Satellite Attitude Tracking Control of Moving Targets combining Deep Reinforcement Learning and Predefined-time Stability considering Energy Optimization

2021 ◽  
Author(s):  
Zhong Shi ◽  
Fanyu Zhao ◽  
Xin Wang ◽  
Zhonghe Jin
Keyword(s):  
Reinforcement Learning ◽  
Tracking Control ◽  
Energy Optimization ◽  
Moving Targets ◽  
Time Stability ◽  
Satellite Attitude ◽  
Attitude Tracking ◽  
Attitude Tracking Control

Robust fault-tolerant flight control of quadrotor against faults in multiple motors

2021 ◽  
pp. 095441002199954
Author(s):  
Dinesh D Dhadekar ◽  
S E Talole
Keyword(s):  
Flight Control ◽  
Tracking Control ◽  
Fault Tolerant ◽  
External Disturbances ◽  
Detection And Identification ◽  
Attitude Tracking ◽  
Fault Detection And Identification ◽  
Attitude Tracking Control ◽  
Disturbance Estimator

In this article, position and attitude tracking control of the quadrotor subject to complex nonlinearities, input couplings, aerodynamic uncertainties, and external disturbances coupled with faults in multiple motors is investigated. A robustified nonlinear dynamic inversion (NDI)-based fault-tolerant control (FTC) scheme is proposed for the purpose. The proposed scheme is not only robust against aforementioned nonlinearities, disturbances, and uncertainties but also tolerant to unexpected occurrence of faults in multiple motors. The proposed scheme employs uncertainty and disturbance estimator (UDE) technique to robustify the NDI-based controller by providing estimate of the lumped disturbance, thereby enabling rejection of the same. In addition, the UDE also plays the role of fault detection and identification module. The effectiveness and benefits of the proposed design are confirmed through 6-DOF simulations and experimentation on a 3-DOF Hover platform.

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