A5090288756- Adaptive Dynamic Programming Control
- Microgrid Control and Optimization
- Frequency Control in Power Systems
- Mechanical Circulatory Support Devices
- Vehicle Dynamics and Control Systems
- Sensorless Control of Electric Motors
- Advanced Control Systems Optimization
- Stability and Controllability of Differential Equations
- Power System Optimization and Stability
- Soil Mechanics and Vehicle Dynamics
- Real-time simulation and control systems
- Advanced Algorithms and Applications
- Iterative Learning Control Systems
- Adaptive Control of Nonlinear Systems
- Advanced Sensor and Control Systems
- Power Systems and Renewable Energy
- Smart Grid Energy Management
- Optimal Power Flow Distribution
Beijing University of Chemical Technology
2023-2024
Shandong University of Technology
2020
Nanchang University
2019
In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming (ADP) technique based on internal model principle (IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely measurement of input and data. More specifically, IMP, control problem can first be converted into stabilization problem. We then design an observer reproduce full system by measuring inputs outputs. Moreover,...
This article proposes an adaptive, optimal, data-driven control approach based on reinforcement learning and adaptive dynamic programming to the three-phase grid-connected inverter employed in virtual synchronous generators (VSGs). takes into account unknown system dynamics different grid conditions, including balanced/unbalanced grids, voltage drop/sag, weak grids. The proposed method is value iteration, which does not rely initial admissible policy for learning. Considering premise that...
The power coupling of the virtual synchronous generator (VSG) in grid-connected mode may aggravate oscillation because a resistance-inductive line. In order to deal with this issue, research study proposes an adaptive and optimal approach controlling VSG via reinforcement learning dynamic programming (ADP). It derives linear nonlinear hybrid equations considering case where line impedance is uncertain. part disturbance, ADP solves feedback control compensation controller, eliminating...
When the grid voltage is unbalanced, positive and negative sequence components in cause current to be disordered. Under balance control, proportional integral (PI) closed-loop control will increase currents instantaneously, which affects safety reliability of inverter operation, PI parameters are difficult select without complete system mathematical model. This paper introduces an adaptive dynamic programming (ADP) approach solve this problem. The best state feedback controller for obtained...
This paper proposed a data-driven adaptive optimal control approach for CVCF (constant voltage, constant frequency) inverter based on reinforcement learning and dynamic programming (ADP). Different from existing literature, the load is treated as uncertainty robust state-feedback controller proposed. The stability of inverter-load system has been strictly analyzed. In order to obtain accurate output current differential signal, this designs tracking differentiator. It ensured that error...
This study presents a novel technique to solve stabilizing regulation for continuous-time systems via adaptive/approximate dynamic programming. To be more precise, first, new virtual system is created replace the existing one. Then, state and differential values are by an observer utilizing output input values. develop controller based on data-driven, we take into account value iteration approach. Compared with adaptive programming methods, method proposed in this does not require integral...