Interpretazioni

• Record Nr.: UNISOBSOBE00019612
• Pubbl/distr/stampa: Roma : Studium
• Lingua di pubblicazione: Non definito
• Formato: Materiale a stampa
• Livello bibliografico: Collezione

Industrial control systems / / Robert C. Gilbert and Angela M. Schultz, editors

• Record Nr.: UNINA9910963726403321
• Pubbl/distr/stampa: Hauppauge, N.Y., : Nova Science Publishers, c2011
• ISBN: 1-62081-607-5
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (263 p.)
• Collana: Mechanical engineering theory and applications; Engineering tools, techniques and tables
• Altri autori (Persone): GilbertRobert C; SchultzAngela M
• Disciplina: 629.8
• Soggetti: Adaptive control systems
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- INDUSTRIAL CONTROL SYSTEMS -- INDUSTRIAL CONTROL SYSTEMS -- CONTENTS -- PREFACE -- Chapter 1 DEVELOPMENT OF FRICTION IDENTIFICATION, MODELING, AND COMPENSATION METHODS FOR FEED DRIVE MOTIONS OF CNC MACHINE TOOLS -- ABSTRACT -- 1. INTRODUCTION -- 2. DESCRIPTIONS OF EXPERIMENT DESIGN AND MEASUREMENT -- 2.1. Experimental Setup -- 2.2. Measurement and Control -- 2.3. Experiments -- 2.3.1. Breakaway Experiment -- 2.3.2. Constant-Velocity Experiment -- 3. FRICTION IDENTIFICATION TECHNIQUES -- 3.1. Estimation of Position-Dependent Friction -- 3.2. Estimation of Velocity-Dependent Friction -- 3.3. Integration of Obtained Position-Dependent and Velocity-Dependent Frictions -- 4. ; DESIGN OF VELOCITY-BASED FRICTION COMPENSATOR -- 5. EXPERIMENTAL RESULTS OF SINUSOIDAL MOTION TESTS -- 6. EXPERIMENTAL RESULTS OF CIRCULAR MOTION TESTS -- CONCLUSION -- REFERENCES -- Chapter 2 DYNAMIC MATRIX CONTROL WITH INTERNAL MODEL BASED ON ANN OF A CONTINUOUS EXTRACTIVE PROCESS FOR BIOETHANOL PRODUCTION -- ABSTRACT -- NOMENCLATURE -- 1. INTRODUCTION -- 1.1. Dynamic Matrix Control (DMC) -- 2. EXTRACTIVE FERMENTATION PROCESS FOR BIOETHANOL PRODUCTION -- 3. PLANT MODEL BASED ON ANN -- 3.1. ANN Configurations -- 3.2. ANN Model Selection -- 3.3. Validation Parity Plot -- 4. USE OF VARIABLE CONTRIBUTIONS TO THE ANN OUTPUT TO IDENTIFY THE IMPORTANCE OF VARIABLES -- 5. USE OF RANDOM STEP DISTURBANCES TO SELECT THE MANIPULATED AND CONTROLLED VARIABLES -- 6. NETWORK TRAINING -- 7. NONLINEAR PREDICTIVE CONTROL -- CONCLUSION -- REFERENCES -- Chapter 3 NONDESTRUCTIVE DYNAMIC MONITORING OF ACCELERATED ION BEAMS -- ABSTRACT -- INTRODUCTION -- 1. DYNAMIC NONDESTRUCTUVE BEAM DIAGNOSTICS FOR INDUSTRIAL CYCLOTRON -- 1.1. Simulation -- 1.2. Dynamic Beam Diagnostic System -- 1.2.1. Transparent Profilometers -- 1.2.2. Charge-Frequency Converters -- 1.2.3. Measurements.; 2. DYNAMIC NONDESTRUCTUVE BEAM DIAGNOSTICS FOR CIRCULATING BEAM OF RESEARCH ACCELERATOR -- 2.1. Detector Design -- 2.2. Readout Electronics and Measurements -- CONCLUSION -- REFERENCES -- Chapter 4 ADAPTIVE JACOBIAN TRAJECTORY TRACKING FOR SERIAL ROBOT MANIPULATOR PASSING THROUGH SINGULARITIES -- ABSTRACT -- 1. INTRODUCTION -- 2. KINEMATICSJACOBIAN OF SERIAL ROBOT MANIPULATORS -- 3. ARTIFICIAL NEURAL NETWORKS (ANNS) -- 4. COLLECTING TRAINING DATA -- 5. NETWORK'S IMPLEMENTATION -- 5.1. Training Stage -- 5.2. Testing Stage -- CONCLUSIONS -- REFERENCES -- Chapter5INTELLIGENTCONTROLSYSTEMFORANINDUSTRIALMANIPULATOR -- Abstract -- 1Introduction -- 2AdaptiveLearningTechniqueforLarge-ScaleTeachingSignals -- 2.1Background -- 2.2Model-basedroboticservosystem -- 2.2.1Computedtorquecontrolmethod -- 2.2.2TeachingsignalforRNN -- 2.3Independentrecurrentneuralnetworksforanindustrialrobotwithsixjoints -- 2.3.1AdaptivelearningofRNNs -- 2.3.2LearningresultsofRNNs -- 2.3.3Discussion -- 2.4AdvancedservosystemusingintegratedRNNs -- 3FineGainTuningforModel-BasedRoboticServoControllersUsingGeneticAlgorithms -- 3.1Background -- 3.2RoboticServoController -- 3.2.1ResolvedAccelerationControl -- 3.2.2BasicGainTuningConsideringCriticallyDampedCondition -- 3.2.3DesiredTrajectory -- 3.3Finegaintuningbyusinggeneticalgorithms -- 3.4TuningResults -- 3.4.1RoboticDynamicswithoutFrictionTorqueTerm -- (1)Incaseofresolvedaccelerationcontrollaw -- (2)Incaseofcomputedtorquecontrollaw -- 3.4.2RoboticDynamicswithFrictionTorqueTerm -- (1)Incaseoftheresolvedaccelerationcontrollaw -- (2)Incaseofthecomputedtorquecontrollaw -- 4Conclusions -- References -- Chapter 6 MODELING AND CONTROL OF INDUSTRIAL SYSTEMS USING GLOBAL AUTOMATA -- ABSTRACT -- 1. INTRODUCTION -- 1.1. Modeling Industrial Systems - A Literature Review -- 1.2. Automatic PLC Code Generation - A Literature Review.; 2. AUTOMATA THEORY -- 2.1. Finite Automata -- Definition 2.1. Finite Automata -- Definition 2.2. Run - Computation -- 2.2. Hybrid Automata -- Definition 2.3. Hybrid Automata -- 2.3. Timed Automata ; -- Definition 2.4. Timed Automata -- 2.4. PLC Automata -- Definition 2.5. PLC Automata -- 2.5. Software for Modeling Discrete Event Systems -- 2.5.1. JGrafchart -- 2.5.2. UPPAAL -- 2.5.3. Diagen -- 2.5.4. Kronos -- 2.5.5. Hytech -- 2.5.6. Moby/PLC -- 2.5.7. Shift -- 2.5.8. Supremica -- 3. GLOBAL AUTOMATA -- 3.1. Global Automata Definition -- Definition 3.1. Global Automata: A Global Automaton is Defined by the Tuple -- 3.2. Global Automata Structural Properties. -- Definition 3.2. A Global Automaton GA is Linear if -- Definition 3.3. A Global Automaton GA is Time Invariant if -- Definition 3.4. -- Definition 3.5. -- Definition 3.6. -- Definition 3.7. -- Definition 3.8. -- Definition 3.9. -- Definition 3.10. -- 3.3. Comparison with Existing Methods -- 4. MODELING TOOLS ON GLOBAL AUTOMATA -- 4.1. State Aggregation -- 4.1.1. The "3-Machines Stop" Problem -- 4.2. Automata Composition -- Definition 4.1. Global Automata Composition: -- 4.2.1. A Three Tank System -- 4.3. Hierarchy on Global Automata -- 5. IMPLEMENTATION TOOLS -- 5.1. Guide for Building Simulation Models Based on Global Automata -- 5.1.1. Guide for Code Generation -- 5.1.2. Examples of Building Simulation Models by Using The Guide -- 5.1.2. A House Thermostat -- 5.1.5. Token Passing Bus Network -- 5.1.6. The "3-Machines Stop" Problem -- 5.2. Synthesis Tool for Implementing Global Automata in PLCs -- 5.2.1. Guide For Programming PLCs In IL, LAD and FBD -- 5.2.2. Guide for Programming PLCs in Structured Text -- 5.2.3. Guide for Programming PLCs in Sequential Function Chart -- 5.2.4. In Case Of Multiple Automata Model. -- 5.3. Applications of Guide Use in Real Problems.; 6. EXAMPLES OF USING GLOBAL AUTOMATA -- 6.1. Reciprocating Internal Combustion Engine -- 6.2. Concrete Batching and Mixing Plant -- 6.2.1. Modeling and Control Using Global Automata -- 6.2.2. Supervisory Control and Data Acquisition Station -- 6.3. A Three Tank System -- CONCLUSIONS -- REFERENCES -- INDEX -- Blank Page.
• Sommario/riassunto: In this book, the authors present current research in industrial control systems. Topics discussed include the development of friction identification, modelling, and compensation methods for feed drive motions of CNC machine tools; MPC (Model Predictive Control) control algorithms for industrial applications; non-destructive dynamic monitoring of accelerated ion beams; and, Jacobian trajectory tracking for serial robot manipulators and intelligent control systems for an industrial manipulator.