Advanced Process Engineering Control (De Gruyter) | Alexandra Ana Csavdari, Botond Szilagyi, and Paul S. Agachi


Advanced Process Engineering Control (De Gruyter)
by Alexandra Ana Csavdari, Botond Szilagyi, and Paul S. Agachi

Advanced Process Engineering Control

The present work, Advanced Process Engineering Control, is intended to be the continuation of the authorsʼ Basic Process Engineering Control published by DeGruyter in 2014. It presents the main and conventional type control loops in process industries. Titles containing the concept of process engineering were deliberately chosen to suggest the inclusion, within the same approach, of processes other than the traditional ones. These come from outside the traditional fields of chemistry and petrochemistry: the sphere of pharmaceuticals, wastewater management, water purification, water reserve management, construction material industry, food processing, household or automotive industries.

During use and development of automatic control systems, control analysis and control system design for process industries have followed the traditional unit operation approach. It means that all control loops are established individually for each unit or piece of equipment in the plant and that the final plantwide control system represents the sum of the individual parts. The disadvantage of this method is the difficulty in stabilizing potential conflicts among individual loops. One very handy method of avoiding these interactions is the different tuning of control loops: those controlling the most important parameters are tuned tight and the others loose. Despite any process complexity, the unit operation approach provided reasonable results and remains in use on a large scale for designing control systems. Consequently, the book follows this traditional approach but provides updates to new industrial achievements.

Modern process plants are designed for flexible production and maximization of energy and material savings, especially within the frame of globalization and strong competition among manufacturers. Additionally, according to the fourth paradigm of process /chemical engineering, the processes have to fulfill tight environmental constraints. Industrial plants become more complex and have therefore strong interactions between process units. As a consequence, the failure of one unit might have a negative effect both on overall productivity and on environmental performances. This situation raises important control issues. A significant example is that of the thermally integrated plants, a concept born during the global energy crisis that started in 1973. Energy recovery became a priority for the industry and at the same time a scientific challenge. The necessity of redesigning industrial processes in terms of energetic efficiency was identified. Moreover, it was discovered that energy saving can be achieved using retrofit and recovery of extra energy from all secondary sources of a process. These aspects posed complex control problems because of the weak process controllability (effects of all disturbances are collected at the end of the process and reintroduced as enhanced disturbances at the input).

The emergence and continuous development of advanced control techniques provided solutions for plantwide control at any level of process complexity and in the above-mentioned conditions. According to Willis and Tham, a definition of the advanced process control can be formulated as “a systematically studied approach for the choice of pertinent techniques and their integration into a co-operative management and control system that will significantly enhance plant operation and profitability”.

Applied on complex chemical processes, advanced control is able to improve product yield, reduce energy consumption, increase plant capacity, improve product quality and consistency, enhance process safety, and reduce environmental impact. The benefits of the advanced control implementation are noticeable in the overall operating costs of a plant. These can decrease by 2% to 6%. Another benefit is the reduction of process variability. As a consequence, a plant can be operated at its designed capacity.

The present book is structured into two parts. Part I, entitled Advanced Process Control comprises chapters 1–7 and defines as advanced control any control system that surpasses simple and conventional loops. This could mean either smarter control configuration (cascade, feedforward, ratio, inferential, digital, or multivariable control) or improved regulator features (fuzzy, model predictive or optimal control). Approaches for the design of plantwide control systems are also presented. Part II, entitled Applied Process Engineering Control includes chapters 8–14 and refers to control solutions for the so-called unit operations: reaction and separation processes (distillation, absorption-desorption, extraction, evaporation, drying, and crystallization). The reader can check her or his level of comprehension by solving the problems and exercises proposed in Chapter 15. These cover the entire list of discussed topics. The authors hope that by including many industrial examples and applications as well as their own and other researcher’s experience accumulated over many years within the Group of Computer Aided Process Control, the present work will be useful for all interested parties in process engineering and process control: students in electrical, chemical, or process engineering; specialists in chemical, petrochemical or automation companies; professionals of water or natural gas management; etc.

The idea of this book series describing the main aspects of modern process engineering as applied to (not only) chemical industry belongs to Prof. Dr. Paul Şerban Agachi. He initiated the manuscripts, developed their structure, and coordinated the authors. More than 20 years ago, he recognized the ever-increasing importance of the subject and founded the Group of Computer Aided Process Engineering at the Faculty of Chemistry and Chemical Engineering of the Babeş-Bolyai University in Cluj-Napoca, Romania. Many professionals emerged from it, and the three younger authors of the present work have also started their carriers here. Although writers have exchanged ideas and discussed all topics of this book, work was distributed in agreement with individual strengths, experience, and competencies: Prof. Dr. Paul Şerban Agachi was in charge of chapters 1, 4, 12 and 13; Prof. Dr. Mircea Vasile Cristea shared his experience in chapters 2, 3, and 5–7; Assoc. Prof. Dr. Alexandra Csavdári wrote chapters 8 and 11, and coauthored with young Eng. Botond Szilágyi chapters 9, 10, and 14 with assistance from Ş. Agachi. The list of problems and exercises in Chapter 15 is the result of a joint effort. Finally, within the framework of this laborious enterprise, the authors gratefully acknowledge graduate students Maria Gherman, Abhilash Nair, Zsolt Tasnadi-Asztalos, Lászlo Zsolt Szabó and Hoa Pham Tai (engineers working in the Group of Computer Aided Process Engineering) for their dedicated and valuable help.


Preface v
Part I: Advanced Process Control 1
1 Complex and nonconventional control systems 3
1.1 Cascade control systems 3
1.1.1 Processes in series 3
1.1.2 Processes in parallel 10
1.2 Feedforward control systems 15
1.3 Ratio control systems 24
1.4 Inferential control systems 27
1.5 Selective control systems 28
References 30
2 Model predictive control 32
2.1 Introduction 32
2.2 MPC history 32
2.3 Basics of MPC control strategy 34
2.4 Types of MPC process models 42
2.4.1 Impulse and step response models 43
2.4.2 State-space models 49
2.4.3 Time series models 49
2.5 Predictions for MPC 50
2.6 Optimization for MPC 60
2.7 MPC tuning 64
2.8 MPC stability 66
2.9 Nonlinear MPC 68
References 71
3 Fuzzy control 75
3.1 Introduction 75
3.2 Fuzzy sets 75
3.3 Typical membership functions of the fuzzy sets 77
3.4 Operations with fuzzy sets 81
3.5 Fuzzy logic 83
References 91
4 Optimal control systems 92
4.1 Steady-state optimal control 92
4.2 Dynamic optimal control of batch processes 102
4.3 Dynamic optimal control of continuous processes 111
References 118
5 Multivariable control 119
5.1 Introduction 119
5.2 Multiloop control 120
5.2.1 Interaction among control loops 120
5.2.2 Pairing the control loops 126
5.2.3 Tuning the multiloop controllers 128
5.2.4 Decoupling interaction for multiloop control 129
5.3 Multivariable centralized control 133
References 134
6 Plantwide control 136
6.1 Introduction 136
6.2 Premises of plantwide control 137
6.3 Designing the plantwide control strategy 139
References 143
7 Linear discrete systems and Z transform 145
7.1 Introduction 145
7.2 Discrete systems described by input-output relationship 147
7.2.1 Sampling the continuous signals 147
7.2.2 Reconstruction of the continuous signals
from their discrete values 153
7.2.3 Analytical description of the discrete systems 156
7.2.4 Z transform 160
7.2.5 Z transform of several simple functions 162
7.2.6 Inverse of the Z transform 163
7.2.7 Z transfer function 166
7.2.8 Z transfer function of the sampled system 168
7.2.9 Z transfer function of the interconnected systems 169
7.3 Discrete PID controller 171
7.4 Other forms of the discrete controllers 173
References 175
Part II: Applied Process Engineering Control 177
8 Reaction unit control 179
8.1 Introduction 179
8.2 Basic concepts of ideal continuous and batch units 179
8.3 Temperature control 182
8.3.1 Into thermal instability 182
8.3.2 Out of thermal instability 184
8.3.3 Temperature control in practice – continuous units 188
8.3.4 Temperature control in practice – batch units 195
8.4 Pressure control 200
8.5 Liquid level control 202
8.6 pH control 202
8.6.1 pH and titration curves 202
8.6.2 pH regulator characteristics 206
8.6.3 Aspects of pH control in practice 208
8.7 End-point detection and product-quality control 210
8.7.1 Some analyzer types 210
8.7.2 End-point detection reliability issues 211
8.8 Control structure design for reaction units 212
8.8.1 Principles of control structure design 212
8.8.2 Control structure design for homogeneous ideal units 218
8.8.3 Control structure design for some heterogeneous units 222
References 230
9 Control of distillation processes 233
9.1 Economic constraints of distillation 233
9.2 The recovery factor 234
9.3 Lowering energy demand of distillation units 237
9.4 General control of continuous distillation columns 239
9.4.1 Mass and energy balance imposed control issues 239
9.4.2 Control solutions 249
9.5 Control issues of continuous distillation column dynamics 254
9.6 Control issues of batch distillation columns 259
References 260
10 Control of absorption processes 262
References 269
11 Control of extraction processes 270
References 278
12 Control of evaporation processes 279
References 286
13 Control of drying processes 287
13.1 Batch drying control 289
13.1.1 Conventional batch drying control 289
13.1.2 Advanced batch drying control 292
13.2 Continuous adiabatic drying 299
References 302
14 Control of crystallization processes 303
14.1 The process of crystallization 303
14.2 Crystal size distribution control 308
14.2.1 Model-free crystal size distribution control 309
14.2.2 Model-based crystal size distribution control 313
References 316
15 Problems and exercises 318
15.1 Advanced process control 318
15.2 Applied process engineering control 322
Index 325


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