Guaranteed Model Reference Adaptive Control Performance in the Presence of Actuator Failures

2017 ◽  
Author(s):  
Ehsan Arabi ◽  
Benjamin C. Gruenwald ◽  
Tansel Yucelen ◽  
James E. Steck
Keyword(s):  
Adaptive Control ◽  
Model Reference Adaptive Control ◽  
Control Performance ◽  
Model Reference ◽  
Actuator Failures ◽  
Model Reference Adaptive

scholarly journals Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems

2017 ◽  
Vol 13 (2) ◽  
Author(s):  
Omar Farouq Lutfy ◽  
Maryam Hassan Dawood
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Adaptive Control ◽  
Artificial Immune System ◽  
Model Reference Adaptive Control ◽  
Wavelet Neural Network ◽  
Control Performance ◽  
Artificial Immune ◽  
Model Reference ◽  
Model Reference Adaptive

Abstract  This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control performance of the SRWNN-based MRAC. As the training method, the recently developed modified micro artificial immune system (MMAIS) was used to optimize the parameters of the SRWNN. The effectiveness of this control approach was demonstrated by controlling several nonlinear dynamical systems. For each of these systems, several evaluation tests were conducted, including control performance tests, robustness tests, and generalization tests. From these tests, the SRWNN-based MRAC has exhibited its effectiveness regarding accurate control, disturbance rejection, and generalization ability. In addition, a comparative study was made with other related controllers, namely the original WNN, the artificial neural network (ANN), and the modified recurrent network (MRN). The results of these comparison tests indicated the superiority of the SRWNN controller over the other related controllers. Keywords: Artificial neural network, micro artificial immune system, model reference adaptive control, self-recurrent wavelet neural network , Wavelet neural network.

Adaptive Actuator Failure and Structural Damage Compensation of NASA Generic Transport Model

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Jiaxing Guo ◽  
Gang Tao ◽  
Yu Liu
Keyword(s):  
Adaptive Control ◽  
Structural Damage ◽  
Transport Model ◽  
Fault Tolerant ◽  
Model Reference Adaptive Control ◽  
Multivariable Model ◽  
Model Reference ◽  
Actuator Failures ◽  
Aircraft Systems ◽  
Model Reference Adaptive

This paper studies design and evaluation of a multivariable model reference adaptive control (MRAC) scheme for aircraft systems under simultaneous actuator failures and structural damage. A key design condition–system infinite zero structure is investigated for nominal and posthazard aircraft systems and the invariance of this essential condition is concluded under realistic failure and damage conditions. The multivariable model reference adaptive control scheme is developed to ensure stability and asymptotic output tracking for the aircraft in the presence of uncertain actuator failures and structural damage. The developed fault-tolerant control design is evaluated by a high-fidelity nonlinear aircraft model–the NASA generic transport model.

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