0% Complete
Home
/
14th International Conference on Computer and Knowledge Engineering
Disturbance Rejection in Quadruple-Tank System by Proposing New Method in Reinforcement Learning
Authors :
Alireza Nezamzadeh
1
Mohammadreza Esmaeilidehkordi
2
1- Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan, 84156-83111, Iran
2- Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan, 84156-83111, Iran
Keywords :
Quadruple-tank system،Water level control،Classical Control،Reinforcement Learning،Actor-Critic Structure،Deep Deterministic Policy Gradient
Abstract :
This paper aims to propose a new method for reinforcement learning and compare it with a PID controller in the Quadruple-tank system in the presence of uncertainty. We use one of the popular structures called actor-critic and train it using a deep deterministic policy gradient algorithm. These methods are compared in terms of accuracy and rise time to show which one can have better performance if we consider uncertainty. The proposed method represents an approach by considering some changes in observation dimensions by a series of error items consisting of some previous and current errors and then training the Reinforcement Learning algorithm through these new observations. Finally, the results of these methods are compared by simulations and the proposed method's performance is evaluated. Which specifies our approach has better performance.
Papers List
List of archived papers
DIPT: Diversified Personalized Transformer for QAC systems
Mahdi Dehghani - Samira Vaez Barenji - Saeed Farzi
Optimizing Question-Answering Framework Through Integration of Text Summarization Model and Third-Generation Generative Pre-Trained Transformer
Ervin Gubin Moung - Toh Sin Tong - Maisarah Mohd Sufian - Valentino Liaw - Ali Farzamnia - Farashazillah Yahya
FGM Copula based Analysis of Coverage Region for Wireless Three-User Multiple Access Channel with Correlated Channel Coefficients
Mona Sadat Mohsenzadeh - Ghosheh Abed Hodtani
AVID: A VARIATIONAL INFERENCE DELIBERATION FOR META-LEARNING
Alireza Javaheri - Arsham Gholamzadeh Khoee - Saeed Reza Kheradpisheh - Hadi Farahani - Mohammad Ganjtabesh
A Chaotic Crow Search Algorithm for Overlapping Clustering
Mostafa Sabzekar - Seyed Vahid Mousavainejad
Semantic Segmentation Using Region Proposals and Weakly-Supervised Learning
Maryam Taghizadeh - Abdolah Chalechale
A Survey of the AVOA Metaheuristic Algorithm and its Suitability for Power System Optimization and Damping Controller Design
Aliyu Sabo - Theophilus Ebuka Odoh - Samuel Habu - Hossien Shahinzadeh - Farshad Ebrahimi
Averting Mode Collapse for Generative Zero-Shot Learning
Shayan Ramazi - Setare Shabani
Efficient Sub-Carrier Relationship Extraction for Human Activity Recognition via EEGNet in Wireless Sensing
Siavash Zaravashan - Sadegh ArefiZadeh - Sajjad Torabi
Improvement of CluStream Algorithm Using Sliding Window for the Clustering of Data Streams
Sahar Ahsani - Morteza Yousef Sanati - Muharram Mansoorizadeh
more
Samin Hamayesh - Version 41.3.1