A flat-zone modification for robust adaptive control of nonlinear output feedback systems with unknown high-frequency gains

2002 ◽  
Vol 47 (2) ◽  
pp. 358-363 ◽  
Author(s):  
Zhengtao Ding ◽  
Xudong Ye
2020 ◽  
Vol 10 (12) ◽  
pp. 4270
Author(s):  
Jiao Chen ◽  
Jiangyun Wang ◽  
Weihong Wang

Model reference adaptive control (MRAC) schemes are known as an effective method to deal with system uncertainties. High adaptive gains are usually needed in order to achieve fast adaptation. However, this leads to high-frequency oscillation in the control signal and may even make the system unstable. A robust adaptive control architecture was designed in this paper for nonlinear aircraft dynamics facing the challenges of input uncertainty, matched uncertainty, and unmatched uncertainty. By introducing a robust compensator to the MRAC framework, the high-frequency components in the control response were eliminated. The proposed control method was applied to the longitudinal-direction motion control of a nonlinear aircraft system. Flight simulation results demonstrated that the proposed robust adaptive method was able to achieve fast adaptation without high-frequency oscillations, and guaranteed transient performance.


2004 ◽  
Vol 126 (1) ◽  
pp. 229-235 ◽  
Author(s):  
Dong H. Kim ◽  
Hua O. Wang ◽  
Hai-Won Yang

This paper describes a systematic procedure to design robust adaptive controllers for a class of nonlinear systems with unknown functions of unknown bounds based on backstepping and sliding mode techniques. These unknown functions can be unmodeled system nonlinearities, uncertainties and disturbances with unknown bounds. Both state feedback and output feedback designs are addressed. In the design procedure, the upper bounds of the unknown functions are estimated using an adaptation strategy, and the estimates are used to design stabilizing functions and control inputs based on the backstepping design methodology. The proposed controllers guarantee that the tracking errors converge to a residual set close to zero exponentially for both state feedback and output feedback designs, while maintaining the boundedness of all other variables.


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