scholarly journals Integral Command Filtered Backstepping Control of a Flexible UAV

2018 ◽  
Vol 160 ◽  
pp. 05005
Author(s):  
Ding Han ◽  
Lin Yan ◽  
Guozheng Yan ◽  
Xiaoliang Wang ◽  
Dengping Duan
Keyword(s):  
Control Systems ◽  
Flight Control ◽  
Research Effort ◽  
Tracking Error ◽  
Rate Of Change ◽  
Body Motion ◽  
Nonlinear Controller ◽  
Integral Action ◽  
Tracking Ability ◽  
Backstepping Controller

Airships, as the significant UAV, have a need for greater autonomy in their new missions. Therefore, airship flight control systems require precise dynamic modeling, taking into account the effect of flexibility and the interaction with aerodynamic forces. This research effort develops an efficient modeling of the autonomous flexible airship. The formalisation used is based on the Lagrange method. The resulting model includes the rigid body motion, the elastic deformation, and the coupling between them. Based on the precise flexible dynamic model, a novel backstepping nonlinear controller with integral action is proposed for motion control systems. The resulting feedback controller is able to adapt to actuator performance limitations, such as limitations in magnitude and rate of change of rudder, than conventional backstepping controller without integral action. With the deformation considered, the presented controller could resist the flexible uncertainty effect, and the system’s trajectory tracking ability is significantly improved. The approach guarantees exponential stability of a compensated tracking error in the sense of Lyapunov.

Design of an Optimal Integral Backstepping Controller for a Quadcopter

2018 ◽  
Vol 24 (5) ◽  
pp. 46
Author(s):  
Laith Jasim Saud ◽  
Alaq Falah Hasan
Keyword(s):  
Pid Controller ◽  
Tracking Error ◽  
Absolute Error ◽  
Swarm Optimization ◽  
Full Control ◽  
Integral Action ◽  
Control Scheme ◽  
Optimal Values ◽  
Backstepping Controller ◽  
Yaw Angle

In this paper, an Integral Backstepping Controller (IBC) is designed and optimized for full control, of rotational and translational dynamics, of an unmanned Quadcopter (QC). Before designing the controller, a mathematical model for the QC is developed in a form appropriate for the IBC design. Due to the underactuated property of the QC, it is possible to control the QC Cartesian positions (X, Y, and Z) and the yaw angle through ordering the desired values for them. As for the pitch and roll angles, they are generated by the position controllers. Backstepping Controller (BC) is a practical nonlinear control scheme based on Lyapunov design approach, which can, therefore, guarantee the convergence of the position tracking error to zero. To improve controller capability in the steady state against disturbances, an integral action is used with the BC. To determine the optimal values of the IBC parameters, the Particle Swarm Optimization (PSO) is used. In the algorithm, the controller parameters are computed by minimizing a cost function that depends on the Integral Time Absolute Error (ITAE) performance index. Finally, different numerical simulations are provided in order to illustrate the performances of the designed controller. And for comparison purposes, a PID controller is designed and optimized using the PSO to control the quadcopter. The obtainediresults indicated a superiority in performance for the IBC over the PID controller based on some points among which are: a 13.3% and 30.5% lesser settling times for X and Y consequently, the ability to perform critical maneuvers that the quadcopter failed to do using the PID controller, and the capability of fast following up and conforming the changes of pitch (

scholarly journals The Effects of Weighting Functions on the Performances of Robust Control Systems

Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 46
Author(s):  
Mircea Dulau ◽  
Stelian-Emilian Oltean
Keyword(s):  
Robust Control ◽  
Control Systems ◽  
Tracking Error ◽  
Weighting Functions ◽  
Loop Control ◽  
Frequency Sensitivity ◽  
Sensitivity Functions ◽  
Loop Control System ◽  
Robust Control Design ◽  
Robust Control Systems

An important stage in robust control design is to define the desired performances of the closed loop control system using the models of the frequency sensitivity functions S. If the frequency sensitivity functions remain within the limits imposed by these models, the control performances are met. In terms of the sensitivity functions, the specifications include: shape of S over selected frequency ranges, peak magnitude of S, bandwidth frequency, and tracking error at selected frequencies. In this context, this paper presents a study of the effects of the specifications of the weighting functions on the performances of robust control systems.

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