Advanced control based on Recurrent Neural Networks learned using Virtual Reference Feedback Tuning and application to an Electronic Throttle Body (with supplementary material)

Voltage Instability Prediction Using a Deep Recurrent Neural Network

This paper develops a new method for voltage instability prediction using a recurrent neural network with long short-term memory. The method is aimed to be used as a supplementary warning system for system operators, capable of assessing whether the current state will cause voltage instability issues several minutes into the future. The proposed method use a long sequence-based network, where both real-time and historic data are used to enhance the classification accuracy. The network is trained and tested on the Nordic32 test system, wherecombinations of different operating conditions and con…

用于起伏船甲板自主着陆的屏障形循环强化学习

Barrier-Shaped Recurrent Reinforcement Learning for Autonomous Landing on a Heaving Ship Deck

本文提出一种基于循环策略的非对称actor-critic强化学习方法，结合控制障碍函数停止裕度，实现无人机在起伏船甲板上的自主着陆，并通过模拟和真实试验验证了高成功率与低接触速度。