Tracking error convergence for multi-input multi-output model reference adaptive control with known nonminimum phase zeros

2015 ◽  
Author(s):  
Kelley E. Hashemi ◽  
Maruthi R. Akella ◽  
Chan-gi Pak
Keyword(s):  
Adaptive Control ◽  
Tracking Error ◽  
Model Reference Adaptive Control ◽  
Model Reference ◽  
Nonminimum Phase ◽  
Model Reference Adaptive

The Model Reference Adaptive Control of the DC Electric Drive System

2014 ◽  
Vol 875-877 ◽  
pp. 2030-2035 ◽  
Author(s):  
Marian Gaiceanu ◽  
Cristian Eni ◽  
Mihaita Coman ◽  
Romeo Paduraru
Keyword(s):  
Adaptive Control ◽  
Reference Model ◽  
Sliding Mode ◽  
Tracking Error ◽  
Model Reference Adaptive Control ◽  
Drive System ◽  
Mode Switching ◽  
Sigmoid Function ◽  
Model Reference ◽  
Model Reference Adaptive

Due to the parametric and structural uncertainty of the DC drive system, an adaptive control method is necessary. Therefore, an original model reference adaptive control (MRAC) for DC drives is proposed in this paper. MRAC ensures on-line adjustment of the control parameters with DC machine parameter variation. The proposed adaptive control structure provides regulating advantages: asymptotic cancellation of the tracking error, fast and smooth evolution towards the origin of the phase plan due to a sliding mode switching k-sigmoid function. The reference model can be a real strictly positive function (the tracking error is also the identification error) as its order is relatively higher than one degree. For this reason, the synthesis of the adaptive control will use a different type of error called augmented or enhanced error. The DC machine with separate excitation is fed at a constant flux. This adaptive control law assures robustness to external perturbations and to unmodelled dynamics.

Composite Model Reference Adaptive Control for a Class of Nonlinear Fractional Order Systems

2015 ◽  
Author(s):  
Yiheng Wei ◽  
Shu Liang ◽  
Yangsheng Hu ◽  
Yong Wang
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Closed Loop ◽  
Tracking Error ◽  
Model Reference Adaptive Control ◽  
Prediction Errors ◽  
Model Reference ◽  
Closed Loop Systems ◽  
The Stability ◽  
Model Reference Adaptive

This article presents a novel model reference adaptive control of fractional order nonlinear systems, which is a generalization of existing method for integer order systems. The formulating adaptive law is in terms of both tracking and prediction errors, whereas existing methods only depends on tracking error. The transient performance of the closed-loop systems with the proposed control strategy improves in the sense of generating smooth system output. The stability and tracking convergence of the resulting closed-loop system are analyzed via the indirect Lyapunov method. Meanwhile, the proposed controller is implemented by employing some fractional order tracking differentiator to generate the required fractional derivatives of a signal. Numerical examples are provided to illustrate the effectiveness of our results.

scholarly journals Robust Model Reference Adaptive Control for Tail-Sitter VTOL Aircraft

Actuators ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 162
Author(s):  
Ahmed R. Ajel ◽  
Amjad J. Humaidi ◽  
Ibraheem Kasim Ibraheem ◽  
Ahmad Taher Azar
Keyword(s):  
Adaptive Control ◽  
Stability Analysis ◽  
Dead Zone ◽  
Tracking Error ◽  
Model Reference Adaptive Control ◽  
Roll Motion ◽  
Wind Disturbance ◽  
Model Reference ◽  
Adaptive Laws ◽  
Model Reference Adaptive

This study presents a control design of roll motion for a vertical take-off and landing unmanned air vehicle (VTOL-UAV) design based on the Model Reference Adaptive Control (MRAC) scheme in the hovering flight phase. The adaptive laws are developed for the UAV system under nonparametric uncertainty (gust and wind disturbance). Lyapunov-based stability analysis of the adaptive controlled UAV system under roll motion has been conducted and the adaptive laws have been accordingly developed. The Uniform Ultimate Boundness (UUB) of tracking error has been proven and the stability analysis showed that the incorporation of dead-zone modification in adaptive laws could guarantee the uniform boundness of all signals. The computer simulation has been conducted based on a proposed controller for tracking control of the roll motion. The results show that the drift, which appears in estimated gain behaviors due to the application of gust and wind disturbance, could be stopped by introducing dead-zone modification in adaptive laws, which leads to better robustness characteristics of the adaptive controller.

A Model Reference Adaptive Control of a Magnetorheological Fluid Brake

2012 ◽  
Vol 77 ◽  
pp. 96-102
Author(s):  
Riccardo Russo ◽  
Mario Terzo
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Tracking Error ◽  
Magnetorheological Fluid ◽  
Model Reference Adaptive Control ◽  
Uncertain Parameters ◽  
Model Reference ◽  
Braking Torque ◽  
Feedback Control Method ◽  
Model Reference Adaptive

The paper describes an experimental/theoretical activity that involves a magnetorheological fluid brake (MRFB). The variability affecting the plant parameters suggests the employment of a model reference adaptive control finalized to regulate the braking torque. This feedback control method is able to minimize the tracking error in presence of a plant characterized by a known dynamics and uncertain parameters. Numerical simulations have been carried out and the obtained results confirm the goodness of the proposed approach.

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