abstract Concerning automated vehicles, various path-following controllers have been designed by the model reference adaptive control (MRAC) approach. Through appropriate Lyapunov redesigns, asymptotical stability and signal boundedness are ensured for the path-tracking control loops. However, transient behaviors of the closed-loop responses are seldom considered in the context of MRAC synthesis. To bridge the foregoing gap, a closed-loop reference model-based MRAC, which yields an improved transient performance compared with a traditional MRAC, is exploited to synthesize a vehicular path following control law. Besides, an infinitely differentiable projection operator is complemented to the control parameters' adaptation schemes for estimation speed-up and robustness enhancement. Hardware-in-the loop experiments are used to evaluate the proposed method and to demonstrate its improvement over some conventional MRAC designs.

Multimode Adaptive Control for Tank Gun Control System Based on Tracking Differentiator

2011 ◽  
Vol 383-390 ◽  
pp. 79-85
Author(s):  
Dong Yuan ◽  
Xiao Jun Ma ◽  
Wei Wei
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
High Speed ◽  
Control Method ◽  
Reference Model ◽  
Gun Control ◽  
Math Model ◽  
Tracking Differentiator ◽  
Switch Control ◽  
Model Reference Adaptive

Aiming at the problems such as switch impulsion, insurmountability for influence caused by nonlinearity in one tank gun control system which adopts double PID controller to realize the multimode switch control between high speed and low speed movement, the system math model is built up; And then, Model Reference Adaptive Control (MRAC) method based on nonroutine reference model is brought in and the adaptive gun controller is designed. Consequently, the compensation of nonlinearity and multimode control are implemented. Furthermore, the Tracking Differentiator (TD) is affiliated to the front of controller in order to restrain the impulsion caused by mode switch. Finally, the validity of control method in this paper is verified by simulation.

Excitation Liquid-Cooled Retarder Control System Design Based on MC9SXS128

2014 ◽  
Vol 525 ◽  
pp. 583-587
Author(s):  
Bing Tu ◽  
Wei Zhang ◽  
Teng Xi Zhan
Keyword(s):  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Closed Loop ◽  
Good Control ◽  
Control Performance ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Application Requirements

This paper presented a excitation liquid-cooled retarder control system based on a microprocessor MC9SXS128. In order to achieve the constant speed, It used PWM to adjust the output current of excitation liquid-cooled retarder. It analyzed and calculated the inductance value in PWM output circuit and also analyzed the excitation liquid-cooled retarder control systematical mathematical model . It divided the brake stalls based on the current flowing through the field coil. by adding the PID closed-loop control system, the retarder could quickly reach the set speed. It tested the PID control algorithm at the experiments in retarder drum test rig and the results show that the control algorithm has good control performance to meet the application requirements.

An Optimal Preview Acceleration Driver Model with a Correction Factor for Vehicle Directional Control

2013 ◽  
Vol 437 ◽  
pp. 623-628 ◽  
Author(s):  
Hsin Guan ◽  
Li Zeng Zhang ◽  
Xin Jia
Keyword(s):  
Correction Factor ◽  
Closed Loop ◽  
Reference Model ◽  
Driver Model ◽  
Closed Loop System ◽  
Moving Vehicle ◽  
Directional Control ◽  
Modeling Errors ◽  
Acceleration Model ◽  
Model Reference Adaptive

Parameters of the optimal preview acceleration driver model for vehicle directional control are determined by drivers delay/lag time and parameters of the reference model of the controlled vehicle. A moving vehicle is a time-varying and nonlinear system, so it is difficult to obtain accurate parameters of the reference model. If large modeling errors of the reference model occur, the classic driver model cannot ensure the driver/vehicle closed-loop system have a satisfactory performance. In this paper, an improved optimal preview acceleration model with a correction factor was proposed, which is based on sensitivity analysis and MRAC (the model reference adaptive control). Simulation results show that the improved driver model has more satisfactory adaptability and robustness comparing with the classic driver model.

Reconfigurable control for ship steering

2003 ◽  
Vol 217 (1) ◽  
pp. 25-39 ◽  
Author(s):  
E Omerdic ◽  
G N Roberts ◽  
Z Vukic
Keyword(s):  
Control System ◽  
Reference Model ◽  
Fault Tolerant ◽  
Control Performance ◽  
Reconfigurable Control ◽  
Safety Hazards ◽  
Ship Steering ◽  
Control Scheme ◽  
Global Positioning ◽  
Waves And Currents

This paper is concerned with the application of a heuristic approach in the design of a fault-tolerant control system for ship steering. It proposes an advanced reconfigurable control system (RCS) for ship course changing/keeping and track keeping, robust to faults in actuator, gyrocompass and global positioning system (GPS) in the presence of disturbances (waves and currents). The proposed control scheme uses a reference model for compensation of signals from fault sensors and a compensator for reducing the loss of the control performance produced by a fault in the steering machine. In the case of the occurrence of the fault in one or more components, this control system minimizes loss in the control performance and gives enough time for operators to take appropriate action in order to reduce the risk of safety hazards and avoid severe consequences of the fault. The unavoidable penalty of degradation in control performance was found to be acceptable.

Vibration Control of Suspension System Using Proposed Neural Networks

2006 ◽  
Author(s):  
S¸ahin Yıldırım ◽  
I˙kbal Eski
Keyword(s):  
Control System ◽  
Control Method ◽  
Reference Model ◽  
Active Suspension ◽  
Suspension System ◽  
Neural Controller ◽  
Control Approach ◽  
Robust Model ◽  
Proposed Model ◽  
Model Reference Adaptive

This paper investigates a new robust model based neural controller for active suspension system’s vibrations via feedback control approach. The proposed model reference adaptive control system consists of a neural controller, a robust feedback controller, a third-order linear reference model and dynamics of active suspension system. The simulation examples with various standard input signals are included to demonstrate the effectiveness of the proposed control method and show significant improvement over the existing PID controller method. The robustness of the proposed neural controller is also analyzed with white noise disturbances on the suspension system. It is shown that the control system is robustly stable for all road disturbances. Finally, this kind of control approach could be employed in real time vehicle applications.

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