Advances in Dynamics, Instrumentation and Control: Proceedings of the 2006 International Conference (Cdic '06), Queretaro, Mexico, 13 - 16 August 2006

This second volume is a compilation of 43 articles representing the scientific and technical advances in various aspects of system dynamics, instrumentation, measurement techniques, simulation and controls, which would serve as an important resource in the field. The articles represent state-of-the-art contributions in the fields of dynamics and control of nonlinear, hybrid and stochastic systems; nonlinear control theory; and adaptive, model predictive and real-time controls with applications involving fault diagnostics, manufacturing systems, vehicular dynamics, simulator designs, smart actuators, etc. CONTENTS......Page 8 Preface......Page 6 1. Introduction......Page 12 2. Multi-robot architecture proposed......Page 13 2.1. Distributed decision mechanisms......Page 14 2.2. Deliberative decision supervision......Page 15 3.2. HDM developed for a team of soccer-playing robots......Page 16 3.3. Decision supervision for this type of multi-robot system......Page 18 4.2. Decision supervision relevance......Page 19 References......Page 20 1. Introduction......Page 22 2. Some preliminaries......Page 23 3. Localization of compact invariant sets of the Rikitake system......Page 24 4. Localization of compact invariant sets of the Pikovsky-Rabinovich-Trakhtengertz system......Page 27 References......Page 30 1. Introduction......Page 32 2. Main results......Page 33 3. The solutions of the inequalities......Page 37 4. An example......Page 38 References......Page 39 1. Introduction......Page 40 2. Experimental Setup......Page 41 3. Model of the Helicopter......Page 43 5. Conclusions......Page 46 References......Page 47 1. Introduction......Page 48 2. Mathematical Modelling of the Flexible Robot Using TB Theory......Page 49 3. Robot Dynamic Model......Page 54 4. Simulation Results......Page 55 5. Conclusions......Page 56 References......Page 57 A New Approach for Modeling, Simulation and Control of Complex Electromechanical Systems: The Computational Mechatronics Scheme L.-I. Lugo-Villeda, V. Parra-Vega and G. Nunez-Esquer......Page 58 1. Computational Mechatronics (CMk) Scheme......Page 59 2. Analysis, Synthesis and Control of Novel Biped Robot using CMk......Page 60 3.1. Mathematical Modeling and Mechanical Design Conceptualization......Page 61 3.2. Integration of Mechatronics Constrains to CAD Model......Page 62 3.3. Stabilizing Control and Planning Trajectories......Page 63 3.5. Experimental Results us CMk-based Results......Page 64 4. Discussions......Page 66 References......Page 67 1. Introduction......Page 68 2. System Models......Page 70 3.1 Control objective......Page 71 3.2 Controller design......Page 72 4. Simulation......Page 74 References......Page 76 1. Introduction......Page 78 2.1 Play and Stop Operators......Page 80 2.2 Prandtl-Ishlinskii Model......Page 81 3. Rate Dependent Hysteresis Operators......Page 82 3.1 Properties of the Rate Dependent hysteresis Operators......Page 83 4. Rate Dependent Prandtl-Ishlinskii Model......Page 84 5. Simulation Results......Page 85 References......Page 86 1. Introduction......Page 88 2. Rotor Model......Page 89 3.1. Parameter Range......Page 91 4.1. Experiment Setup......Page 92 4.2. Results and Discussion......Page 93 5 . Conclusions......Page 96 References......Page 97 Modelling and Experimentation the Accreting Medium in the 1d Semi-Infinite Moving Solid for Heat Transfer with a Novel Control Volume Conductance Method Luis Del Llano Vizcayu and Alejandro Castaneda-Miranda......Page 98 2. Theoretical Model......Page 99 3. Experimental Results And Discussion......Page 100 References......Page 105 1. Introduction......Page 107 3.1. Solution for convective spatially distributed system......Page 109 3.2. Hybrid representation for convective spatially distributed system......Page 110 4. Control for a convective one-dimensional system with constant conditions......Page 112 5. Study case......Page 114 6. Conclusions......Page 115 References......Page 116 1. Introduction......Page 117 2. Methodology......Page 119 2.1. Steady State Analysis......Page 120 2.2. Time Domain analysis......Page 122 References......Page 124 1. Introduction......Page 127 2. Nomenclature and mathematical model......Page 128 3.2. Application to a heat exchanger......Page 130 3.3. Numerical simulations......Page 131 3.4. Experimental results......Page 132 References......Page 134 1. Introduction......Page 135 2.1. Conventional Speed Control Strategy......Page 136 2.2. Discrete-time 2DF Speed Control......Page 138 3. Neurofuzzy 2 Degrees-of-freedom PI Controller......Page 139 4.1. Knowledge-Based Manual Tuning......Page 142 4.2. Automatic Tuning of PI-NF2DF Controller......Page 143 5. Simulation Experiments and Results......Page 144 References......Page 145 1. INTRODUCTION......Page 147 2. BASIC CONCEPT OF STABLE PID CONTROLLER FOR ASPR PLANTS......Page 148 3. APPLICATION TO THE DESIGN OF STABLE TRACKING PID CONTROL SYSTEMS......Page 149 4. A CONCRETE DESIGNSCHEME OF PFC......Page 151 5. CONSIDERATION CONCERNING STEADY STATE OF THE CONTROL SYSTEM......Page 153 6. Example......Page 154 References......Page 156 1. Introduction......Page 157 2. Problem setup......Page 159 3. The partial linearization method to tracking the time-variant reference function......Page 160 4. Numerical simulations......Page 163 References......Page 165 1. Introduction......Page 166 2.1. Separately Excited Configuration......Page 167 3. FPRG for Linear Systems......Page 168 5.1. Fault Scenarios for a Separately Excited DC Motor......Page 169 5.2.1. Geometric FDI Analysis for a DC Motor in Parallel Connection......Page 171 5.2.2. Simulation Results for a DC Motor in Parallel Connection......Page 172 5.2.3. Experimental Results for a DC Motor in Parallel Connection......Page 173 6. Conclusions and Final Remarks......Page 174 References......Page 175 1. Introduction......Page 176 2. Fault Detection via DPCA......Page 178 3. DPCA based Fault Detection with Adaptation......Page 179 3.1. Preservation of the Correlation Structure in a MIMO Linear System under Changes in the Operation Point......Page 180 3.2. Estimating the Inputs-Output Relations......Page 181 3.3. Fault Detection with Adaptive Standardization......Page 182 4. Application Example: Three Tanks System......Page 183 5 . Conclusions......Page 184 References......Page 185 1. Introduction......Page 186 2. Modelling and Problem Formulation......Page 187 3. Structure of Fault Detection Observer......Page 189 4. Simulation......Page 190 5. Conclusion......Page 191 References......Page 192 1. Introduction......Page 193 2.2. Method I......Page 194 2.3. Method II......Page 196 3.1. Vibration reduction problem......Page 197 4.1. An experimental model of the stacker crane......Page 198 4.2. Experimental results......Page 199 References......Page 200 1. Introduction......Page 201 2. Stability of a class of perturbed second order systems......Page 202 3. State observer design......Page 206 4. A simple pendulum example......Page 208 References......Page 210 1. Introduction......Page 211 3. Design Scheme of Two DOF of GPC with Computational Savings......Page 214 3.1. GPC without an integral action......Page 215 3.2. Two DOF of GPC with computational savings......Page 216 5. Example......Page 217 References......Page 218 1. Introduction......Page 221 2. Problem Statements......Page 222 3.1. Prediction Form......Page 223 3.2. Discrete Equivalent Performance Function......Page 224 3.3. Control Law......Page 225 4. Simulation Result......Page 226 5. Conclusion......Page 228 References......Page 229 1. Introduction......Page 230 2.1. System Description......Page 231 2.2. Modelling......Page 232 3. Fault Diagnosis System......Page 233 4. Experimental Result......Page 235 5. Conclusion......Page 236 References......Page 237 1. Introduction......Page 238 2.1. Actuator Faults......Page 240 3. Fault Diagnosis Approaches for VSD......Page 241 4.1. Hardware Reconfiguration for Power Actuators......Page 243 4.2. Fault Compensation Strategies......Page 244 References......Page 246 1. Introduction......Page 248 2. Multibody Modeling......Page 250 3. Sensor Design......Page 251 3.1. Micro-structure model for dynamic analysis:......Page 252 4. Interaction of the Sensor and Multibody Model......Page 253 5. Simulation Results......Page 254 6. Conclusion......Page 256 7. References......Page 257 1. Introduction......Page 258 2.1. BG Model of the SCIM......Page 259 2.2. BG Model of the Inverter......Page 260 3.1. Fault trees......Page 262 4. Diagnosis Results......Page 264 References......Page 266 1.2. Combustion of Black Liquor in the Kraft Recovery Boiler......Page 268 2. Problem Statement......Page 269 3.1. 18 Degree-of-Freedom Model for High Frequency Attenuation......Page 271 3.2. Finite Difference Model for Low Frequency Attenuation......Page 273 3.3. Computational Results......Page 274 4. Conclusions......Page 276 References......Page 277 1. Introduction......Page 278 2. Roll plane model of a heavy vehicle......Page 279 3. Suspension force formulations......Page 281 4.1. Suspension rate......Page 282 4.2. Roll stiffness......Page 283 5.1. Roll dynamics......Page 284 5.2. Ride qualities and suspension travel under random road inputs......Page 285 Conclusions......Page 286 References......Page 287 1. Guidelines......Page 288 2. HOPN Model......Page 289 3.1. Reliability Model of Object......Page 290 3.2. Hierarchical Net in Object......Page 292 3.3. Reliability Model of UMT......Page 293 References......Page 294 1. Introduction......Page 296 2. Effect of Cargo Tie-Down Flexibility......Page 297 3.1. Approach......Page 299 3.2. Time history of trailer angle......Page 300 3.3. Soil surfaces......Page 301 3.5. Example results......Page 302 4. Conclusions......Page 304 References......Page 305 1. Introduction......Page 306 2. State Observer Design......Page 307 3.1. The State space model......Page 308 3.3. Controller construction......Page 309 4. Numerical Results......Page 310 Conclusion......Page 311 References......Page 313 1. Introduction......Page 314 2.2. Sonar Model......Page 316 3.1. SIFT......Page 318 3.3. Triangulation......Page 319 3.4. Stereo Triangulation Error......Page 320 4.2. Bayes Update Formula......Page 321 5 . Results......Page 322 6. Conclusion and Future Work......Page 323 References......Page 325 1. Introduction......Page 326 2. The sensor Design......Page 328 3. Finite Element Modeling......Page 330 4. Simulation Results......Page 331 5. Conclusions......Page 333 References......Page 334 1 Introduction......Page 336 3 Directional granulometry and supremum of directional erosions......Page 338 4 Fingerprint orientation field based on directional granulometry and quadtree structure......Page 340 5 Fingerprint orientation field based on the supremum of directional erosions......Page 342 Conclusion......Page 344 References......Page 345 1. Introduction......Page 346 2. Design of the optical layout......Page 347 3. Experiments and results......Page 348 4. Discussion of results......Page 349 5. Conclusion......Page 351 References......Page 352 1. Introduction......Page 353 2.1. Solution of the Mathematical Model......Page 354 3. The Reactor Control System......Page 355 3.1. Fuzzy-PI Controller......Page 357 4. Simulation Results......Page 358 References......Page 360 1. Introduction......Page 361 2. Mathematical models......Page 362 2.1. Dissolved oxygen model......Page 363 2.2. Oxygen mass transfer model......Page 364 3.1. PID control with anti-windup......Page 365 3.2. Linearizing+PID control......Page 366 4. Results......Page 367 5. Conclusions......Page 369 References......Page 370 1. Introduction......Page 371 2. Design and Operation Principle......Page 372 3. Ceramic Oxide Deposition......Page 374 3.1 Cobalt oxide deposition......Page 375 3.2 Titanium dioxide deposition......Page 376 References......Page 378 1. Introduction......Page 380 2. Adaline Linear Network......Page 381 2.1 The Delta Rule......Page 382 3. Experiments and Results......Page 384 3.2 Experiments......Page 385 4. Conclusion......Page 388 References......Page 389 1. Introduction......Page 390 2. Problem Formulation......Page 392 3. Neural Network Adaptation......Page 394 4. Application to Camless Engines......Page 395 References......Page 398 1. Introduction......Page 400 2. The Coupled Dynamic Model......Page 401 3.1. Electrostatic Equivalent Stiffness Matrix......Page 405 3.2. Frequency Spectrum......Page 406 3.3. Dynamic Responses......Page 408 References......Page 409 1. Introduction......Page 411 2. Closed Loop Parameter Identification......Page 413 2.1. Stability......Page 414 3. LQR Controller Design......Page 416 4. Experimental Results......Page 417 References......Page 419