Multiple model adaptive control using second level adaptation for a delta-wing aircraft

2015 ◽  
Vol 3 (1) ◽  
pp. 2-17 ◽  
Author(s):  
Narjes Ahmadian ◽  
Alireza Khosravi ◽  
Pouria Sarhadi

Purpose – The purpose of this paper is to design a stable controller such that the control input is applied to the delta-wing aircraft in order to adjust the roll dynamics. The controller must provide a desired tracking performance with minimum tracking error. Design/methodology/approach – In this paper, the second level adaptation (SLA) strategy is applied to control a delta-wing aircraft using multiple models. The implemented control structure is compared with the first level adaptation (FLA) and model reference adaptive control (MRAC) techniques. Findings – SLA architecture not only copes with a wide uncertainty domain caused by aerodynamic effects, but also its rapid and accurate convergence is one of its most important features. Furthermore, this strategy makes a smoother control signal with respect to FLA and MRAC even at the same initial times. It should be also noted that SLA using three models, copes with uncertainty that may occur to the aircraft at high Angle Of Attacks (AOAs) at the entire flight envelope. Originality/value – In this paper for the first time the application of this strategy is used to identify and control a delta-wing aircraft. Furthermore a systematic block diagram approach is proposed for the design.

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Xinhao Yang ◽  
Ze Li

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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