# A New PID Neural Network Controller Design for Nonlinear Processes

arXiv: https://arxiv.org/abs/1512.07529 · HTML: https://mlsanity.com/paper/1512.07529/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Dec 2015.

## Built on by (most cited first, 1 of 1)

- [Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e](https://mlsanity.com/paper/2312.17372/) (2023)

## Abstract (arXiv)

In this paper, a novel adaptive tuning method of PID neural network (PIDNN) controller for nonlinear process is proposed. The method utilizes an improved gradient descent method to adjust PIDNN parameters where the margin stability will be employed to get high tracking performance and robustness with regard to external load disturbance and parameter variation. Simulation results show the effectiveness of the proposed algorithm compared with other well-known learning methods.