Informatics in Control, Automation and Robotics : 18th International Conference, ICINCO 2021 Lieusaint - Paris, France, July 6–8, 2021, Revised Selected Papers

The book focuses the latest endeavors relating researches and developments conducted in fields of control, robotics, and automation. Through more than ten revised and extended articles, the present book aims to provide the most up-to-date state of the art of the aforementioned fields allowing researcher, Ph.D. students, and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book. The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same book a factual and well-balanced prospect of nowadays research in those topics. A special attention toward “Intelligent Robots and Control” may characterize another benefit of this book. Preface Organization Contents Intelligent Control Systems and Optimization Approximation Methods and Reference Values for Maximum Allowed Collaborative Operating Speeds in Quasi-Static and Transient Contact Cases 1 Introduction 2 Theoretical Background 3 Materials and Method 3.1 Introduction 3.2 Quasi-Static Case 3.3 Transient Contact Case with Cobot Outer Geometry 4 Results 4.1 Quasi-Static Contact Case 4.2 Transient Contact Case with Cobot Outer Geometry 5 Conclusions and Discussion References Toward Real-Time Multi-objective Optimization for Bus Service KPIs 1 Introduction 2 Literature Review of KPIs 3 Control Method 3.1 General Control Method 3.2 Proposed Method 4 The KPIs Formulas 4.1 Punctuality Index 4.2 Regularity Index 4.3 Correspondence Index 5 Optimization Approach 5.1 Multi-objectives Optimization Resolution 5.2 Fuzzy Logic for Determination of Weighting Factors 5.3 Formulation of Constraints 6 Control System Modeling 6.1 Multi-agents Model 6.2 Inter-agent Message Exchange 7 Computational Results 7.1 Simulation Model 7.2 Scenario and Results 8 Conclusion and Future Work References Robotics and Automation A Two-Stage Trajectory Prediction Algorithm for Mobile Robots Combining the Bayesian and the DMOC Frameworks 1 Introduction 1.1 Related Works 1.2 Contributions 2 Intention Evaluation-Based Bayesian Path Waypoint Prediction 2.1 Intention Evaluation 2.2 Improved Probabilistic Dynamics Model 2.3 Bayesian Waypoint Prediction Framework 3 Trajectory Prediction Based on the DMOC Framework 3.1 DMOC Framework 3.2 Complementarity Constraints 3.3 Optimization Formulation 4 Experiments 4.1 Simulation Experiments 4.2 Hardware Experiment 5 Conclusion References Adaptive Neural Network Based Fractional Order Control of Unmanned Aerial Vehicle 1 Introduction 2 Preliminaries 3 Problem Formulation 4 Quadrotor Model 4.1 Quadrotor Dynamics 4.2 Error Model 5 Controller Design 5.1 Fractional Order Sliding Surface Design 5.2 Fractional Order Controller Design 6 Stability Analysis of Controller 6.1 Reaching Phase Stability 6.2 Sliding Phase Stability 7 Adaptive Neural Network Based Controller Design 7.1 Function Approximation 7.2 Tuning of Weights Using Optimality Conditions 7.3 Adaptive Neural Network Based Control Law 8 Simulation Results 8.1 Quadrotor Hovering 8.2 Circular and Spiral Shaped Trajectory Tracking 9 Conclusion and Future Scope References Design and Development of a Dexterous Teleoperation Setup for Nuclear Waste Remote Manipulation 1 Introduction 2 Bi-manual Teleoperation Platform 3 Dexterous Three Fingers Gripper 3.1 Design Rationales and Principles 3.2 Electro-mechanical Design 3.3 Kinematics 3.4 Manufacturing and Integration 4 Tri-Digital Dexterous Hand Master 4.1 Design Drivers 4.2 Electro-mechanical Design 4.3 Kinematics 4.4 Manufacturing and Integration 5 Bi-manual Teleoperation Controller 5.1 Detailed Presentation of the Bi-manual Teleoperation Set-Up 5.2 Master-Slave Coupling 5.3 Tri-Digital Master-Three Fingers Slave Hand Mapping 6 Bi-manual Teleoperation Tests and Validation 7 Conclusions and Perspectives References Pose Optimization of Task-Redundant Robots in Second-Order Rest-to-Rest Motion with Cascaded Dynamic Programming and Nullspace Projection 1 Introduction and State of the Art 1.1 State of the Art and Related Work 1.2 Summary of the State of the Art and Scenario of the Paper 1.3 Contribution of the Paper 2 Problem Description: Task Redundancy Optimization 2.1 Static Formulation of the Optimization Problem 2.2 Differential Formulation of the Optimization Problem 2.3 Hypothesis of the Paper: Decoupling of Problem Phases 3 Local Optimization: Second-Order Inverse Kinematics 3.1 Kinematics Model for Serial and Parallel Robots 3.2 Second-Order Nullspace Inverse Kinematics Controller Scheme 3.3 Performance Criteria for Gradient Projection 3.4 Extensions for Rest-to-Rest Motion 3.5 Trajectory Performance Criterion 4 Global Optimization: Dynamic Programming 4.1 Discrete Dynamic Programming 4.2 State-Interval Dynamic Programming 4.3 Overlapping Intervals 5 Simulative Validation for a Parallel Robot 6 Conclusion References Signal Processing, Sensors, Systems Modelling and Control Output Feedback Reference Tracking and Disturbance Rejection for Constrained Linear Systems Using Invariant Sets 1 Introduction 2 Invariant Sets 3 Disturbance Model for Constant Reference Tracking 4 Dynamic Output Feedback Controller 4.1 Linear State Estimator 4.2 Tracking Target Calculation 5 Tracking Controller Design 5.1 Control Action Calculation 5.2 Improved Tracking Performance 6 Numerical Example 7 Conclusions and Future Work References Output-Feedback Model Predictive Control Using Set of State Estimates 1 Introduction 2 Bayesian State Estimation of LSU Model 3 Control Design 4 Experiments 4.1 Robot Model 4.2 Experiment Setup 4.3 Search for the Best Point Estimate 4.4 Results and Discussion 5 Conclusion References Prediction of Overdispersed Count Data Using Real-Time Cluster-Based Discretization of Explanatory Variables 1 Introduction 1.1 Problem Formulation 2 General Solution with Cluster-Based Poisson Model 2.1 Cluster-Based Discretization of Explanatory Variables 2.2 Estimation of the Local Poisson Distributions on Clusters 2.3 Prediction with the Cluster-Based Poisson Model 3 Cluster-Based Models of Overdispersed Count Data 3.1 Cluster-Based Zero-Truncated Poisson Model 3.2 Cluster-Based Consul's Generalized Poisson Model 3.3 Cluster-Based Famoye's Generalized Poisson Model 3.4 Cluster-Based Rayleigh Model 3.5 Theoretical Counterparts 4 Experiments 4.1 Simulations 4.2 Results and Discussion 5 Conclusion References Model-Based Optimization of Vaccination Strategies in Different Phases of Pandemic Virus Spread 1 Introduction 2 Epidemic Model Considering Partially Ineffective Vaccines 3 Optimized Vaccination Strategies for Limited Amount of Vaccines 4 Simulation for Limited Amount of Vaccines 4.1 Uniform Vaccination Strategy 4.2 Optimized Vaccination Strategy 5 Epidemic Modeling for Reduced Motivation for Vaccination and New Virus Variants 6 Optimized Vaccination Strategies for New Virus Variants 7 Simulation for the Modified Model 7.1 Omicron as a Natural Vaccine 7.2 The Strategy of Mass Vaccination 7.3 New Vaccine Targeted to Omicron 7.4 New Treatments for Infected Patients 7.5 Optimized Vaccination Strategy 8 Conclusions References Author Index