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INTRODUCTION

1.1 An Integration Approach, What and Why?

Today’s science and technology have reached such diversity that a young researcher can easily get lost in the face of countless disciplines. Therefore some philosophical guideline might be helpful for motivating the road chosen for the research and development pursued, on which this thesis reports.

Since the celebrated work of Newton 300 years ago, Western society has experienced scientific and industrial revolutions which constitute an important component of today’s Western civilization. Due to its success "Newtonianism", or the mechanistic world view, has been dominating Western science and technology, especially natural science. This world view perceives the universe as a machine, governed by exact mathematical laws. By this philosophy, in principle, any system can be modelled like a clock; it consists of different elements like the parts of the clock. If all individual elements of the system and their interactions can be analyzed clearly, one will get perfect understanding of the total system behavior. Under such a philosophy, the methodology of the present Western science, especially natural sciences, can be characterized as analytical, rational, reductional and experimental. This method has been extremely successful for studying mechanical systems. Recent developments, however, are showing that this method cannot give satisfactory solutions to problems when studying modern physics, sociology, economy, biology, and so on. Now Some researchers are convinced that modern science should be guided by at philosophy that has an organic systematic and dynamic world view; cf. Capra, (1984); in fact this was the world view of ancient Eastern philosophy and wisdom (Chinese and Indian). Perhaps it was also the world View in the West before Newton.

Coming from China, Let me try to tell some Chinese stories. In the old time, the Chinese believed that there is an ultimate reality which underlies and unifies the multiple things and events. This reality was called the Dao (Tao), inadequately translated as ’the Way’. A principal characteristic of the Tao is the cyclical nature of its ceaseless motion. This world view was symbolized by the Tai-Ji-Tu 太極圖 or ’Diagram of the Supreme Ultimate’, see Fig. 1.1. This diagram is a symmetric arrangement of the polar opposites: the dark yin (陰) and bright yang (陽), From this pattern, one feels strongly a Continuous Cyclic movement: "The yang returns  to its beginning; the yin attains its maximum and gives place to the yang" (Kuei Ku Tzu, 鬼谷子, fourth century B.C.; translated by J. Needham, 1956).

The two dots in the suggest the idea that the two forces contain in themselves the Seeds of their opposites. Yang is associated with strong, male and creative power; yin is associated with receptive, female and maternal element. Further associations are:

yin yang

earth heaven

moon sun

night day

winter Summer

water fire

coolness warmth

interior surface

The relation between yin and yang is complementary. It is important to recognize that these opposites do not belong to different categories but are extreme poles of a single whole. Yin does not exist without yang and vice versa. Nothing is only yin or only yang. All natural phenomena and social events are manifestations of a continuous oscillation between yin and yang. Just as it does not make sense to ask which is more important for life, the is good is not yin or yang but the dynamic balance or harmony between the two; what is bad or harmful is imbalance.

There were two most influential schools in old China: Confucianism,

founded by Kong Fu-Zi (Confucius, 孔夫子 479 B.C.), and Taoism, founded by Lao Zi (Lao Tzu, 老子 , who was said to be 20 years older than Confucius). Confucius studied social system; and he believed that in order to keep the balance of the society there must be a strict convention of social etiquette. One of the rules Confucius made for the people was that everyone in society should behave according his social position - an emperor should act as an emperor, minister as minister, father as father and son as son (  君君臣臣父父子子  ). He also advised people not to be extreme and radical ( 中庸之道 , moderation). Taoists studied more on the relation between the human being and nature. The harmony of this system is achieved if people can discover the Tao, or the law of nature, acting spontaneously. Wu Wei (無為) is the action Taoists took; it means follow the nature and do not act against nature.

In our time, when talking about social life and scientific research, the following associations of yin and yang might be acceptable:

yin yang

feminine masculine

contractive expansive

conservative demanding

responsive aggressive

cooperative competitive

intuitive rational

synthesizing analytic

integral reductional

Examining this list of opposites, we see that at least since 300 years ago, Western society and science have consistently favored yang over yin (when compared with Eastern culture): competition over cooperation, exploitation of nature over conservation, rational knowledge over intuitive wisdom, reduction over integration, analysis over synthesis, and so on.

After having recognized this imbalance, it is not difficult to understand why Western scientists are so fond of formal mathematics; why they are so good in differentiating problems into their smallest possible components; and why they often forget to put the pieces back together again, This imbalance also shows that there is a need to emphasize more strongly yin in Western research, i.e., to emphasize intuition, synthesis and integration.

Under such a guideline, in this work, we will try to integrate identification and control for industrial manufacturing systems; we will show how this philosophy can be useful for choosing a research topic and even for generating new ideas.

In the last few centuries in the history, however, Chinese preferred yin to yang (when compared with Western culture) - they would give response to the nature rather than exploit it, they tried to follow the rules in order to avoid conflicts, they preferred talking about general philosophy to the completion of a concrete project, they preferred intuitive wisdom and common sense to analytical reasoning. This is perhaps one of the reasons why modern science has not been born in China.

One might ask what modem China can learn from Western culture. The author believes that there is a need to emphasize yang. For example, make competition fair play and bring it into the public eye from underground; give individuals more freedom and opportunities for self-fulfillment; use more scientific reasoning and analytical approach to study social, political and economic problems; test theories by facts instead of by doctrines; and so on. The science and technology in modern China, however, suffer the same illness as in the West, that is, there is in general a lack of intuition and integration approach. One of the reasons is that most researchers in China are in the learning period, we do not have enough experience and confidence yet to go further to Combine the Western and the Chinese approaches. Time and an open policy are needed to achieve a good combination of the Western and the Eastern approaches and, more broadly, their cultures. But if this happens, there will be a renaissance of Eastern culture, which will be enjoyed, this time, by both Eastern and Western people due to modern communications. More discussions on this topic are beyond the scope of the thesis.

1.2 The Philosophy of Identification

There are basically two ways of building models of systems – the mathematical modelling approach and the identification approach.

Mathematical modelling is the most common and conventional method in Western science and technology. By this approach one starts with decomposing the system into its subsystems, and subsystems into their elements; then one writes down the equations for each element based on first principles, e.g., physical laws; and finally one forms the system model by putting the equations together according to the interrelations between the elements and the subsystems. Some people also call this approach physical modelling. From the methodological point of view, this is typically a reductional, rational and analytical approach; a yang approach.

System identification can be defined as deriving system models from observations and measurements. In this approach, the system is viewed as a whole; there is perhaps no need or intention to analyze each element of the system; the systems behavior is observed by measuring some relevant variables; and such a model is chosen of which the behavior fits best the measurements. By this approach one does not attempt to go deep into the system, the precise physical knowledge of the System elements and their interrelations is not necessary; therefore identification is also called black-box modelling; see Fig. 1.2.a. Identification is a new branch in the field of dynamic systems and control; and is formally founded about 25 years ago (the first IFAC symposium on identification was held in Prague, 1967).

In contrast with the mathematical modelling approach, the philosophy of

identification is the wholeness; its methodology is integral and synthetical. This is, however, not very much a typical modern Western methodology. It has a strong yin force. Here we see another parallel between ancient Eastern philosophy and modern Western science and technology (physicists have pointed out many parallels between Eastern philosophy and modern physics; see c.g., Capra, 1984). It is interesting to observe that modern identification has been born on the bed of systems and control. From a philosophical point of view, it is not difficult to see why this happened. Needless to say, the philosophy behind dynamic system theory is the systems view or the wholeness.

The mathematical modelling approach follows Newton’s philosophy; its use is limited whenever the fundamental laws of some system elements and/or some interrelations are not known yet or too complex. With the aid of identification, which has also a systems view, one might go beyond this limit. A remark should be given here that we are not trying to say that identification is better than mathematical modelling or vice versa. To obtain the best model of a system in practice, one should Combine the two approaches (that is, to reach at balance between yin and yang).

There is more to tell about identification. Chinese medicine is a good example to show how the ancient Chinese philosophy and wisdom influenced the practice of Chinese people. The human body was modelled as the universe; viewed as an organic whole and there are yin and yang parts. For example, the back is yang, the from is yin; the skin or surface is yang, the interior is yin. Inside the body, there are yin and yang organs. Of the five viscera the heart and liver are yang organs and the spleen, lungs and kidneys are yin organs. The balance between  and yang is maintained by a continuous flow of qi (chi  氣) or vital energy, cyclically between yin and yang organs. Whenever the flow between yin and yang is obstructed (hindered), an imbalance will occur and the body falls ill. Te detect the illness, pulse feeling was the most important method of diagnosis of Chinese medicine. The examinations made upon both the right and left wrists, the physician using three fingers (index, middle and ring fingers) to feel the pulse of his patient. It is recorded that Bian Qian (Pien Chiao, 扁鵲  ) who lived about 255 B.C. was the inventor of this idea; cf. Wong and Wu, (1936). Before him the pulses from many places of the body should be measured. But Bien Qiao realized that one could gather enough information only from the two wrists of the patient, which was much more convenient.

One of the rules made by Confucianism was that men and women should not be close with each other ( 男女授受不親), except within the family; and an unmarried girl should not be seen by male outsiders. But this rule was not really a restriction for a Chinese doctor to perform diagnosis for his female patient. In such a case, he could simply feels the pulses of the lady behind the curtain; see Fig. 1.2.1b. This procedure, however, fits very well to the definition of identification; and we note that the doctor was identifying a three output system! This story of pulse feeling suggests that the history of system identification is at least 2000 years longer than we usually think.

So much about philosophy. Let us now turn to more practical and technical issues.

Preface to Multi-variable System Identification for Process Control by Yucai Zhu

Systems and control theory has experienced a continuous development in the last few decades. The state space approach and Kalman filter are the products of the 1960s which, for the first time, made it possible to solve general linear multivariable control problems. Since 1970 adaptive control theory and techniques have been developed. In the 1980s robust control and H-infinity control of multivariable systems were developed. Fault detection and diagnosis techniques were also developed in this period. These new techniques are very promising for industrial applications and have attracted much interest from the academic researchers. The impact of these developments on process industries, however, has been very limited. When we visit plants in process industries, we find that a typical modern computer control system is a combination of the state-of-the-art computer technology and classical PID (proportional, integral and differential) control algorithms which are the restrictive single variable control techniques of the 1940s and 1950s.

Many possible reasons for this failure of technology transfer can be identified. One important reason is the lack of accurate dynamic models of industrial processes, since all the above mentioned modern techniques are model-based and need reasonably accurate process models. Another reason is the lack of good communication between the modern control community and process industries.

However, one process industry has made a distinction. In the last decade, model predictive control (MPC) technology has gained its industrial position in the refinery and petrochemical industry, and has started to attract interest from other process industries. There are over 500 control engineers from contracting and operation companies several thousands of applications have been reported. Most often, an MPC controller uses a linear dynamic model of the process that is obtained by way of black-box identification. However, due to various reasons, the cost of current MPC identification is very high and many trials and errors have to be made by the user. The test time is rather long (from several weeks to several months) and the tests are carried out manually around the clock. This, on the one hand, demands very high commitment of engineers and operators and, on the other hand, makes MPC project planning difficult. It is believed nowadays that process modeling and identification is the most difficult and time consuming part of an MPC project. Wide spread applications of MPC technology call for more effective and efficient identification technology.

Process identification is the field of mathematical modeling using test data. This branch of automatic control has been very actively developed in the last three decades, with many books published on the topic. Most of these books have very high academic quality. However, they are too theoretically oriented for industrial users and for undergraduate students. Therefore, the purpose of this book is to fill the gap between theory and application and to provide industrial solutions to process identification that are based on sound scientific theory. We will study various identification methods; both linear and block-oriented nonlinear models will be treated. We will present, in detail, project procedures for multivariable process identification for control. Identification test design and model validation will be emphasized. The book is organized in a way that is reader friendly and easy to use for engineers and students. We will start with the simplest method, and then gradually introduce other methods. In this way, one can bring more physical insight to the reader and some mathematics can be avoided. Each method is treated in a single chapter or section, and experiment design is explained before discussing any identification algorithms. The many simulation examples and actual industrial case studies will show the power and efficiency of process identification and will make the theory more applicable. Matlab® M files are included that will help the reader to learn identification in a computing environment.