NDLI: Distributed mixed continuous-discrete receding horizon filter for multisensory uncertain active suspension systems with measurement delays

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Distributed mixed continuous-discrete receding horizon filter for multisensory uncertain active suspension systems with measurement delays

Content Provider	IET Digital Library
Author	Song, Il Young Shin, Vladimir
Abstract	This study presents a new robust filtering method in modelling an active multisensory suspension system with measurement delays and parameteric uncertainties in a state-space dynamical model. To achieve good performance of the system, a new distributed fusion receding horizon filtering frameworks are constructed to couple the continuous dynamics with the multisensory discrete measurements, and to coordinately deal with the parametric uncertainty and time-delays. The novel filtering algorithm is proposed based on the receding horizon strategy, standard mixed continuous-discrete Kalman filtering and discrete Kalman filtering for systems with time-delays in order to achieve high estimation accuracy and stability under parametric uncertainties. The key theoretical contributions of this study are the derivation of the error cross-covariance equations between the local receding horizon filters in order to compute the optimal matrix fusion weights. The high accuracy and efficiency of the new filter are demonstrated through its implementation and performance and then compared to the existing vehicle active suspension system.
Starting Page	1922
Ending Page	1931
Page Count	10
ISSN	17518644
Volume Number	7
e-ISSN	17518652
Issue Number	Issue 15, Oct (2013)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/7/15
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2013.0179
Journal	IET Control Theory & Applications
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Active Multisensory Suspension System Automotive Component Continuous System Delay System Digital Signal Processing Discrete Control System Discrete System Distributed Fusion Receding Horizon Filtering Distributed Mixed Continuous-discrete Filter Distributed Parameter Control System Error Cross-covariance Equation Kalman Filter Measurement Delay Mechanical Component Mixed Continuous-discrete Kalman Filtering Multisensory Discrete Measurement Multisensory Uncertain Active Suspension System Optimal Matrix Fusion Weight Parameteric Uncertainty Road Traffic Control Road Traffic System Control Robust Filtering Method Stability Stability in Control Theory State-Space Dynamical Model Suspensions Uncertain System
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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