Deep Reinforcement Learning based Super Twisting Controller for Liquid Slosh Control Problem

Author:

Shakya Ashish Kumar,Bithel Kshitij,Pillai G.N.,Chakrabarty Sohom

Publisher

Elsevier BV

Subject

Control and Systems Engineering

Reference30 articles.

1. Abramson, H.N. (1966). The dynamic behaviour of liquids in moving containers with applications to space vehicle technology, National Aeronautics and Space Administration Tech. Rep. NASA, Washington, D.C. USA, SP-106.

2. Sliding mode control for slosh-free motion-A class of underactuated system;Bandyopadhyay;International Journal of Advanced Mechatronic Systems,2009

3. Sliding mode observer based sliding mode controller for slosh-free motion through PID scheme;Bandyopadhyay;IEEE Transactions on Industrial Electronics,2009

4. Modeling and coupling dynamics of the spacecraft with multiple propellant tanks;Baozeng;AIAA,2016

5. De Souza, A.G. and De Souza, L.C.G. (2014). Satellite Attitude Control System Design Taking into Account the Fuel Slosh and Flexible Dynamics, Mathematical Problems in Engineering, 2014, 1–8.

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1. Control of chaotic systems through reservoir computing;Chaos: An Interdisciplinary Journal of Nonlinear Science;2023-12-01

2. Learning Based Adaptation of Proportional Derivative Controller for a Novel Rotary Slosh Dynamics Model;2023 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE);2023-11-08

3. Data-efficient deep reinforcement learning with expert demonstration for active flow control;Physics of Fluids;2022-11

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