Hypersonic Vehicle Trajectory Optimization and Control
نویسندگان
چکیده
This paper presentsa classofmodifiedHopfieldneuralnetworks and theiruse insolvingaircraftoptimalcontroland identificationproblems.This classofnetworksconsistsofparallelrecurrentnetworks which have variabledimensions that can bechanged tofithe problemsunder considezal;ion.Ithas a structureto implement aninversetransformationthatisessentialforembedding optimalcontrolgainsequences.Equilibriumsolutionsaxe discussed.Energy minimizationofthe networks leadstoidentificationfthe system parameters.Numerical resultsareprovided toidenti_vthe dynamics ofan aircraft,and the correspondingoptimalcontroliscalculatedon-line.Comparison of the neuralnetwork solutionswith point-wiseoptimalcontrolusing LQiW.formulationforthismuitivaxiablecontrolproblem shows nearidencica/resultsthroughoutthe trajectories,
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