Neural Network-based Adaptive Backstepping Controller for UAV Quadrotor system

2020 ◽  
Author(s):  
Lemya Guettal ◽  
Abdelghani Chelihi ◽  
Mostefa Mohamed Touba ◽  
Hossam-Eddine Glida ◽  
Riadh Ajgou
Keyword(s):  
Neural Network ◽  
Adaptive Backstepping ◽  
Backstepping Controller ◽  
Quadrotor System ◽  
Adaptive Backstepping Controller

scholarly journals Adaptive backstepping controller design based on neural network for PMSM speed control

2021 ◽  
Vol 12 (3) ◽  
pp. 1940
Author(s):  
E. Sabouni ◽  
B. Merah ◽  
I. K. Bousserhane
Keyword(s):  
Neural Network ◽  
Control Algorithm ◽  
Controller Design ◽  
Classical Method ◽  
Permanent Magnet Synchronous Motor ◽  
Adaptive Controller ◽  
Nonlinear Controller ◽  
Adaptive Backstepping ◽  
Backstepping Controller ◽  
Adaptive Backstepping Controller

<span lang="EN-US">The aim of this research is the speed tracking of the permanent magnet synchronous motor (PMSM) using an intelligent Neural-Network based adapative backstepping control. First, the model of PMSM in the Park synchronous frame is derived. Then, the PMSM speed regulation is investigated using the classical method utilizing the field oriented control theory. Thereafter, a robust nonlinear controller employing an adaptive backstepping strategy is investigated in order to achieve a good performance tracking objective under motor parameters changing and external load torque application. In the final step, a neural network estimator is integrated with the adaptive controller to estimate the motor parameters values and the load disturbance value for enhancing the effectiveness of the adaptive backstepping controller. The robsutness of the presented control algorithm is demonstrated using simulation tests. The obtained results clearly demonstrate that the presented NN-adaptive control algorithm can provide good trackingperformances for the speed trackingin the presence of motor parameter variation and load application.</span>

scholarly journals Composite adaptive backstepping controller design and the energy calculation for active suspension system

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110105
Author(s):  
Xiaoyu Su ◽  
Bin Lin ◽  
Shuai Liu
Keyword(s):  
Adaptive Algorithm ◽  
Power Calculation ◽  
Calculation Formula ◽  
Adaptive Backstepping ◽  
Adaptive Law ◽  
Car Suspension ◽  
Backstepping Controller ◽  
Suspension Model ◽  
Storage Characteristics ◽  
Adaptive Backstepping Controller

The half-car suspension has the coupling of pitch angle and front and rear suspension. Especially when the suspension model has a series of uncertainties, the traditional linear control method is difficult to be applied to the half-car suspension model. At present, there is no systematic method to solve the suspension power. According to the energy storage characteristics of the elastic components of the suspension, the power calculation formula is proposed in this paper. This paper proposes a composite adaptive backstepping control scheme for the half-car active suspension systems. In this method, the correlation information between the output error and the parameter estimation error is used to construct the adaptive law. According to the energy storage characteristics of the elastic components of the suspension, the power calculation formula is introduced. The compound adaptive law and the ordinary adaptive law have good disturbance suppression, both of which can solve the pitching angle problem of the semi-car suspension, but the algorithm of the compound adaptive law is superior in effect. In terms of vehicle comfort, the algorithm of the general adaptive law can achieve stability quickly, but compared with the composite adaptive law, its peak value and jitter are higher, while the algorithm of the composite adaptive law is relatively gentle and has better adaptability to human body. In terms of vehicle handling, both control algorithms can maintain driving safety under road excitation, and the compound adaptive algorithm appears to have more advantages. Compared with the traditional adaptive algorithm, the power consumption of the composite adaptive algorithm is relatively lower than that of the former in the whole process. The simulation results show that the ride comfort, operating stability and safety of the vehicle can be effectively improved by the composite adaptive backstepping controller, and the composite adaptive algorithm is more energy-saving than the conventional adaptive algorithm based on projection operator.

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