scholarly journals Transient performance, resetting and filtering in nonlinear multiple model adaptive control

2004 ◽  
Author(s):  
J. Hansen ◽  
T.A. Johansen
Keyword(s):  
Adaptive Control ◽  
Multiple Model ◽  
Transient Performance ◽  
Multiple Model Adaptive Control

scholarly journals Adaptive Control for a Class of Nonlinear System with Redistributed Models

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Haisen Ke ◽  
Jiang Li
Keyword(s):  
Adaptive Control ◽  
Nonlinear System ◽  
Adaptive Controller ◽  
Multiple Models ◽  
Multiple Model ◽  
Transient Performance ◽  
Feedback Form ◽  
System A ◽  
Multiple Model Adaptive Control ◽  
The Stability

Multiple model adaptive control has been investigated extensively during the last ten years in which the “switching” or “switching and tuning” have emerged as the mainly approaches. It is the “switching” that can improve the transient performance to some extent and also make it difficult to analyze the stability of the system with multiple models adaptive controller. Towards this goal, this paper develops a novel multiple models adaptive controller for a class of nonlinear system in parameter-strict-feedback form which not only improves the transient performance significantly, but also guarantees the stability of all the states of the closed-loop system. A simulation example is proposed to illustrate the effectiveness of the developed multiple models adaptive controller.

scholarly journals Congestion Control Based on Multiple Model Adaptive Control

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Xinhao Yang ◽  
Ze Li
Keyword(s):  
Adaptive Control ◽  
Congestion Control ◽  
Output Feedback ◽  
Control Method ◽  
Feedback Controller ◽  
Multiple Model ◽  
Network Condition ◽  
Output Feedback Controller ◽  
Weight Calculation ◽  
Multiple Model Adaptive Control

The congestion controller based on the multiple model adaptive control is designed for the network congestion in TCP/AQM network. As the conventional congestion control is sensitive to the variable network condition, the adaptive control method is adopted in our congestion control. The multiple model adaptive control is introduced in this paper based on the weight calculation instead of the parameter estimation in past adaptive control. The model set is composed by the dynamic model based on the fluid flow. And three “local” congestion controllers are nonlinear output feedback controller based on variable RTT, H2output feedback controller, and proportional-integral controller, respectively. Ns-2 simulation results in section 4 indicate that the proposed algorithm restrains the congestion in variable network condition and maintains a high throughput together with a low packet drop ratio.

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