Automotive Engine Idle Speed Control with Recurrent Neural Networks
作者： G. V. Puskorius , L. A. Feldkamp
DOI: 10.23919/ACC.1993.4792864
关键词:
摘要: This paper describes the development of recurrent neural network controllers for an automotive engine idle speed control (ISC) problem. Engine ISC is a difficult problem because troublesome characteristics such as severe process nonlinearities, variable time delays, time-varying dynamics and unobservable system states disturbances. We demonstrate that can be trained to handle these difficulties gracefully while achieving good regulator performance representative model 4-cylinder, 1.6 liter engine. Empirical results clearly illustrate with relatively large amounts internal feedback provide more robust than do are static or contain limited connections.
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