This chapter introduces a new concept of robust adaptive dynamic programming (RADP), a natural extension of ADP to uncertain dynamic systems. It presents an online learning strategy for the design of robust ada
缺陷和限制-robust adaptive dynamic programmingJo**on 上传1.13MB 文件格式 pdf 中科大软院软 5.1 软件能力 软件完成需求描述的功能,对边界情况和各种条件组合情况也满足输出要求。 5.2 缺陷和限制 健壮性有待提升,测试用例无法穷举,可能有位置错误,没测出来。 5.3 建议 健壮性有待提升,测试多采用的弱...
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...
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...
PDF Tools Share Abstract This study develops an adaptive dynamic programming (ADP) scheme for uncertain systems to achieve the robust trajectory tracking. In this framework, the augmented state is first established via combining the tracking error and reference trajectory, where the robust tracking cont...
Adaptive robust optimization has been applied to develop solutions that effectively address these uncertainties. Ultimately, the results show that, even with the aforementioned uncertainties, the SDN operation is resilient up to a maximum prediction error of 45%. Furthermore, if the distribution ...
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...