Reinforcement-learning-based output-feedback control of nonstrict nonlinear discrete-time systems with application to engine emission control

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 39, Issue 5, 2009, Pages 1162-1179

  Shih, Peter ^a   Kaul, Brian C ^a   Jagannathan, Sarangapani ^a   Drallmeier, James A ^a  

^a University of Missouri Rolla   (United States)

Author keywords

Adaptive critic; Discrete time system; Engine emission control; Nonstrict nonlinear output feedback; Reinforcement learning control

Indexed keywords

ADAPTIVE CRITIC; ADAPTIVE NEURAL NETWORKS; CERTAINTY EQUIVALENCE; CLOSED-LOOP-TRACKING; CONTROL INPUTS; CYCLIC DISPERSION; DISCRETE-TIME SYSTEM; EQUIVALENCE RATIOS; FEEDBACK FORMS; GRADIENT-DESCENT; HEAT RELEASE; NONLINEAR DISCRETE-TIME SYSTEMS; NONSTRICT NONLINEAR OUTPUT FEEDBACK; OUTPUT FEEDBACK CONTROLS; OXIDES OF NITROGEN; PERFORMANCE INDICES; PERSISTENCY OF EXCITATION; REINFORCEMENT LEARNING CONTROL; SPARK IGNITION ENGINES; TRACKING PERFORMANCE; UNBURNED HYDROCARBONS; UNKNOWN DISTURBANCE; UNKNOWN PARAMETERS; UTILITY FUNCTIONS;

ADAPTIVE CONTROL SYSTEMS; CONTINUOUS TIME SYSTEMS; CONTROLLERS; DIFFERENTIAL EQUATIONS; DIGITAL CONTROL SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; DROPS; EDUCATION; EMISSION CONTROL; HYDROCARBONS; LEAKAGE (FLUID); LEARNING ALGORITHMS; LYAPUNOV FUNCTIONS; REINFORCEMENT; REINFORCEMENT LEARNING; TELECOMMUNICATION NETWORKS;

FEEDBACK;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOMIMETICS; COMPUTER SIMULATION; EXHAUST GAS; FEEDBACK SYSTEM; METHODOLOGY; NONLINEAR SYSTEM; POWER SUPPLY; REINFORCEMENT; SIGNAL PROCESSING; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMIMETICS; COMPUTER SIMULATION; ELECTRIC POWER SUPPLIES; FEEDBACK; MODELS, THEORETICAL; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; REINFORCEMENT (PSYCHOLOGY); SIGNAL PROCESSING, COMPUTER-ASSISTED; VEHICLE EMISSIONS;

EID: 67649411597     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2009.2013272     Document Type: Article

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