Finite-Approximation-Error-Based Optimal Control Approach for Discrete-Time Nonlinear Systems

By Derong Liu, Qinglai Wei. IEEE Transactions on Cybernetics, 2013

294 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/34db7a4751e6b0fd673ba7991cbabf2c45267ac2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Derong Liu
2. Qinglai Wei
3. Hamidreza Modares
4. Biao Luo
5. Frank L. Lewis
6. Bo Zhao
7. Shan Xue
8. Ding Wang

In Control and Systems Engineering

1. Derong Liu
2. Hamidreza Modares
3. Qinglai Wei
4. Frank L. Lewis
5. Biao Luo
6. Bo Zhao
7. Shan Xue
8. Ding Wang

In Electrical and Electronic Engineering

1. Hamidreza Modares
2. Derong Liu
3. Frank L. Lewis
4. Qinglai Wei
5. Biao Luo
6. Bo Zhao
7. Shan Xue
8. Ding Wang

Citations in the corpus

• Optimal tracking control of nonlinear partially-unknown constrained-input systems using integral reinforcement learning (2014, methodology): “During the last few years, RL methods have been successfully used to solve the optimal regulation problems by learning the solution to the so-called Hamilton–Jacobi–Bellman (HJB) equation (Lewis, Vrabie, & Syrmos, 2012; Liu & Wei, 2013).”
• Adaptive Dynamic Programming for Control: A Survey and Recent Advances (2021, background): “Then, it was shown in [86] and [87] that the iterative value function eventually converges to the neighborhood of the optimal solution in the presence of NN approximation errors.”