scholarly journals Adaptive Dynamic Surface Control for a Class of Nonlinear Pure-Feedback Systems with Parameter Drift

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Cheng He ◽  
Jian Wu ◽  
Jin Ying ◽  
Jiyang Dai ◽  
Zhe Zhang ◽  
...  

In order to solve the problem of unknown parameter drift in the nonlinear pure-feedback system, a novel nonlinear pure-feedback system is proposed in which an unconventional coordinate transformation is introduced and a novel unconventional dynamic surface algorithm is designed to eliminate the problem of “calculation expansion” caused by the use of backstepping in the pure-feedback system. Meanwhile, a sufficiently smooth projection algorithm is introduced to suppress the parameter drift in the nonlinear pure-feedback system. Simulation experiments demonstrate that the designed controller ensures the global and ultimate boundedness of all signals in the closed-loop system and the appropriate designed parameters can make the tracking error arbitrarily small.

2011 ◽  
Vol 110-116 ◽  
pp. 4381-4388
Author(s):  
Amezquita S. Kendrick ◽  
Lin Yan ◽  
Waseem Aslam Butt

An adaptive dynamic surface control scheme for actuator failures compensation in a class of nonlinear system is presented. Radial basis function neural networks (RBF NNs) are incorporated into our controller design, for approximating the nonlinearities around the known nominal model. The RBF NNs compensate the system dynamics uncertainties and disturbance induced by actuator failures. The closed-loop signals of the system are proven to be uniformly ultimately bounded (UUB) by Lyapunov analysis. The output tracking error is bounded within a residual set which can be made small by appropriately choosing the controller parameters. We show the effectiveness of our approach by simulating the longitudinal dynamics of a twin otter aircraft with half portion of the elevator failing at unknown value and time instant.


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