Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach

By Derong Liu, Ding Wang, Hongliang Li. IEEE Transactions on Neural Networks and Learning Systems, 2014

330 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/f8f7ffd65637ac43309d06e54e897beb22223278

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. Shaocheng Tong
2. Yong-ming Li
3. Yanjun Liu
4. Derong Liu
5. Qinglai Wei
6. Haibo He
7. Ding Wang
8. Biao Luo

In Control and Systems Engineering

1. Shaocheng Tong
2. Yanjun Liu
3. Yong-ming Li
4. Kangkang Sun
5. Shuai Sui
6. Derong Liu
7. Ding Wang
8. Haibo He

In Electrical and Electronic Engineering

1. Shaocheng Tong
2. Yong-ming Li
3. Derong Liu
4. Yanjun Liu
5. Qinglai Wei
6. Ding Wang
7. Biao Luo
8. Kangkang Sun

Citations in the corpus

• Observer-Based Adaptive Fuzzy Decentralized Optimal Control Design for Strict-Feedback Nonlinear Large-Scale Systems (2018, methodology): “[38] proposed an adaptive neural optimal decentralized control method for a class of nonlinear large-scale systems.”
• Adaptive Dynamic Programming for Control: A Survey and Recent Advances (2021, background): “It was shown in [210] that decentralized control {ui}i=1 of the interconnected system (78) can be obtained by increasing the local feedback gain proportionally.”
• Fuzzy Approximation-Based Adaptive Backstepping Optimal Control for a Class of Nonlinear Discrete-Time Systems With Dead-Zone (2016, background): “proposed two adaptive NN online learning optimal strategies to stabilize nonlinear continuous-time systems with control constraints [18] and interconnections [19].”
• Adaptive Critic Nonlinear Robust Control: A Survey (2017, methodology): “Letting i(xi) ≤ Qi(xi) and according to [144], we can derive a set of optimal feedback control laws u∗i (xi), i ∈ N+ to minimize the local cost functions”
• Observer-Based Neuro-Adaptive Optimized Control of Strict-Feedback Nonlinear Systems With State Constraints (2021, background): “The works in [23] and [24] designed two adaptive NN optimal control methods for nonlinear systems subject to input saturation and interconnections.”