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Full Description
Introduction to Process Control, Second Edition provides a bridge between the traditional view of process control and the current, expanded role by blending conventional topics with a broader perspective of more integrated process operation, control, and information systems. Updating and expanding the content of its predecessor, this second edition addresses issues in today's teaching of process control.Teaching & Learning PrinciplesPresents a concept first followed by an example, allowing students to grasp theoretical concepts in a practical mannerUses the same problem in each chapter, culminating in a complete control design strategyIncludes 50 percent more exercisesContentDefines the traditional and expanded roles of process control in modern manufacturingIntroduces the link between process optimization and process control (optimizing control), including the effect of disturbances on the optimal plant operation, the concepts of steady-state and dynamic backoff as ways to quantify the economic benefits of control, and how to determine an optimal transition policy during a planned production changeIncorporates an introduction to the modern architectures of industrial computer control systems with real case studies and applications to pilot-scale operationsDiscusses the expanded role of process control in modern manufacturing, including model-centric technologies and integrated control systems Integrates data processing/reconciliation and intelligent monitoring in the overall control system architectureWeb Resource The book's website offers a user-friendly software environment for interactively studying the examples in the text. The site contains the MATLAB (R) toolboxes for process control education as well as the main simulation examples from the book. Access the site through the authors' websites at www.pseonline.net and www.chms.ucdavis.edu/research/web/pse/ahmet/Drawing on the authors' combined 50 years of teaching experiences, this classroom-tested text is designed for chemical engineering students but is also suitable for industrial practitioners who need to understand key concepts of process control and how to implement them. The authors help readers see how traditional process control has evolved into an integrated operational environment used to run modern manufacturing facilities.
Contents
INTRODUCTIONWhy Process Control?Historical BackgroundRole of Control in Process IndustriesObjectives of ControlSummaryContinuing ProblemReferencesDefinitions and TerminologyConcepts and DefinitionsControl Design ProblemControl System DesignControl Design ProjectSummaryContinuing ProblemReferencesMODELING FOR CONTROLBasic Concepts in ModelingWhy Is Process Modeling Necessary?Classification of ModelsTypes of ModelsDegrees of FreedomModels and ControlSummaryReferencesDevelopment of Models from Fundamental LawsPrinciples of ModelingModels Based on Fundamental LawsModeling of Processes Involving Chemical ReactionsModeling of Complex SystemsDistributed Parameter SystemsNumerical Solution of Model EquationsSummaryContinuing ProblemReferencesInput-Output Models: The Transfer FunctionLinear (Linearized) ModelConcept of Transfer FunctionTransfer Functions of Single-Input Single-Output ProcessesProperties of Transfer FunctionsNonrational Transfer FunctionsSummaryContinuing ProblemModels from Process DataDevelopment of Empirical ModelsModel StructuresProcess Reaction Curve MethodRegression in ModelingSummaryContinuing ProblemReferencesPROCESS ANALYSISStabilityStability of Linear SystemsInput-Output StabilityRouth's CriterionRoot-Locus MethodDirect Substitution MethodSummaryReferencesDynamic PerformanceInput TypesFirst-Order ProcessesSecond-Order ProcessesMulticapacity ProcessesEffect of ZerosEffect of Time DelaysSummaryContinuing ProblemFrequency ResponseWhat Is Frequency Response?Complex Numbers in Polar CoordinatesConstruction of Frequency ResponseEvaluation of Frequency ResponseFrequency Response of Common SystemsBode DiagramsNyquist DiagramsSystems in SeriesSummaryContinuing ProblemFEEDBACK CONTROLBasic Elements of Feedback ControlFeedback Control ProblemControl LawClosed-Loop Transfer FunctionsAnalysis of Individual Terms in PID ControllersPractical Issues in PID DesignSummaryContinuing ProblemReferenceStability Analysis of Closed-Loop ProcessesClosed-Loop StabilityRouth's CriterionRoot-Locus MethodModeling ErrorsFrequency Response MethodsSummaryContinuing ProblemFeedback Control DesignDesign ObjectivesController Tuning TechniquesComparing the MethodsSummaryContinuing ProblemReferencesMODEL-BASED CONTROLModel-Based ControlFeedforward ControlDelay Compensation (Smith Predictor)Internal Model ControlSummaryContinuing ProblemReferencesModel Uncertainty and RobustnessIMC Structure with Model UncertaintyDescription of Model UncertaintyIMC Design under Model UncertaintySummaryReferencesModel Predictive Control General PrinciplesDynamic Matrix ControlProcess ConstraintsState-Space Formulation of MPCSummaryContinuing ProblemReferencesMULTIVARIABLE CONTROLMultivariable Systems: Special CasesCascade ControlRatio ControlSplit-Range ControlOverride ControlSummaryContinuing ProblemReferencesMultivariable SystemsCharacteristics of Multivariable ProcessesModeling of Multivariable ProcessesTransfer Functions of Multivariable ProcessesMultivariable Feedback Control StructureSummaryContinuing ProblemReferencesDesign of Multivariable ControllersMultiple-Input-Multiple-Output Feedback AnalysisRGA Interaction MeasureMultiloop Controller DesignDesign of Noninteracting Control Loops: DecouplersSummaryContinuing ProblemReferencesPractical Control of Nonlinear Processes Operating Regime Modeling ApproachGain-Scheduling ControllerMultimodel Controller DesignSummaryReferencesProcess Optimization and ControlProcess OptimizationOptimizing Control of DisturbancesDynamic Optimization and Transition PlanningSummaryReferencesIndustrial Control TechnologyEvolution of Industrial Control TechnologyGeneric Industrial Control Systems ArchitectureSummaryContinuing ProblemReferencesRole of Process Control in Modern ManufacturingExpanded Role of Control in Modern ManufacturingModel-Centric TechnologiesIntegrated Control SystemsSummaryReferencesData Processing and ReconciliationDealing with Missing PointsOutliersCharacterizing Process DataModeling Process DataData ReconciliationIssues in Data ReconciliationProcess MonitoringProcess MonitoringStatistical Process ControlPrincipal Component AnalysisMultivariate Performance MonitoringFault Diagnosis and ClassificationController Performance MonitoringSummaryReferencesAppendix A: LinearizationAppendix B: Laplace TransformationAppendix C: Matrix OperationsAppendix D: Basic StatisticsIndexAdditional Reading and Exercises appear at the end of each section.
