# Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/neural-network-control-based-adaptive-learning-design-for-nonlinear-systems-with/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yan‐Jun Liu,Jing Li,Shaocheng Tong,C. L. Philip Chen |
| Citations | 513 |
| DOI | 10.1109/tnnls.2015.2508926 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2343036750 |
| PMID | 26978833 |
| Type | article |
| Year | 2016 |

## Paper authors

- [Jing Li](https://scholariq.org/researchers/jing-li-2/)

## Paper journal

- [IEEE Transactions on Neural Networks and Learning Systems](https://scholariq.org/journals/ieee-transactions-on-neural-networks-and-learning-systems/)

## Paper primary topic

- [Adaptive Control of Nonlinear Systems](https://scholariq.org/topics/adaptive-control-of-nonlinear-systems/)

## Paper topics

- [Adaptive Control of Nonlinear Systems](https://scholariq.org/topics/adaptive-control-of-nonlinear-systems/)
- [Adaptive Dynamic Programming Control](https://scholariq.org/topics/adaptive-dynamic-programming-control/)
- [Neural Networks and Applications](https://scholariq.org/topics/neural-networks-and-applications/)

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