A Biologically Inspired Dynamic Model for Object Recognition

Iftekharuddin, Khan M.; Li, Yaqin; Siddiqui, Faraz

doi:10.1007/978-3-540-73267-9_10

Cited by 1 publication

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References 16 publications

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“…As for industrial applications, ADP has focused on flight control , engine control , power systems , auto‐landing problem , missile systems , artificial intelligence , etc. Enns and Si demonstrated a model‐free nonlinear multi‐input multi‐output (MIMO) helicopter flight controller .…”

Section: Introductionmentioning

confidence: 99%

An approximate dynamic programming method for multi‐input multi‐output nonlinear system

Huang

2011

Optim Control Appl Methods

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SUMMARYApproximate dynamic programming is a useful tool in solving multi-stage decision optimal control problems. In this work, we first promote the action-dependent heuristic dynamic programming method to multi-input multi-output control system by extending its action network to multi-output form. The detailed derivation is also given. We then apply this method to the fluctuation control of a spark engine idle speed. An engine idling model is set up to verify the control effect of this method. Results here show that this method requires several iterations to suppress unbalanced combustion by manipulating spark ignition timing. This method provides an alternative for a simpler multi-input multi-output approximate dynamic programming scheme. Moreover, it has a faster iteration convergence effect. The derivation of this method also has a rigorous mathematical basis. Although illustrated for engines, this control system framework should also be applicable to general multi-input multi-output nonlinear system.

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Section: Introductionmentioning

confidence: 99%

An approximate dynamic programming method for multi‐input multi‐output nonlinear system

Huang

2011

Optim Control Appl Methods

View full text Add to dashboard Cite

show abstract

A Biologically Inspired Dynamic Model for Object Recognition

Cited by 1 publication

References 16 publications

An approximate dynamic programming method for multi‐input multi‐output nonlinear system

An approximate dynamic programming method for multi‐input multi‐output nonlinear system

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