Neural network-based adaptive decentralized learning control for interconnected systems with input constraints
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Publication:2138915
DOI10.1007/S11768-021-00056-WzbMath1490.93007OpenAlexW3197785733MaRDI QIDQ2138915
Publication date: 17 May 2022
Published in: Control Theory and Technology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11768-021-00056-w
Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Decentralized systems (93A14) Hamilton-Jacobi equations in optimal control and differential games (49L12)
Cites Work
- Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem
- On optimality of decentralized control for a class of nonlinear interconnected systems
- Mitigating the curse of dimensionality: sparse grid characteristics method for optimal feedback control and HJB equations
- Decentralized adaptive optimal stabilization of nonlinear systems with matched interconnections
- Single-parameter-learning-based fuzzy fault-tolerant output feedback dynamic surface control of constrained-input nonlinear systems
- Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach
- Decentralized robust control of mechanical systems
- Towards to dynamic optimal control for large-scale distributed systems
- Multi-agent graphical games with input constraints: an online learning solution
- Adaptive dynamic programming for finite-horizon optimal control of linear time-varying discrete-time systems
- Task-Space Synchronization of Networked Robotic Systems With Uncertain Kinematics and Dynamics
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