@article{(Open Science Index):https://publications.waset.org/pdf/10011696,
	  title     = {State Estimation Method Based on Unscented Kalman Filter for Vehicle Nonlinear Dynamics},
	  author    = {Wataru Nakamura and  Tomoaki Hashimoto and  Liang-Kuang Chen},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper provides a state estimation method for
automatic control systems of nonlinear vehicle dynamics. A nonlinear
tire model is employed to represent the realistic behavior of a vehicle.
In general, all the state variables of control systems are not precisedly
known, because those variables are observed through output sensors
and limited parts of them might be only measurable. Hence, automatic
control systems must incorporate some type of state estimation. It is
needed to establish a state estimation method for nonlinear vehicle
dynamics with restricted measurable state variables. For this purpose,
unscented Kalman filter method is applied in this study for estimating
the state variables of nonlinear vehicle dynamics. The objective of
this paper is to propose a state estimation method using unscented
Kalman filter for nonlinear vehicle dynamics. The effectiveness of
the proposed method is verified by numerical simulations.},
	    journal   = {International Journal of Electrical and Information Engineering},
	  volume    = {14},
	  number    = {12},
	  year      = {2020},
	  pages     = {435 - 438},
	  ee        = {https://publications.waset.org/pdf/10011696},
	  url   	= {https://publications.waset.org/vol/168},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 168, 2020},
	}