Practical process control tuning and troubleshooting pdf
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- PID Control in the Third Millennium
- Practical Process Control Tuning and Troubleshooting
- Practical Process Control Tuning And Troubleshooting
The early 21 st century has seen a renewed interest in research in the widely-adopted proportional-integral-derivative PID controllers. Each chapter has specialist authorship and ideas clearly characterized from both academic and industrial viewpoints. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline.
PID Control in the Third Millennium
Practical Process Control by Douglas J. Cooper Copyright by Control Station, Inc. All Rights Reserved. All rights reserved. No portion of this book may be reproduced in any form or by any means except with explicit, prior, written permission of the author. Doug Cooper, professor of chemical engineering at the University of Connecticut, has been teaching and directing research in process control since Doug's research focuses on the development of advanced control strategies that are reliable, and perhaps most important, easy for practitioners to use.
He strives to teach process control from a practical perspective. Thus, the focus of this book is on proven control methods and practices that practitioners and new graduates can use on the job. Author Prof. Douglas J. Cooper Chemical Engineering Dept. Publisher Control Station, Inc. Fundamental Principles of Process Control 1. Process Control Preliminaries 4. Advanced Modeling of Dynamic Process Behavior 7. Integral Action and PI Control 8. Evaluating Controller Performance 9. First Principles Modeling of Process Dynamics Linearization of Nonlinear Equations and Deviation Variables Laplace Transforms Transfer Functions Block Diagrams Cascade Control Feed Forward Control Multivariable Controller Interaction and Loop Decoupling Modeling, Analysis and Control of Multivariable Processes Non-Self Regulating Integrating Processes They achieve this by continually measuring process operating parameters such as temperatures, pressures, levels, flows and concentrations, and then making decisions to, for example, open valves, slow down pumps and turn up heaters so that selected process measurements are maintained at desired values.
The overriding motivation for modern control systems is safety, which encompasses the safety of people, the environment and equipment. The safety of plant personal and people in the community is the highest priority in any plant operation. The design of a process and associated control system must always make human safety the prime objective.
The tradeoff between safety of the environment and safety of equipment is considered on a case by case basis. At the extremes, a nuclear power plant will be operated to permit as much as the entire plant to be ruined rather than allowing significant radiation to be leaked to the environment. On the other hand, a fossil fuel power plant may be operated to permit an occasional cloud of smoke to be released to the environment rather than permitting damage to a multimillion dollar process unit.
Whatever the priorities for a particular plant, safety of both the environment and the equipment must be specifically addressed when defining control objectives. The Profit Motive When people, the environment and plant equipment are properly protected, control objectives can focus on the profit motive.
Automatic control systems offer strong benefits in this regard. Plant-wide control objectives motivated by profit include meeting final product specifications, minimizing waste production, minimizing environmental impact, minimizing energy use and maximizing overall production rate. Process: Gravity Drained Tank.
Product specifications set by the marketplace your customers are an essential priority if deviating from these specifications lessens a product's market value. Example product specifications range from maximum or minimum values for density, viscosity or component concentration, to specifications on thickness or even color.
A common control challenge is to operate close to the minimum or maximum of a product specification, such as a minimum thickness or a maximum impurities concentration.
It takes more raw material to make a product thicker than the minimum specification. Consequently, the closer an operation can come to the minimum permitted thickness constraint without going under, the greater the profit.
It takes more processing effort to remove impurities, so the closer an operation can come to the maximum permitted impurities constraint without going over, the greater the profit. All of these plant-wide objectives ultimately translate into operating the individual process units within the plant as close as possible to predetermined values of temperature, pressure, level, flow, concentration or other of the host of possible measured process variables.
As shown in Fig. To ensure a constraint limit is not exceeded, the baseline set point operation of the process must be set far from the constraint, thus sacrificing profit. Figure 1.
The result is improved profitability because the process can be operated closer to the operating constraint. Automatic Process Control Because implementation of plant-wide objectives translates into controlling a host of individual process parameters within the plant, the remainder for this text focuses on proven methods for the automatic control of individual process variables.
The Case Studies module presents industrially relevant process control challenges including level control in a tank, temperature control of a heat exchanger, purity control of a distillation column and concentration control of a jacketed reactor. These real-world challenges will provide hands-on experience as you explore and learn the concepts of process dynamics and automatic process control presented in the remainder of this book. We introduce some basic jargon here by discussing a control system for heating a home as illustrated in Fig.
This is a rather simple automatic control example because a home furnace can only be either on or off.
As we will explore later, the challenges of control system design increase greatly when process variable adjustments can assume a complete range of values between full on and full off. In any event, a home heating system is easily understood and thus provides a convenient platform for introducing the relevant terminology. The control objective for the process illustrated in Fig. To achieve this control objective, the measured process variable is compared to the thermostat set point.
The difference between the two is the controller error, which is used in a computation by the controller to compute a controller output adjustment an electrical or pneumatic signal. If the manipulated process variable is moved in the right direction and by the right amount, the measured process variable will be maintained at set point, thus satisfying the control objective. This example, like all in process control, involves a measurement, computation and action: Measurement.
Note that computing the necessary controller action is based on controller error, or the difference between the set point and the measured process variable. Such block diagrams provide a general organization applicable to most all feedback control systems and permit the development of more advanced analysis and design methods. This measurement feedback signal is subtracted from the set point to obtain the controller error.
The error is used by the controller to compute a controller output signal. The signal causes a change in the mechanical final control element, which in turn causes a change in the manipulated process variable. An appropriate change in the manipulated variable works to keep the measured process variable at set point regardless of unplanned changes in the disturbance variables.
The home heating control system of Fig. Both these figures depict a closed loop system based on negative feedback, because the controller works to automatically counteract or oppose any drift in the measured process variable. Suppose the measurement signal was disconnected, or opened, in the control loop so that the signal no longer feeds back to the controller.
With the controller no longer in automatic, a person must manually adjust the controller output signal sent to the final control element if the measured process variable is to be affected.
It is good practice to adjust controller tuning parameters while in this manual, or open loop mode. Switching from automatic to manual, or from closed to open loop, is also a common emergency procedure when the controller is perceived to be causing problems with process operation, ranging from an annoying cycling of the measured process variable to a dangerous trend toward unstable behavior.
For the kinds of process control applications discussed in this book, example categories of such equipment include: Sensors to Measure: temperature, pressure, pressure drop, level, flow, density, concentration Final Control Elements: solenoid, valve, variable speed pump or compressor, heater or cooler The best place to learn about the current technology for such devices is from commercial vendors, who are always happy to educate you on the items they sell. Contact several vendors and learn how their particular merchandise works.
Ask about the physical principles employed, the kinds of applications the device is designed for, the accuracy and range of operation, the options available, and of course, the cost of purchase. Keep talking with different vendors, study vendor literature, visit websites and participate in sales demonstrations until you feel educated on the subject and have gained confidence in a purchase decision.
Don't forget that installation and maintenance are important variables in the final cost equation. The third piece of instrumentation in the loop is the controller itself. Thus, the focus of this book is to help you:. To activate cruise control, the driver presses a button while traveling at a desired velocity and removes his or her foot from the gas pedal. The control system then automatically maintains whatever speed the car was traveling when the button was pressed in spite of disturbances.
For example, when the car starts going up or down a hill, the controller automatically increases or decreases fuel flow rate to the engine by a proper amount to maintain the set point velocity. The flow of liquid out of the tank is regulated by a valve in the drain line. The control objective is to maintain liquid level in the tank at a fixed or set point value.
Liquid level is inferred by measuring the pressure differential across the liquid from the bottom to the top of the tank. The Case Studies module, a training simulator that challenges you with real-world scenarios, provides this reinforcement. Use Case Studies to explore dozens of challenges, brought to life in color-graphic animation, to safely and inexpensively gain hands-on experience.
The Case Studies module contains several simulations for study. You can manipulate process variables to obtain step, pulse, ramp, sinusoidal or PRBS pseudo-random binary sequence test data. Process data can be recorded as printer plots and as disk files for process modeling and controller design studies. After designing a controller, return to the Case Studies simulation to immediately evaluate and improve upon the design for both set point tracking and disturbance rejection.
The processes and controllers available in Case Studies enable exploration and study of increasingly challenging concepts in an orderly fashion. Early concepts to explore include basic process dynamic behaviors such as process gain, time constant and dead time.
Intermediate concepts include the tuning and performance capabilities of P-Only through PID controllers and all combinations in between. Advanced concepts include cascade, decoupling, feed forward, dead time compensating and discrete sampled data control. This simulates the lag associated with the mechanical movement of a process valve.
Practical Process Control Tuning and Troubleshooting
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. Description: Practical troubleshooting advice that's easy to understand and easy to implement Practical Process Control shows you how to analyze and troubleshoot process control systems in process manufacturing plants. Easy to read and understand, the book stresses practical solutions that don't require complex mathematics. This book offers several advantages that you won't find in comparable texts.
Practical Process Control loop tuning and troubleshooting. This book differs from others on the market in several respects. First, the presentation is totally in the time domain the word "LaPlace" is nowhere to be found. The focus of the book is actually troubleshooting, not tuning. If a controller is "tunable", the tuning procedure will be straightforward and uneventful. But if a loop is "untunable", difficulties will be experienced, usually early in the tuning effort. The nature of any difficulty provides valuable clues to what is rendering the loop "untunable".
Practical Process Control Tuning And Troubleshooting
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. Smith Published Engineering. Practical Process Control loop tuning and troubleshooting. This book differs from others on the market in several respects.