
Informatics in Control, Automation and Robotics
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The goal of this book is to familiarize readers with the latest research on, and recent advances in, the field of Informatics in Control, Automation and Robotics. It gathers a selection of papers highlighting the state-of-the-art in Intelligent Control Systems, Optimization, Robotics and Automation, Signal Processing, Sensors, Systems Modelling and Control. Combining theoretical aspects with practical applications, the book offers a well-balanced overview of the latest achievements, and will provide researchers, engineers and PhD students with both a vital update and new inspirations for their own research.
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Content
- Intro
- Preface
- Organization
- Conference Chair
- Program Chair
- Program Committee
- Additional Reviewers
- Invited Speakers
- Contents
- Fast and Simple Interacting Models of Drape Tool and Ply Material for Handling Free Hanging, Pre-impregnated Carbon Fibre Material
- 1 Introduction
- 2 The FlexDraper Tool and Material
- 3 The Process and Model Requirements
- 4 Related Work
- 5 The Drape Tool Model
- 5.1 Kinetic Energy and Drape Tool Kinematics
- 5.2 Interlink Constraints
- 5.3 Actuator Movements
- 6 The Ply Material Model
- 6.1 Derivation of r
- 6.2 Derivation of rho
- 6.3 Derivation of gamma
- 7 Validation
- 7.1 Tool Model
- 7.2 Ply Model
- 8 Conclusions and Future Work
- References
- Optimal Time-Sampling in a Statistical Process Control with a Polynomial Expected Loss
- 1 Introduction
- 2 Problem Formulation
- 2.1 Process Monitoring Conditions
- 2.2 Variable Sampling Time-Interval
- 2.3 Polynomial Loss Model
- 3 Optimal Time-Sampling for a Known
- 3.1 Analytical Solution of the Extremal Problem
- 3.2 Numerical Solution of EP
- 3.3 Numerical Evaluation of the Optimal and Suboptimal Sampling Time-Intervals
- 4 Time-Sampling Independent of
- 4.1 Case 1=0
- 4.2 Case 1&0
- 4.3 Numerical Evaluation of the Time-Samplings i(z) and ii(z)
- 5 Conclusions
- References
- Observability for the Wave Equation with Variable Support in the Dirichlet and Neumann Cases
- 1 Introduction
- 1.1 Alternating Observation
- 1.2 One Dimensional Neumann Problem
- 2 The One Dimensional Problem
- 2.1 One Dimensional Neumann Problem
- 3 Applications - One Dimensional Case
- 4 Multidimensional Dirichlet Problem
- 4.1 The Role of {ti}i=-1,.,N.
- 5 Applications - Multidimensional Case
- 6 Numerical Simulations
- 7 Conclusions
- References
- Nonprehensile Manipulation Control and Task Planning for Deformable Object Manipulation: Results from the RoDyMan Project
- 1 Introduction
- 1.1 The RoDyMan Project
- 1.2 Literature Review
- 2 Robot Design
- 2.1 Mechatronic Design
- 2.2 Software Architecture
- 3 Manipulation Planning for Deformable Objects
- 3.1 Modelling of Deformable Objects
- 3.2 Detection of Deformable Objects
- 3.3 Task Planning to Stretch a Deformable Object by a Tool
- 4 Nonprehensile Manipulation: Planning and Control
- 4.1 Holonomic Rolling
- 4.2 Nonholonomic Rolling
- 4.3 Friction-Induced Manipulation
- 4.4 Tossing of a Deformable Object
- 5 Discussion and Future Work
- References
- Towards a Novel Maintenance Support System Based On mini-terms: Mini-term 4.0
- 1 Introduction
- 1.1 Previous Works. from Micro-term to Long-Term
- 1.2 Maintenance Support Systems and the Industry 4.0
- 1.3 Mini-term Degradation Path. A Change Point
- 2 What Kind of Pathology Produces the Change Point?
- 2.1 Welding Line at Ford Almussafes Factory
- 2.2 A Test Bench for a Welding Station
- 2.3 Pathologies Analyzed
- 2.4 Rules Definition Based on Statistical Analysis
- 3 How Does It Affect the Production Rate?
- 4 Mini-term 4.0. A New Paradigm for Failure Prognosis
- 4.1 Mini-term 4.0 Installation Setup
- 4.2 Towards a Real-Time mini-term Whatchdog for Failure Prognosis at Ford Motor Company
- 5 Conclusions and Future Works
- References
- Automated Nonlinear Control Structure Design by Domain of Attraction Maximization with Eigenvalue and Frequency Domain Specifications
- 1 Introduction
- 2 Background
- 2.1 Stability of Nonlinear Systems and the Domain of Attraction
- 2.2 Linear Systems and Sensitivity Analysis
- 2.3 Optimization by Grammatical Evolution
- 3 Methods
- 3.1 Centroids for Pole Placement
- 3.2 Frequency Response Magnitude Specifications
- 3.3 Optimization Problem and Domain of Attraction Estimation
- 4 Experiments
- 4.1 Optimization Setup
- 4.2 Inverted Pendulum
- 5 Conclusion
- References
- Computational Experience with a Modified Newton Solver for Discrete-Time Algebraic Riccati Equations
- 1 Introduction
- 2 Basic Theory and Conceptual Algorithm
- 3 Algorithmic Details
- 3.1 Computing Residual and Closed-Loop Matrices
- 3.2 Iterative Process
- 3.3 Finding the Step Size
- 3.4 Backtracking Strategy
- 4 Numerical Results
- 4.1 Pure Line Search, Identity Matrices Q and R
- 4.2 Backtracking, Identity Matrices Q and R
- 4.3 Pure Line Search, Diagonal Matrices Q and R
- 4.4 Backtracking, Diagonal Matrices Q and R
- 5 Conclusions
- References
- Influence of the Predictive Rainfall/Runoff Model Accuracy on an Optimal Water Resource Management Strategy
- 1 Introduction
- 2 Water Asset Management Strategy
- 2.1 Integrated Model
- 2.2 Flow-Based Network
- 2.3 Optimal Allocation Planning
- 3 Predictive Rainfall/Runoff Models
- 3.1 State of the Art
- 3.2 Data-Driven ARX Models for Flood Forecasting
- 3.3 Example of Prediction Results
- 4 Case Study
- 4.1 Description
- 4.2 Design of the Optimal Water Allocation Strategy
- 4.3 Water Allocation Planning
- 5 Conclusions
- References
- Interlocking Problem in Automatic Disassembly Planning and Two Solutions
- Abstract
- 1 Introduction
- 2 Contact and Relation Matrices: Fundamental Tools
- 3 Separability Check
- 3.1 Definition of Separability
- 3.2 Separable Pairs Search Process
- 4 Set and Closure: Mathematical Representation
- 4.1 Set
- 4.2 Subassembly and Closure
- 5 Divide-and-Conquer Disassembly Strategy
- 5.1 Subassembly Search Process
- 5.2 Procedure of Divide-and-Conquer Strategy
- 6 Case Study
- 6.1 'Separable Pairs' Method
- 6.2 Divide-and-Conquer Strategy
- 7 Conclusion
- Acknowledgement
- Appendix
- References
- Thermal Imaging for Psychophysiological State Detection in the Human-Machine Interface (HMI) Control System
- 1 Introduction
- 1.1 Participants
- 1.2 Simulation of Human-Machine Interaction
- 1.3 Data Acquisition
- 1.4 Data Analysis
- 1.5 Procedure
- 2 Results
- 2.1 Maximum Facial Temperature
- 2.2 Mean Nasal Temperature
- 2.3 Mean Forehead Temperature
- 2.4 Differential Energy Between Philtrum and Forehead
- 2.5 Comparison with Conventional Biomarker
- 3 Discussions
- 3.1 Facial Temperature Biomarkers
- 3.2 Human-Machine Interface Prediction
- 4 Conclusions
- References
- Nonlinear Model Predictive Control Algorithms for Industrial Articulated Robots
- 1 Introduction
- 2 Nonlinear Robot Model
- 3 Integration Concept
- 4 Nonlinear Design of Model Predictive Control
- 4.1 Criterion and Cost Function
- 4.2 Equations of Predictions - Algorithm with Nonlinear Prediction
- 4.3 Equations of Predictions - Single-Pass Algorithm
- 4.4 Square-Root Minimization
- 5 Simulation Examples
- 5.1 Simulation Setup
- 5.2 Summary of the Results
- 6 Conclusion
- References
- Experimental Investigation of a Biologically Inspired Gripper with Active Haptic Control for Geometric Compliancy
- Abstract
- 1 Introduction
- 1.1 Background
- 1.2 Overview
- 1.3 Related Studies
- 1.4 Fin Ray Effect® Mechanism and Related Studies
- 2 Conceptual Design of Flexible Gripper
- 2.1 Closed-Loop Robotic System Integration
- 2.2 Design of Flexible Gripper
- 2.3 Simulation for Optimal Conformity
- 2.4 Robot Sensory System Integration
- 3 Active Haptic Control
- 3.1 Pseudocode and Mechatronic Control
- 3.2 Dynamic Interferences Forces
- 4 Testing of Active Haptic Control
- 4.1 Visual Static Testing
- 4.2 Dynamic Testing Preparation
- 4.3 Dynamic Performance Without Haptic Feedback Control
- 4.4 Dynamic Performance of Haptic Feedback Control
- 5 Discussion
- 5.1 Gripper Performance
- 6 Conclusions
- References
- Quantifying Robotic Swarm Coverage
- 1 Introduction
- 2 Quantifying Coverage
- 2.1 Preliminaries
- 2.2 Calculating eN
- 2.3 The Pitfalls of Discretization
- 2.4 Setup for Main Examples
- 3 Error Metric Extrema
- 3.1 Extrema Bounds via Nonlinear Programming
- 3.2 Error Metric for Optimal Swarm Design
- 4 Error Metric Probability Density Function
- 4.1 Kernel Density Estimation
- 4.2 Theoretical Central Limit Theorem
- 4.3 Numerical Approximation of the Error Metric PDF
- 4.4 Benchmark for Stochastic Controllers
- 5 Future Work
- 6 Conclusion
- References
- Design of a Vibration Driven Motion System Based on a Multistable Tensegrity Structure
- 1 Introduction
- 2 Mechanical Model of the Tensegrity Structure
- 2.1 Topology of the Tensegrity Structure
- 2.2 Equations of Motion and Equilibrium Configurations of the Tensegrity Structure
- 3 Parameter Finding for the Tensegrity Structure
- 3.1 Multistability of the Tensegrity Structure
- 3.2 Tilting by Changing the Equilibrium Configuration
- 4 Design of the Actuation of the Tensegrity Structure
- 4.1 Modal Analysis of the Tensegrity Structure
- 4.2 Frequency Response Analysis of the Tensegrity Structure
- 5 Simulation of the Vibration Driven Motion System
- 5.1 Modeling of the Vibration Driven Motion System
- 5.2 Motion Characteristics of the Vibration Driven Motion System
- 5.3 Change of the Equilibrium Configuration of the Vibration Driven Motion System
- 6 Conclusion
- References
- An Experimental Study for the Contactless Manipulation of Single Object in Vertical Plane Using Multiple Air Jets
- Abstract
- 1 Introduction
- 2 Outline and Problem Setting of Proposed Technology
- 2.1 Basic Idea and Conveyance Image
- 2.2 An Essential Problem to Be Solved
- 3 Preliminary Experiments to Propose the Air Jet Relay Control Method
- 3.1 Consideration of Air Jet Manipulation Experiment on a Flat Surface
- 3.2 Observation of the Behavior of an Object When Two Air Jets Join in the Air
- 4 Proposed Control Method
- 4.1 Approach to Problem Solving
- 4.2 Proposed Algorithm
- 5 Demonstration Experiment
- 5.1 Outline of Experiment
- 5.2 Experimental Results and Discussion
- 6 Conclusion
- References
- Combined Feedback-Feed Forward Control Strategy for a Knee Rehabilitation Device with Soft Actuation
- 1 Introduction
- 2 Device Modeling Approach
- 3 Combined Feedback and Feedforward Control Strategy
- 3.1 Control Requirements
- 3.2 Control Design
- 3.3 Controller Simulation
- 4 Results and Discussion
- 4.1 Simulation Results
- 4.2 Experimental Results
- 5 Conclusion
- References
- Controlling Off-Road Bi-steerable Mobile Robots: An Adaptive Multi-control Laws Strategy
- 1 Introduction
- 2 Modeling of the Robot
- 2.1 Assumptions and Notations
- 2.2 Classical Motion Equations
- 2.3 Modeling Robot Motion in Two Subsystems
- 3 Observation of Sideslip Angles
- 3.1 Observer State
- 3.2 Observer Equations
- 4 Control Laws
- 4.1 Rear Steering Angle
- 4.2 Front Steering Angle
- 4.3 Curvature Anticipation
- 5 Prevention of Steering Angle Saturations
- 6 Experimental Results
- 6.1 Experimental Setup
- 6.2 Maneuverability Improvement and Tracking Accuracy
- 6.3 Prevention of Steering Saturation
- 7 Conclusion
- References
- On Randomized Searching for Multi-robot Coordination
- 1 Introduction
- 2 Problem Definition
- 2.1 Actions
- 2.2 Constraints
- 2.3 Composite Configuration Space
- 3 Proposed Algorithm
- 3.1 Discrete RRT
- 3.2 Proposed Improvements
- 4 Experiments
- 5 Conclusion
- References
- Increasing Machining Accuracy of Industrial Manipulators Using Reduced Elastostatic Model
- 1 Introduction
- 1.1 Related Work
- 1.2 Problem Statement
- 2 Theoretical Background
- 2.1 Virtual Joint Method
- 2.2 Identification
- 2.3 Design of Experiment
- 3 Model Description
- 3.1 Stiffness Estimation
- 3.2 Deflection Maps
- 4 Results
- 4.1 Deflection Maps
- 4.2 Deflection Compensation
- 5 Discussion
- 6 Conclusion
- References
- Control of Force in Surgical Robots with Random Time Delays Using Model Predictive Control
- Abstract
- 1 Introduction
- 2 System's Control Architecture
- 2.1 Communication System
- 2.2 Master Level
- 2.3 Slave Model
- 3 Simulations Results
- 4 Discussions
- 5 Future Work
- 6 Conclusion
- References
- An IPM Approach to Multi-robot Cooperative Localization: Pepper Humanoid and Wheeled Robots in a Shared Space
- 1 Introduction
- 2 Methodology
- 2.1 Problem Definition
- 2.2 Inverse Perspective Mapping (IPM)
- 2.3 Detection Phase
- 3 Results and Discussion
- 3.1 Tests with Static Objects
- 3.2 Tests with Wheeled Robots
- 4 Conclusion
- References
- Study of the Physiological Parameters of a Regulated Oxygen Mask
- 1 Introduction
- 2 Conclusions from Previous Work
- 2.1 Physical Model of the Mask
- 2.2 Equilibrium Trajectory of the Mask
- 2.3 Results from the Appplication of the Routh Criterion
- 3 Study of the Mask Physiological Parameters
- 3.1 Opening Time
- 3.2 Closing Time
- 3.3 Mask Pressure Value
- 3.4 Mask Pressure Overshoot
- 4 Improvement of the Mask Behaviour
- 5 Conclusion
- References
- Linear Discrete-Time Systems - H Dynamic Output-Feedback Control with Preview
- 1 Introduction
- 2 Problem Formulation
- 3 State-Feedback Tracking Control
- 3.1 Stationary State-Feedback Tracking Control
- 4 Dynamic Output-Feedback Tracking Control
- 4.1 BRL for Systems with Tracking Signal
- 4.2 The Output-Feedback Tracking Control
- 5 Stationary Output-Feedback Tracking Control
- 6 Conclusions
- References
- Direct Integrability for State Feedback Optimal Control with Singular Solutions
- 1 Introduction
- 2 The Optimal Control Problem Formulation
- 3 The Case of Block Sub Triangular Single Input Systems
- 3.1 The Class of Dynamics Considered
- 3.2 Results for the Class of Dynamics Considered
- 3.3 The Example of a SIR Model
- 4 An Extended Case
- 4.1 The Example of a SIR Model with No Immunization
- 5 Conclusions
- References
- Petri Nets Tracking Control for Electro-pneumatic Systems Automation
- 1 Introduction
- 2 Basic Concepts
- 2.1 Petri Nets
- 2.2 Interpreted Petri Nets
- 3 Tracking Control Problem
- 3.1 Electro-Pneumatic Component Models
- 3.2 Building the Plant Model
- 3.3 Specification Model
- 3.4 Tracking Control Problem
- 4 Control Synthesis Algorithm
- 4.1 Properties of the Closed-Loop System
- 4.2 Ladder Diagram
- 5 Case Study
- 6 Conclusions
- References
- 18O Isotope Separation Process Control
- Abstract
- 1 Introduction
- 2 Modeling of the Isotope Separation Process
- 3 The Proposed Control Strategy
- 4 Controllers Tuning and Simulations Results
- 5 Conclusions
- References
- Approximate Bayesian Prediction Using State Space Model with Uniform Noise
- 1 Introduction
- 2 Multidimensional Uniform Distribution and Geometrical Interpretation of its Support
- 2.1 Definition of Uniform Pdf
- 2.2 Examples of Supports
- 2.3 Approximation of a Complex Pdf by a Uniform Pdf with a Parallelotopic Support
- 3 Approximate Bayesian Estimation of Uniform State Space Model
- 3.1 Bayesian Filtering
- 3.2 Linear State Space Model with Uniform Noise
- 3.3 Approximate State Estimation of LSU Model
- 4 Approximate Predictor for Scalar Output and -dimensional State
- 4.1 Predictive Pdf
- 4.2 Point Prediction
- 5 Algorithmic Summary
- 6 Experiments
- 6.1 Experiment Setup
- 6.2 Results
- 6.3 Discussion
- 7 Concluding Remarks
- References
- Author Index
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