Robust adaptive dynamic programming for large-scale systems with an application to multimachine power systems. IEEE Transactions on Circuits and Systems II: Express Briefs, 2012, 59(10): 693-697Y. Jiang, Z.P. Jiang, Robust adaptive dynamic programming for large-scale systems with an application...
Then, the idea of neural dynamic programming is adopted to perform the main controller design task by building and training a critic network. Finally, the effectiveness of the present adaptive robust control strategy is illustrated via a simulation example....
With the wish to solve the optimal control problem online, reinforcement learning (RL) was further explored, leading to the named adaptive dynamic programming (ADP) method [13]. In recent years, ADP has been proved as a feasible technique to learn the optimal control solution [14], [15], ...
This brief studies the cooperative output regulation problems of multi-agent systems with parametric and dynamic uncertainties. By means of robust adaptive dynamic programming, a model-free distributed controller is developed via online input and state data. The cyclic-small-gain theorem is applied to...
This paper aims to develop a robust optimal control method for longitudinal dynamics of missile systems with full-state constraints suffering from mismatched disturbances by using adaptive dynamic programming (ADP) technique. First, the constrained states are mapped by smooth functions, thus, the conside...
Taking inspiration from zeroing neural dynamics with fixed-time convergence and robustness, this paper proposes an adaptive fixed-time robust controller (AFTRC) for tracking time-varying tasks of quadrotors. In the construction of the AFTRC, a new adaptive parameter based on system error is introduc...
To describe the multi-energy carrier system uncertainties, an adaptive robust integrated bidding strategy has been presented in Ref. [175] for the EH participating in day-ahead energy markets. The proposed model has been designed as a min-max-min problem in the sense of adaptive RO, and it ...
Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming doi:10.1109/TNNLS.2020.3009015Shan XueBiao LuoDerong LiuIEEEIEEE Transactions on Neural Networks and Learning Systems Q Zhang,D Zhao,D Wang - 《IEEE Transactions on Neural Networks & Learning Systems》 被引量...
This approach accounts the dynamic nature of real-world problems by incorporating adaptability. This research paper focuses on leveraging unsupervised learning to improve uncertainty modelling in robust optimization. The primary objective is to propose an adaptive framework that starts from data leading to...
Zhong-Ping JIANG is a Professor ofElectrical and Computer Engineering at New York University, a recipient of theDistinguished Overseas Chinese Scholar Award from the NSF of China. Prof. Jiangis a Fellow of the IEEE and a Fellow of the IFAC.0...