Results 21 to 30 of about 889,599 (262)
Distributed parameter identification algorithm for large‐scale interconnected systems
IET Control Theory & Applications, 2023 This paper deals with parameter estimation problem of large‐scale systems. A recursive distributed parameter estimation algorithm, based on the minimization of the prediction estimation error method, is developed.
Mounira Hamdi +4 more
doaj +1 more source
Sensors, 2023 This study aims to propose and validate the state space mode decomposition technique for precise mode separation of non-classical damping systems and closely distributed modal systems.
Jungtae Noh, Jae-Seung Hwang
doaj +1 more source
TIME-VARIANT MODEL OF HEAT-AND-MASS EXCHANGE FOR STEAM HUMIDIFIER
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2020 The dynamical model of heat-mass exchange for a steam humidifier with lumped parameters, which can be used for synthesis of control systems by inflowing-exhaust ventilation installations, or industrial complexes of artificial microclimate, is considered.
Igor Golinko, Volodymyr Drevetskiy
doaj +1 more source
Hover flight control of helicopter using optimal control theory [PDF]
INCAS Bulletin, 2015 This paper represents the optimal control theory and its application to the full scale helicopters. Generally the control of a helicopter is a hard task, because its system is very nonlinear, coupled and sensitive to the control inputs and external ...
Ahmed ABOULFTOUH +2 more
doaj +1 more source
Semisupervised Deep State-Space Model for Plant Growth Modeling
Plant Phenomics, 2020 The optimal control of sugar content and its associated technology is important for producing high-quality crops more stably and efficiently. Model-based reinforcement learning (RL) indicates a desirable action depending on the type of situation based on
S. Shibata, R. Mizuno, H. Mineno
doaj +1 more source
Parameter and State Estimator for State Space Models [PDF]
The Scientific World Journal, 2014 This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least ...
Ruifeng Ding, Linfan Zhuang
openaire +3 more sources
Bellman Filtering for State-Space Models [PDF]
SSRN Electronic Journal, 2020 This article presents a filter for state-space models based on Bellman's dynamic programming principle applied to the mode estimator. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while remaining equally inexpensive computationally.
openaire +3 more sources
On the State-Space Model of Unawareness
, 2023 working paper, please reference this version in further ...
openaire +2 more sources
A Meson Binding State Model in Two-Dimensional Space
ParticlesIn this paper, we first show that the four masses of the Upsilon binding states—namely, Y(1S) through Y(4S)—composed of bottom quarks and anti-bottom quarks follow logarithmic spacing. The correlation coefficient R between the experimental values and the
Yasushi Muraki, Shoichi Shibata
doaj +1 more source
Posterior Analysis of State Space Model with Spherical Symmetricity
Journal of Probability and Statistics, 2015 The present work investigates state space model with nonnormal disturbances when the deviation from normality has been observed only with respect to kurtosis and the distribution of disturbances continues to follow a symmetric family of distributions ...
Ranjita Pandey
doaj +1 more source