Scientific Research An Academic Publisher. Loh , Witt Thanom , Jan S. ABSTRACT: Electronic throttle control ETC system has worked its way to becoming a standard subsystem in most of the current automobiles as it has contributed much to the improvement of fuel economy, emissions, drivability and safety. Precision control of the subsystem, which consists of a dc motor driving a throttle plate, a pre-loaded return spring and a set of gear train to regulate airflow into the engine, seems rather straightforward and yet complex. The difficulties lie in the unknown system parameters, hard nonlinearity of the pre-loaded spring that pulls the throttle plate to its default position, and friction, among others. Details of modeling and parameters identification based on laboratory experiments, data analysis, and knowledge of the system are provided.
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New articles by this author. New citations to this author. New articles related to this author's research. Email address for updates. My profile My library Metrics Alerts. Sign in. Get my own profile Cited by View all All Since Citations h-index 61 35 iindex Michigan State University. Articles Cited by. Title Sort Sort by citations Sort by year Sort by title. Society for Industrial and Applied Mathematics , International Journal of control 56 5 , , International journal of control 55 6 , , International Journal of Robust and Nonlinear Control 24 6 , , IEEE Transactions on automatic control 53 10 , , Articles 1—20 Show more.
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Nonlinear Systems, 3rd Edition
Scientific Research An Academic Publisher. ABSTRACT: The risk-sensitive filtering design problem with respect to the exponential mean-square cost criterion is con-sidered for stochastic Gaussian systems with polynomial of second and third degree drift terms and intensity parameters multiplying diffusion terms in the state and observations equations. The closed-form optimal fil-tering equations are obtained using quadratic value functions as solutions to the corresponding Focker- Plank-Kolmogorov equation. The performance of the obtained risk-sensitive filtering equations for stochastic polynomial systems of second and third degree is verified in a numerical example against the optimal po-lynomial filtering equations and extended Kalman-Bucy for system polynomial of second degree , through comparing the exponential mean-square cost criterion values. The simulation results reveal strong advan-tages in favor of the designed risk-sensitive equations for some values of the intensity parameters. Related Articles:. Date: December 9,
View larger. Request a copy. Download instructor resources. Additional order info. Buy this product. For a first-year graduate-level course on nonlinear systems.