Time Series Predictive Control in Robotics
Published on 21. May 2024
230 pages
978-2-7598-3510-2 (ISBN)
Description
No detailed description available for "Time Series Predictive Control in Robotics".
More details
Series
Edition
Digital original
Language
English
Place of publication
Les Ulis
France
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
23,06 MB
ISBN-13
978-2-7598-3510-2 (9782759835102)
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Schweitzer Classification
Person
LIU Hui:
Hui LIU is Professor and Vice dean of the School of Traffic & Transportation Engineering, Central South University, China. His main research interests include computational intelligence, intelligent robotics in traffic & transportation engineering, and nonlinear signal modeling & forecasting. He holds double Ph.D degrees from China (Traffic & Transportation Engineering, from Central South University in 2011) and Germany (Automation Engineering, from University of Rostock in 2013), and obtained his professorship degree in Automation Engineering from University of Rostock in 2016. He has published more than 100 international research papers and authorized beyond 100 invention patents in the field of robotics, data science, and time series predictive control, as the first inventor.
Hui LIU is Professor and Vice dean of the School of Traffic & Transportation Engineering, Central South University, China. His main research interests include computational intelligence, intelligent robotics in traffic & transportation engineering, and nonlinear signal modeling & forecasting. He holds double Ph.D degrees from China (Traffic & Transportation Engineering, from Central South University in 2011) and Germany (Automation Engineering, from University of Rostock in 2013), and obtained his professorship degree in Automation Engineering from University of Rostock in 2016. He has published more than 100 international research papers and authorized beyond 100 invention patents in the field of robotics, data science, and time series predictive control, as the first inventor.
Content
- Intro
- Time Series Predictive Control in Robotics
- Preface
- Abbreviations
- Contents
- Introduction
- Robotics and Control Technology
- Robotics
- Robotics Control Technology
- Time Series Forecasting in Robotics Control
- Time Series Forecasting Objectives
- Time Series Forecasting Methods
- Predictive Control in Robotics
- Uncertainty Problems in Predictive Control of Robotics
- Model Predictive Control
- Significance and Purpose of Research
- Scope of This Book
- References
- Robot Navigation Position Time Series Predictive Control
- Introduction
- Robot Navigation Position Time Series Measurement
- Robot Navigation Position Time Series Uncertainty Analysis
- Robot Navigation Position Time Series Statistical Forecasting Method
- ARIMA Forecasting Algorithm
- ARIMA-GARCH Forecasting Algorithm
- Robot Navigation Position Time Series Intelligent Forecasting Method
- RBF Neural Network Forecasting Algorithm
- Elman Neural Network Forecasting Algorithm
- Extreme Learning Machine Forecasting Algorithm
- Robot Navigation Position Time Series Deep Learning Forecasting Method
- LSTM Deep Neural Network Forecasting Algorithm
- ESN Deep Neural Network Forecasting Algorithm
- Comparative Analysis of Forecasting Performance
- Robot Anti-Collision Monitoring and Control Based on Navigation Position Forecasting
- Conclusions
- References
- Mobile Robot Power Time Series Predictive Control
- Introduction
- Mobile Robot Power Time Series Measurement
- Mobile Robot Power Time Series Uncertainty Analysis
- Mobile Robot Power Time Series Statistical Forecasting Method
- Experimental Design
- Modeling Steps
- Forecasting Results
- Mobile Robot Power Time Series Intelligent Forecasting Method
- Experimental Design
- Modeling Steps
- Forecasting Results
- Mobile Robot Power Time Series Deep Learning Forecasting Method
- Experimental Design
- Modeling Steps
- Forecasting Results
- Comparative Analysis of Forecasting Performance
- Analysis of Statistical Methods
- Analysis of Intelligent Methods
- Analysis of Deep Learning Methods
- Mobile Robot Delivery Process Control Based on Power Forecasting
- Conclusions
- References
- Robot Arm Time Series Predictive Control
- Introduction
- Robot Arm Time Series Measurement
- Robot Arm Time Series Uncertainty Analysis
- Robot Arm Time Series Statistical Forecasting Method
- Pandit-Wu Forecasting Algorithm
- KF-ARMA Forecasting Algorithm
- Robot Arm Time Series Intelligent Forecasting Method
- RELM Forecasting Algorithm
- XGBoost Forecasting Algorithm
- GRNN Forecasting Algorithm
- Robot Arm Time-Series Deep Learning Forecasting Method
- Autoencoder Deep Neural Network Forecasting Algorithm
- Deep Belief Network Forecasting Algorithm
- Comparative Analysis of Forecasting Performance
- Analysis of Statistical Methods
- Analysis of Intelligent Methods
- Analysis of Deep Learning Methods
- Robot Arm Positioning Control Based on Arm Forecasting
- Conclusions
- References
- Unmanned Vehicle Time Series Predictive Control
- Introduction
- Unmanned Vehicle Time Series Measurement
- Unmanned Vehicle Time Series Uncertainty Analysis
- Unmanned Vehicle Time Series Statistical Forecasting Method
- Kalman Filter Forecasting Algorithm
- Fuzzy Time Series Forecasting Algorithm
- Unmanned Vehicle Time Series Intelligent Forecasting Method
- Elman Neural Network Forecasting Algorithm
- NAR Neural Network Forecasting Algorithm
- ANFIS Neural Network Forecasting Algorithm
- Unmanned Vehicle Time Series Deep Learning Forecasting Method
- RNN Deep Neural Network Forecasting Algorithm
- LSTM Deep Neural Network Forecasting Algorithm
- GRU Deep Neural Network Forecasting Algorithm
- Comparative Analysis of Forecasting Performance
- Analysis of Statistical Methods
- Analysis of Intelligent Methods
- Analysis of Deep Learning Methods
- Unmanned Vehicle Navigation Control Based on Multi-Source Position Time Series Fusion
- Unmanned Vehicle Fusion Positioning
- Unmanned Vehicle Navigation Control
- Unmanned Vehicle Charging Control Based on Multi-Source Power Time Series Fusion
- Conclusions
- References
- Wearable Assistive Robot Time Series Predictive Control
- Introduction
- Wearable Assistive Robot Time Series Measurement
- Wearable Assistive Robot Time Series Uncertainty Analysis
- Wearable Assistive Robot Time Series Statistical Forecasting Method
- Experimental Design
- Modeling Step
- Forecasting Results
- Wearable Assistive Robot Time Series Intelligent Forecasting Method
- Experimental Design
- Modeling Step
- Forecasting Results
- Wearable Assistive Robot Time-Series Deep Learning Forecasting Method
- Experimental Design
- Modeling Step
- Forecasting Results
- Comparative Analysis of Forecasting Performance
- Wearable Assistive Robot Motion Control Based on Forecasting
- Conclusions
- References
- Intelligent Manufacturing Performance Prediction and Application
- Introduction
- Data Acquisition
- Data-Driven Method
- Model-Driven Method
- Prediction Modeling
- Regression Algorithms
- Artificial Neural Network (ANN)
- Comparison Analysis
- Application
- System Configuration
- The Other Application
- Conclusions
- References
