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contributor authorMa Yu;Cai Yuanli
date accessioned2019-02-26T07:32:29Z
date available2019-02-26T07:32:29Z
date issued2018
identifier other%28ASCE%29AS.1943-5525.0000856.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4247729
description abstractThis paper presents a scheduled composite off-line output feedback model predictive control strategy for a constrained hypersonic vehicle (HV) in the presence of external persistent disturbances. First, multiple linear time invariant (LTI) models are constructed to represent the nominal longitudinal dynamics of HV without external persistent disturbances. Then, by combining the construction of asymptotically stable polyhedral invariant sets for explicitly handling asymmetric constraints of control inputs and angle of attack and the state estimator for estimating partial unmeasured states, a set of local off-line output feedback model predictive control schemes are first developed for multiple LTI models. Additionally, based on the strong nonlinear approximation ability of a recurrent cerebellar model articulation controller (RCMAC), a RCMAC disturbance observer (RCMACDO) is presented to estimate the actual disturbances, and then an auxiliary compensation controller is appended to attenuate the influences of external persistent disturbances. Furthermore, by designing a proper scheduling strategy, the proposed control strategy with the overlapped stable regions is proposed for the wide tracking task. Finally, the comparative simulation results for tracking reference commands of velocity and altitude verify the effectiveness of the proposed control strategy.
publisherAmerican Society of Civil Engineers
titleScheduled Composite Off-Line Output Feedback Model Predictive Control for a Constrained Hypersonic Vehicle Using Polyhedral Invariant Sets
typeJournal Paper
journal volume31
journal issue4
journal titleJournal of Aerospace Engineering
identifier doi10.1061/(ASCE)AS.1943-5525.0000856
page4018035
treeJournal of Aerospace Engineering:;2018:;Volume ( 031 ):;issue: 004
contenttypeFulltext


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