# Adaptive Dynamic Programming Control

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/adaptive-dynamic-programming-control/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the application of Adaptive Dynamic Programming and Reinforcement Learning techniques to solve optimal control problems in continuous-time nonlinear systems. It explores the use of neural networks, policy iteration, actor-critic algorithms, and $H_{infty}$ control for online learning and feedback control in various domains such as robotics, energy management, and multi-agent systems. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t12794 |
| Works | 10 |

## Topic papers all

- [Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints](https://scholariq.org/papers/neural-network-control-based-adaptive-learning-design-for-nonlinear-systems-with/)
- [Neural-Network-Based Adaptive Leader-Following Control for Multiagent Systems With Uncertainties](https://scholariq.org/papers/neural-network-based-adaptive-leader-following-control-for-multiagent-systems/)
- [Adaptive Neural Dynamic Surface Control With Prespecified Tracking Accuracy of Uncertain Stochastic Nonstrict-Feedback Systems](https://scholariq.org/papers/adaptive-neural-dynamic-surface-control-with-prespecified-tracking-accuracy-of/)
- [Adaptive Impedance Control of Human–Robot Cooperation Using Reinforcement Learning](https://scholariq.org/papers/adaptive-impedance-control-of-human-robot-cooperation-using-reinforcement/)
- [Adaptive NN output‐feedback decentralized stabilization for a class of large‐scale stochastic nonlinear strict‐feedback systems](https://scholariq.org/papers/adaptive-nn-output-feedback-decentralized-stabilization-for-a-class-of-large/)
- [Approximate dynamic programming-based approaches for input–output data-driven control of nonlinear processes](https://scholariq.org/papers/approximate-dynamic-programming-based-approaches-for-input-output-data-driven/)
- [Globally stable direct adaptive backstepping NN control for uncertain nonlinear strict-feedback systems](https://scholariq.org/papers/globally-stable-direct-adaptive-backstepping-nn-control-for-uncertain-nonlinear/)
- [Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay](https://scholariq.org/papers/design-of-a-completely-model-free-adaptive-control-in-the-presence-of-parametric/)
- [A recurrent neural network with finite-time convergence for convex quadratic bilevel programming problems](https://scholariq.org/papers/a-recurrent-neural-network-with-finite-time-convergence-for-convex-quadratic/)
- [LLM-Driven Pareto-Optimal Multi-Mode Reinforcement Learning for Adaptive UAV Navigation in Urban Wind Environments](https://scholariq.org/papers/llm-driven-pareto-optimal-multi-mode-reinforcement-learning-for-adaptive-uav/)

## Topic primary papers

- [Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay](https://scholariq.org/papers/design-of-a-completely-model-free-adaptive-control-in-the-presence-of-parametric/)
- [LLM-Driven Pareto-Optimal Multi-Mode Reinforcement Learning for Adaptive UAV Navigation in Urban Wind Environments](https://scholariq.org/papers/llm-driven-pareto-optimal-multi-mode-reinforcement-learning-for-adaptive-uav/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.