Design Optimization of Direct Heuristic Dynamic Programming Based on Hybrid Estimation of Distribution Algorithm
As an important class of approximate dynamic programming, the direct heuristic dynamic programming (DHDP) is discussed in this paper.DHDP performs well due to its model-free online learning capability.While the classical DHDP is implemented with gradient-based adaptation learning algorithm of neural network, in this paper we present a design strategy of DHDP with a novel hybrid estimation of distribution algorithm for online learning and control, and the proposed design optimization method achieves the weight training of neural networks with faster convergence rate.Our proposed approach can be viewed as an improvement for DHDP.The simulation is conducted on a practical system plant to test the online learning performance by using our approach.Then, the simulation results show the effectiveness of our approach.
Approximate Dynamic Programming Direct Heuristic Dynamic Programming Estimation of Distribution Algorithm Online Learning
Xiong LUO Mi ZHOU Yixuan LV
School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing 100083,China;Beijing Key Laboratory of Knowledge Engineering for Materials Science,Beijing 100083,China
国内会议
金华
英文
1-9
2015-10-30（万方平台首次上网日期，不代表论文的发表时间）