Madani / Peaucelle / Gusikhin Informatics in Control, Automation and Robotics

13th International Conference, ICINCO 2016 Lisbon, Portugal, 29-31 July, 2016
1. Auflage 2018
ISBN: 978-3-319-55011-4
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 430, 455 Seiten

Reihe: Lecture Notes in Electrical Engineering

The book addresses the latest advances in research and development in the field of informatics in control, robotics and automation. With more than twenty revised and extended articles covering the theoretical aspects as well as applications and their implementation, it offers a factual and well-balanced overview of the state of the art in the field. In addition, it highlights the trends in control of intelligent robots. The book is an up-to-date source of information and inspiration for researchers, engineers and PhD students.

Autoren/Hrsg.

Madani, Kurosh

Peaucelle, Dimitri

Gusikhin, Oleg

Inhaltsverzeichnis

1;Preface;6
2;Organizing Committee;8
3;Contents;16
4;Intelligent Control Systems and Optimization;19
5;A Method for the Energy Optimization of a Multisource Elevator;20
5.1;1 Introduction;21
5.2;2 Formal Description of the Sourcing Problem;21
5.3;3 Related Work;24
5.4;4 Coupled Optimizer and Controller to Handle Different Time Scales;25
5.4.1;4.1 Data and Interactions;26
5.4.2;4.2 Strategic Optimizer;28
5.4.3;4.3 Local Controller;33
5.5;5 Results;36
5.5.1;5.1 A Typical Strategy;36
5.5.2;5.2 Strategic Controller Error Induced by Aggregating Periods;37
5.5.3;5.3 Local Controller Parametrizations;40
5.5.4;5.4 Interaction with an Aggregator, a Demand-Response Market Simulation;42
5.6;6 Conclusions;45
5.7;References;46
6;Visual Servoing Path-Planning with Elliptical Projections;47
6.1;1 Introduction;47
6.2;2 Background;49
6.2.1;2.1 Camera Frame;49
6.2.2;2.2 Elliptical Projections;50
6.2.3;2.3 Image Moments;51
6.3;3 Pose Estimation from Image Moments;52
6.4;4 Polynomial Minimization;54
6.4.1;4.1 Path Parametrization and Polynomial Model;54
6.4.2;4.2 Constraints and Limitations;57
6.4.3;4.3 Tracking the Planned Elliptical Projections;63
6.5;5 Evaluation Examples;64
6.5.1;5.1 Following a Straight Line with Two Circles;64
6.5.2;5.2 Occlusion Avoidance Among Three Spheres;67
6.6;6 Conclusions;70
6.7;References;70
7;Fractional Models of Lithium-Ion Batteries with Application to State of Charge and Ageing Estimation;72
7.1;1 Introduction;72
7.2;2 Electrochemical Model Considered;73
7.3;3 From the Electrochemical Model to a Fractional Dynamic Model;76
7.4;4 Parameters Estimation;77
7.4.1;4.1 Open Circuit Voltage Law Identification;78
7.4.2;4.2 Estimation of Parameter K2;78
7.4.3;4.3 Estimation of Parameter K1;79
7.4.4;4.4 Identification of Parameter c;80
7.5;5 Model Validation;80
7.6;6 State-of-Charge Estimation;81
7.7;7 Aging Monitoring Through Open Circuit Voltage (OCV) Curve Modelling and Adjustment;84
7.8;8 Model Parameter Adjustment as Ageing;85
7.9;9 Conclusion;87
7.10;References;87
8;Co-operation of Biology Related Algorithms for Solving Opinion Mining Problems by Using Different Term Weighting Schemes;90
8.1;1 Introduction;90
8.2;2 Co-Operation of Biology Related Algorithms;91
8.3;3 Data Mining Tools with Co-Operation of Biology Related Algorithms;94
8.3.1;3.1 Artificial Neural Networks;94
8.3.2;3.2 Support Vector Machines;95
8.3.3;3.3 Fuzzy Rule-Based Classifiers;95
8.4;4 Term Relevance Estimation;97
8.5;5 Experimental Results;98
8.6;6 Conclusions;105
8.7;References;106
9;Bifurcation Analysis and Active Control of Surge and Rotating Stall in Axial Flow Compressors via Passivity;108
9.1;1 Introduction;109
9.2;2 Axial Compressors Models;111
9.2.1;2.1 MG3 for CSACs;111
9.2.2;2.2 Surge and Rotating Stall Simulation;115
9.2.3;2.3 Bifurcation Analysis of MG3;116
9.2.4;2.4 MG3 Model Including CCV;119
9.3;3 Passivity-Based Control;122
9.4;4 PBC Design for MG3;124
9.5;5 Results and Discussion;126
9.6;6 Conclusion;131
9.7;References;131
10;Task Controller for Performing Remote Centre of Motion;134
10.1;1 Introduction;134
10.2;2 Control Design;136
10.2.1;2.1 Remote Center of Motion Constraints;136
10.2.2;2.2 3D Path Following;140
10.3;3 Validation;142
10.3.1;3.1 Implementation;142
10.3.2;3.2 Results;144
10.4;4 Conclusion;146
10.5;References;148
11;Toward an Automatic Fongbe Speech Recognition System: Hierarchical Mixtures of Algorithms for Phoneme Recognition;150
11.1;1 Introduction;150
11.2;2 Overview of the Proposed System;151
11.3;3 Speech Data;151
11.4;4 Continuous Speech Segmentation;153
11.5;5 Classification of the Detected Phonemes;157
11.6;6 Recognition of the Classified Phonemes;158
11.6.1;6.1 Formant Analysis of Vowels;159
11.6.2;6.2 Fongbe Consonant System;160
11.6.3;6.3 Baseline Phoneme Recognition System;162
11.7;7 Experiments Results;163
11.8;8 Conclusion;165
11.9;References;165
12;Robotics and Automation;167
13;Spatial Fusion of Different Imaging Technologies Using a Virtual Multimodal Camera;168
13.1;1 Introduction;168
13.2;2 Related Work;170
13.3;3 Notation;172
13.4;4 Virtual Multimodal Camera;173
13.4.1;4.1 Preprocessing;174
13.4.2;4.2 Intermodal Calibration;175
13.4.3;4.3 Time Synchronization;177
13.4.4;4.4 Mapping;178
13.4.5;4.5 Reprojection;178
13.5;5 Parallelization;179
13.6;6 Experiments;180
13.6.1;6.1 Experimental Setup;180
13.6.2;6.2 Intrinsic and Extrinsic Calibration;181
13.7;7 Results;181
13.7.1;7.1 Calibration;182
13.7.2;7.2 Processing Time;183
13.7.3;7.3 Virtual Multimodal Camera;184
13.7.4;7.4 Limitations;185
13.8;8 Conclusion and Further Work;187
13.9;References;187
14;Fusing LiDAR and Radar Data to Perform SLAM in Harsh Environments;190
14.1;1 Introduction;190
14.2;2 Methods;191
14.2.1;2.1 The MPR - A 2D FMCW Radar Scanner;191
14.2.2;2.2 Comparing the MPR;193
14.2.3;2.3 SLAM Based on Features with LiDAR and Radar;194
14.2.4;2.4 SLAM Based on Scan Registration;197
14.3;3 Experiments;199
14.4;4 Results and Discussion;200
14.5;5 Conclusion;202
14.6;References;203
15;On Redundancy Resolution in Minimum-Time Trajectory Planning of Robotic Manipulators Along Predefined End-Effector Paths;205
15.1;1 Introduction;205
15.2;2 Problem Description;206
15.2.1;2.1 Kinematically Redundant Manipulators;206
15.2.2;2.2 Optimal Trajectory Planning for Prescribed End-Effector Paths;207
15.3;3 Path Following;208
15.3.1;3.1 Differential Inverse Kinematics;208
15.3.2;3.2 Optimal Nullspace Basis Scaling;210
15.3.3;3.3 Joint Space Decomposition;211
15.4;4 Example;212
15.4.1;4.1 Kinematic and Dynamic Model;212
15.4.2;4.2 Error Stabilization, Jacobian Regularization;213
15.4.3;4.3 Task;214
15.4.4;4.4 Direct Multiple Shooting Trajectory Optimization;214
15.4.5;4.5 Results;217
15.5;5 Conclusion;220
15.6;References;220
16;Parameter Identification and Model-Based Control of Redundantly Actuated, Non-holonomic, Omnidirectional Vehicles;222
16.1;1 Introduction;222
16.2;2 Platform Kinematics;224
16.3;3 Dynamic Modeling;226
16.3.1;3.1 Redundantly Parametrized Equations of Motion;226
16.3.2;3.2 Elimination of Constraint Forces;228
16.4;4 Model-Based Control;231
16.4.1;4.1 Inverse Dynamics and Redundancy Resolution;231
16.4.2;4.2 Augmented PD-Control;232
16.5;5 Parameter Identification;233
16.5.1;5.1 Parameter Specification and Model Reformulation;234
16.5.2;5.2 Base Parameters and Trajectory Optimization;235
16.5.3;5.3 Estimation Experiment;236
16.6;6 Experimental Results;239
16.7;7 Summary and Outlook;242
16.8;References;243
17;Passivity-Based Control Design and Experiments for a Rolling-Balancing System;245
17.1;1 Introduction;245
17.2;2 Port-Hamiltonian Systems;247
17.2.1;2.1 Hamiltonian Models;247
17.2.2;2.2 Energy Shaping and Damping Assignment;247
17.3;3 Control Design for the Disk-on-Disk;248
17.3.1;3.1 Dynamic Model;248
17.3.2;3.2 Energy Shaping and Damping Assignment Control;250
17.3.3;3.3 Effect of Input Disturbances;252
17.3.4;3.4 Robust Energy Shaping;252
17.4;4 Simulations and Experiments;255
17.4.1;4.1 Standard IDA-PBC;256
17.4.2;4.2 IDA-PBC Plus IA;257
17.4.3;4.3 IDA-PBC Plus NLPI;258
17.4.4;4.4 IDA-PBC Plus NLPID1;260
17.4.5;4.5 IDA-PBC Plus NLPID2;261
17.4.6;4.6 Tracking Angle Ramp References for the Disk 1;263
17.4.7;4.7 Discussion;265
17.5;5 Conclusion;268
17.6;References;269
18;Time-Optimal Paths for a Robotic Batting Task;271
18.1;1 Introduction;271
18.1.1;1.1 Overview and Outline of the Paper;272
18.2;2 State of the Art About the Robotic Batting Primitive;273
18.3;3 Hybrid Dynamic Equations of the System;274
18.4;4 Time-Optimal Prediction;276
18.4.1;4.1 Workflow of the Algorithm;276
18.4.2;4.2 Stage 1: Prediction of the Impacting Time, Position and Velocities of the Ball;278
18.4.3;4.3 Stage 2: Desired Configuration of the Paddle at Impact;280
18.5;5 Minimum Acceleration Path in SE(3);280
18.5.1;5.1 Brief Background About Differential Geometry;281
18.5.2;5.2 Optimized Path Planning in SE(3);282
18.6;6 Simulations;283
18.6.1;6.1 Evaluation of the Batting Motion Planner with a Predefined Impact Time;284
18.6.2;6.2 Evaluation of the Optimal Impact Time Prediction;285
18.6.3;6.3 Discussion on the Minimum Acceleration Planner;288
18.7;7 Conclusions and Future Work;288
18.8;References;289
19;An Adaptive Terminal Sliding Mode Guidance Law for Head Pursuit Interception with Impact Angle Considered;292
19.1;1 Introduction;292
19.2;2 Related Work;293
19.3;3 Overview of Head Pursuit Interception;295
19.3.1;3.1 Head Pursuit Interception Principles;295
19.3.2;3.2 Hp Kinematic Equation;296
19.4;4 The Stage of Approach;298
19.4.1;4.1 Dynamics;298
19.4.2;4.2 Sliding Mode Surface Design;298
19.4.3;4.3 Guidance Law Design;299
19.4.4;4.4 Stability Proof;300
19.5;5 Numerical Simulations and Their Analysis;301
19.6;6 Conclusions;305
19.7;References;306
20;Kinematic and Dynamic Approaches in Gait Optimization for Humanoid Robot Locomotion;308
20.1;1 Introduction;308
20.2;2 Problem Statement;310
20.3;3 Kinematic Approach;311
20.3.1;3.1 Dynamic Programming Method for Swing Leg Trajectory Optimization;311
20.3.2;3.2 Trapezoidal Angular Velocity Profile Method;322
20.4;4 Dynamic Approach;324
20.4.1;4.1 Walking Gait Parametrization;325
20.4.2;4.2 Inverse Kinematics;326
20.4.3;4.3 Inverse Dynamics;326
20.4.4;4.4 Motion Stability;327
20.4.5;4.5 Gait Optimization;327
20.4.6;4.6 Optimization Results;328
20.5;5 Conclusions;331
20.6;References;332
21;Signal Processing, Sensors, Systems Modelling and Control;336
22;Identification and Control of the Waelz Process Using Infrared Image Processing;337
22.1;1 Introduction;337
22.2;2 Camera Based Temperature Measurement;339
22.3;3 Image Processing;340
22.4;4 Camera Based Process Identification;343
22.4.1;4.1 Model Structure;344
22.4.2;4.2 Parameter Estimation;346
22.4.3;4.3 Model Validation;348
22.5;5 Camera Based Slag Temperature Control;349
22.5.1;5.1 Model Based Controller Design;349
22.5.2;5.2 Controller Parameter Optimization;351
22.5.3;5.3 Industrial Controller Validation;354
22.6;6 Conclusion;354
22.7;References;355
23;Modeling and Calibrating Triangulation Lidars for Indoor Applications;356
23.1;1 Introduction;356
23.2;2 Triangulation Lidar Range Sensors;359
23.3;3 Modelling the Lidar Measurements Under the Hypothesis of Flat and Perpendicularly Aligned Obstacles;360
23.3.1;3.1 Motivating the Nonlinear term f() in Model (1);361
23.3.2;3.2 Motivating the Multiplicative Term f(dk)2 in Model (1);362
23.3.3;3.3 Calibrating Model (1);363
23.3.4;3.4 An Approximate Procedure for Calibrating Model (1);364
23.3.5;3.5 Using the Calibrated Model (1) to Estimate dk;365
23.4;4 Extending Model (1) to Account for Non-null Incident Angles Effects;366
23.4.1;4.1 Verifying if the Sensor Measurement Process Is Influenced by Incidence Angle Effects;366
23.4.2;4.2 Extending Model (1);367
23.4.3;4.3 Training Model (23);368
23.4.4;4.4 Testing Model (23);370
23.5;5 Numerical Experiments;373
23.5.1;5.1 Calibration and Testing Under Null Incidence Angles Hypotheses;373
23.5.2;5.2 Calibration and Testing Under No Hypotheses on the Incidence Angles;374
23.6;6 Conclusions;377
23.7;References;378
24;A Comparison of Discretization Methods for Parameter Estimation of Nonlinear Mechanical Systems Using Extended Kalman Filter: Symplectic versus Classical Approaches;381
24.1;1 Introduction;381
24.2;2 Methods;383
24.2.1;2.1 Extended Kalman Filter;383
24.2.2;2.2 Discretization Methods;384
24.3;3 Testbed and Modeling;386
24.4;4 Results;390
24.4.1;4.1 Comparison of Continuous- and Discrete-Time Model;390
24.4.2;4.2 Parameter Estimation;394
24.5;5 Conclusion;396
24.6;References;397
25;Dynamics Calibration and Real-Time State Estimation of a Redundant Flexible Joint Robot Based on Encoders and Gyroscopes;399
25.1;1 Introduction;399
25.1.1;1.1 System;400
25.1.2;1.2 Problem Statement;401
25.1.3;1.3 Contribution;402
25.2;2 Related Work;402
25.3;3 Model;403
25.3.1;3.1 Kinematics;403
25.3.2;3.2 Dynamics - Elastic Joint Model;403
25.3.3;3.3 Extended Model;405
25.4;4 Measurement Functions;406
25.4.1;4.1 Calibration Parameters;406
25.4.2;4.2 Measurements;407
25.4.3;4.3 Extended Calibration;409
25.5;5 Evaluation;410
25.5.1;5.1 Initial Guess;412
25.5.2;5.2 Verification;413
25.6;6 State Estimation;417
25.6.1;6.1 Evaluation;420
25.6.2;6.2 Ball Batting Example;422
25.7;7 Conclusion;422
25.8;References;423
26;Mathematical Model for the Output Signal's Energy of an Ideal DAC in the Presence of Clock Jitter;424
26.1;1 Introduction;424
26.2;2 Signal's Energy at the Output of a d-dimensional Ideal DAC;426
26.3;3 Applications of ``Annihilate Operators'' to the Ideal DAC Model;428
26.4;4 Conclusions;434
26.5;References;435
27;Stochastic Integration Filter with Improved State Estimate Mean-Square Error Computation;437
27.1;1 Introduction;437
27.2;2 State Estimation;438
27.2.1;2.1 Formulation of Nonlinear State Estimation Problem;439
27.2.2;2.2 General Solution to State Estimation and State Estimation Methods;439
27.2.3;2.3 Gaussian Filters;440
27.3;3 Stochastic Integration Filter;441
27.3.1;3.1 Stochastic Integration Rule;441
27.3.2;3.2 Stochastic Integration Rule of Third and Fifth Degree;441
27.3.3;3.3 Properties of SIR;442
27.3.4;3.4 Algorithm of SIF;444
27.4;4 Improved Calculation of MSE by SIF;444
27.4.1;4.1 Theoretical Values of the MSE;444
27.4.2;4.2 Evaluation of Error Terms;447
27.5;5 Numerical Illustrations;448
27.5.1;5.1 Scalar Example;448
27.5.2;5.2 Bearing-Only Tracking Example;449
27.6;6 Conclusions;452
27.7;References;453
28;Appendix Author Index;454
29;Index;454