| Preface | p. xi |
| Introduction | p. 1 |
| Objectives | p. 1 |
| Introduction | p. 1 |
| Basic definitions and terms used in process control | p. 2 |
| Process modeling | p. 2 |
| Process dynamics and time constants | p. 5 |
| Types or modes of operation of process control systems | p. 13 |
| Closed loop controller and process gain calculations | p. 15 |
| Proportional, integral and derivative control modes | p. 16 |
| An introduction to cascade control | p. 16 |
| Process measurement and transducers | p. 18 |
| Objectives | p. 18 |
| The definition of transducers and sensors | p. 18 |
| Listing of common measured variables | p. 18 |
| The common characteristics of transducers | p. 19 |
| Sensor dynamics | p. 21 |
| Selection of sensing devices | p. 21 |
| Temperature sensors | p. 22 |
| Pressure transmitters | p. 28 |
| Flow meters | p. 35 |
| Level transmitters | p. 42 |
| The spectrum of user models in measuring transducers | p. 44 |
| Instrumentation and transducer considerations | p. 45 |
| Selection criteria and considerations | p. 48 |
| Introduction to the smart transmitter | p. 50 |
| Basic principles of control valves and actuators | p. 52 |
| Objectives | p. 52 |
| An overview of eight of the most basic types of control valves | p. 52 |
| Control valve gain, characteristics, distortion and rangeability | p. 67 |
| Control valve actuators | p. 71 |
| Control valve positioners | p. 76 |
| Valve sizing | p. 76 |
| Fundamentals of control systems | p. 78 |
| Objectives | p. 78 |
| On-off control | p. 78 |
| Modulating control | p. 79 |
| Open loop control | p. 79 |
| Closed loop control | p. 81 |
| Deadtime processes | p. 84 |
| Process responses | p. 85 |
| Dead zone | p. 86 |
| Stability and control modes of closed loops | p. 87 |
| Objectives | p. 87 |
| The industrial process in practice | p. 87 |
| Dynamic behavior of the feed heater | p. 88 |
| Major disturbances of the feed heater | p. 88 |
| Stability | p. 89 |
| Proportional control | p. 90 |
| Integral control | p. 93 |
| Derivative control | p. 95 |
| Proportional, integral and derivative modes | p. 98 |
| I.S.A vs 'Allen Bradley' | p. 98 |
| P, I and D relationships and related interactions | p. 98 |
| Applications of process control modes | p. 99 |
| Typical PID controller outputs | p. 99 |
| Digital control principles | p. 100 |
| Objectives | p. 100 |
| Digital vs analog: a revision of their definitions | p. 100 |
| Action in digital control loops | p. 100 |
| Identifying functions in the frequency domain | p. 101 |
| The need for digital control | p. 103 |
| Scanned calculations | p. 105 |
| Proportional control | p. 105 |
| Integral control | p. 105 |
| Derivative control | p. 106 |
| Lead function as derivative control | p. 106 |
| Example of incremental form (Siemens S5-100 V) | p. 107 |
| Real and ideal PID controllers | p. 108 |
| Objectives | p. 108 |
| Comparative descriptions of real and ideal controllers | p. 108 |
| Description of the ideal or the non-interactive PID controller | p. 108 |
| Description of the real (Interactive) PID controller | p. 109 |
| Lead function - derivative control with filter | p. 110 |
| Derivative action and effects of noise | p. 110 |
| Example of the KENT K90 controllers PID algorithms | p. 111 |
| Tuning of PID controllers in both open and closed loop control systems | p. 112 |
| Objectives | p. 112 |
| Objectives of tuning | p. 112 |
| Reaction curve method (Ziegler-Nichols) | p. 114 |
| Ziegler-Nichols open loop tuning method (1) | p. 116 |
| Ziegler-Nichols open loop method (2) using POI | p. 117 |
| Loop time constant (LTC) method | p. 119 |
| Hysteresis problems that may be encountered in open loop tuning | p. 120 |
| Continuous cycling method (Ziegler-Nichols) | p. 120 |
| Damped cycling tuning method | p. 123 |
| Tuning for no overshoot on start-up (Pessen) | p. 126 |
| Tuning for some overshoot on start-up (Pessen) | p. 127 |
| Summary of important closed loop tuning algorithms | p. 127 |
| PID equations: dependent and independent gains | p. 127 |
| Controller output modes, operating equations and cascade control | p. 131 |
| Objectives | p. 131 |
| Controller output | p. 131 |
| Multiple controller outputs | p. 132 |
| Saturation and non-saturation of output limits | p. 133 |
| Cascade control | p. 134 |
| Initialization of a cascade system | p. 136 |
| Equations relating to controller configurations | p. 136 |
| Application notes on the use of equation types | p. 139 |
| Tuning of a cascade control loop | p. 140 |
| Cascade control with multiple secondaries | p. 141 |
| Concepts and applications of feedforward control | p. 142 |
| Objectives | p. 142 |
| Application and definition of feedforward control | p. 142 |
| Manual feedforward control | p. 143 |
| Automatic feedforward control | p. 143 |
| Examples of feedforward controllers | p. 144 |
| Time matching as feedforward control | p. 144 |
| Combined feedback and feedforward control | p. 147 |
| Objectives | p. 147 |
| The feedforward concept | p. 147 |
| The feedback concept | p. 147 |
| Combining feedback and feedforward control | p. 148 |
| Feedback-feedforward summer | p. 148 |
| Initialization of a combined feedback and feedforward control system | p. 149 |
| Tuning aspects | p. 149 |
| Long process deadtime in closed loop control and the Smith Predictor | p. 150 |
| Objectives | p. 150 |
| Process deadtime | p. 150 |
| An example of process deadtime | p. 151 |
| The Smith Predictor model | p. 152 |
| The Smith Predictor in theoretical use | p. 153 |
| The Smith Predictor in reality | p. 153 |
| An exercise in deadtime compensation | p. 154 |
| Basic principles of fuzzy logic and neural networks | p. 155 |
| Objectives | p. 155 |
| Introduction to fuzzy logic | p. 155 |
| What is fuzzy logic? | p. 156 |
| What does fuzzy logic do? | p. 156 |
| The rules of fuzzy logic | p. 156 |
| Fuzzy logic example using five rules and patches | p. 158 |
| The Achilles heel of fuzzy logic | p. 159 |
| Neural networks | p. 159 |
| Neural back propagation networking | p. 161 |
| Training a neuron network | p. 162 |
| Conclusions and then the next step | p. 163 |
| Self-tuning intelligent control and statistical process control | p. 165 |
| Objectives | p. 165 |
| Self-tuning controllers | p. 165 |
| Gain scheduling controller | p. 166 |
| Implementation requirements for self-tuning controllers | p. 167 |
| Statistical process control (SPC) | p. 167 |
| Two ways to improve a production process | p. 168 |
| Obtaining the information required for SPC | p. 169 |
| Calculating control limits | p. 173 |
| The logic behind control charts | p. 175 |
| Some Laplace transform pairs | p. 176 |
| Block diagram transformation theorems | p. 179 |
| Detail display | p. 181 |
| Auxiliary display | p. 185 |
| Configuring a tuning exercise in a controller | p. 188 |
| Installation of simulation software | p. 190 |
| Operation of simulation software | p. 193 |
| Configuration | p. 197 |
| General syntax of configuration commands | p. 198 |
| Configuration commands | p. 199 |
| Algorithms | p. 208 |
| Background graphics design | p. 223 |
| Configuration example | p. 224 |
| Introduction to exercises | p. 229 |
| Flow control loop - basic example | p. 231 |
| Proportional (P) control- flow chart | p. 234 |
| Integral (I) Control - flow control | p. 237 |
| Proportional and integral (PI) control - flow control | p. 240 |
| Introduction to derivative (D) control | p. 242 |
| Practical introduction into stability aspects | p. 246 |
| Open loop method - tuning exercise | p. 252 |
| Closed loop method - tuning exercise | p. 256 |
| Saturation and non-saturation output limits | p. 260 |
| Ideal derivative action - ideal PID | p. 263 |
| Cascade control | p. 267 |
| Cascade control with one primary and two secondaries | p. 271 |
| Combined feedback and feedforward control | p. 276 |
| Deadtime compensation in feedback control | p. 279 |
| Static value alarm | p. 284 |
| Index | p. 286 |
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