Data-based optimal control
WebJun 10, 2005 · This paper deals with data-based optimal control. The control algorithm consists of two complementary subsystems, namely a data-based observer and an … WebApr 13, 2024 · In recent years, the data-driven based FDD (Fault Detection and Diagnosis) of high-speed train electric traction systems has made rapid progress, as the safe operation of traction system is closely related to the reliability and stability of high-speed trains. The internal complexity and external complexity of the environment mean that fault diagnosis …
Data-based optimal control
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WebOct 1, 2024 · The main contribution of this paper is to develop the distributed identifier-critic-based optimal adaptive control method, which is emphasized with the following three properties: (1) the implementation of the distributed controller just depends on the available system data, and thus the proposed approach is model-free; (2) the controller design … WebThe control law solves the optimal consensus problem for multiagent systems with measured I/O information, and does not rely on the model of multiagent systems. A …
WebJan 10, 2024 · A data-based method is proposed to design the initial stabilizing feedback gain that the algorithm requires. Robustness of the algorithm in the presence of noisy measurements is analyzed. We compare the proposed algorithm in simulation to different direct and indirect data-based control design methods. WebMar 9, 2024 · Data-based methods require the system data instead of the accurate knowledge of system dynamics that can be considered as model-free learning control methods. The data-based methods are effective solutions for the optimal control of nonlinear systems, which motivate this special issue.
WebMay 1, 2024 · For model-free optimal control design, this paper proposes an approach based on optimizing the reference model that is used in direct data-driven controller … WebOct 30, 2015 · Data-Based Adaptive Critic Designs for Nonlinear Robust Optimal Control With Uncertain Dynamics Abstract: In this paper, the infinite-horizon robust optimal control problem for a class of continuous-time uncertain nonlinear systems is investigated by using data-based adaptive critic designs.
WebMar 27, 2024 · The problem that it is difficult to balance vehicle stability and economy at the same time under the starting steering condition of a four-wheel independent drive electric …
WebApr 13, 2024 · To obtain the equivalent data model, fuzzy rules emulated networks are utilized to derive a class of discrete-time systems based on the daily hospitalized individuals’ data. The aim of this study is to investigate the optimal control problem to determine the most effective interventional policy including precautionary and awareness measures ... maintenance access toilet chaseWebThe control law solves the optimal consensus problem for multiagent systems with measured I/O information, and does not rely on the model of multiagent systems. A numerical example is provided to illustrate the effectiveness of the proposed algorithm. maintenance acronyms consequence of breakdownWebApr 10, 2024 · An infinite-horizon function is minimized online, which allows the data-based control policy to be considered the optimal control method. The gains of the constrained data-based control signal are computed at each time step to enhance accuracy. Applying the data-based state feedback controller to the system yields positive and stable state ... maintenance activity familiarityWebThis paper investigates data-based optimal control, that is applicable on-line both to regulation and tracking control problems over an arbitrary time interval. A Markov data … maintenance access arkham asylumWebThe model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than th … maintenance activity of flat head screwdriverWebThis paper investigates data-based optimal control, that is applicable on-line both to regulation and tracking control problems over an arbitrary time interval. A Markov data-based LQG control algorithm is suggested in [4]. This al-gorithm derives the control input by adequate processing of several measurements and it consists of two parts ... maintenance administrative clerk salaryWebJun 1, 2024 · This paper presents a model-free reinforcement learning (RL) algorithm to solve the risk-averse optimal control (RAOC) problem for discrete-time nonlinear systems and presents data-driven implementations of these algorithms based on Q-function which enables learning the optimal value without any knowledge of the system dynamics. 4 PDF maintenance agreement for private road