# Approximate Optimal Trajectory Tracking for Continuous Time Nonlinear Systems

arXiv: https://arxiv.org/abs/1301.7664 · HTML: https://mlsanity.com/paper/1301.7664/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jan 2013.

## Built on by (most cited first, 2 of 2)

- [Online inverse reinforcement learning with limited data](https://mlsanity.com/paper/2008.08972/) (2020)
- [Control of synaptic plasticity in neural networks](https://mlsanity.com/paper/2303.07273/) (2023)

## Abstract (arXiv)

Approximate dynamic programming has been investigated and used as a method to approximately solve optimal regulation problems. However, the extension of this technique to optimal tracking problems for continuous time nonlinear systems has remained a non-trivial open problem. The control development in this paper guarantees ultimately bounded tracking of a desired trajectory, while also ensuring that the controller converges to an approximate optimal policy.