On the basis of demonstrating that the future era will be the era of automation, this paper first introduces the basic concept and development history of automation, and forms an overall understanding of automation. Then, the content of each part of automation discipline and its application significance in modern production practice are further introduced comprehensively. Finally, with a comprehensive understanding of automation, this paper discusses how to learn automation, and puts forward that we should pay attention to mathematics, professional theoretical knowledge, practice and knowledge update.

The first perspective of automation

Abstract: Based on the research that the future era will be the era of automation, this paper first introduces the basic definition and development history of automation in order to form an overall view. After that, it is further introduced in chapters and explains its significance in practical application. Finally, after having an overall view of automation, this paper discusses how to learn automation, and mentions mathematics, professional theory, practice and knowledge renewal.

Keywords: automation era; Basic definition; Progress; Content and application; How to learn automation

With the rapid development of science and technology in the 20th century, many new branches of science and technology have emerged: computer and information theory; Such as cybernetics and automation technology; Molecular biology and genetic engineering; Laser technology and optical fiber; Space technology and so on. They have gathered into a huge force, which has greatly changed the labor and lifestyle of human beings and promoted profound changes in all aspects of society. It not only impacts workers and farmers in the front line of production, but also impacts enterprises, institutions, government agencies and even housewives.

These changes have come so fast that sociologists who are most sensitive to social phenomena are surprised: where will this society go?

From a scientific point of view, human society is an organic combination of energy exchange and information exchange. When we know all kinds of specific special laws of human society in detail, we can use machines with these two functions to complete it [1], which is automation technology. So in a sense, automation is synonymous with modernization. It can be asserted that human society is now in a new period of change after the primitive human era and the era of precision machinery, and the end of this change is the exciting era of automation.

The reason why it is "inspiring" is that in the era of automation, almost all production activities can be completed by machines, and human labor productivity will be greatly improved and social wealth will be greatly enriched. Only at this time can human beings get rid of the forced labor that they have to engage in in order to make a living, and the productive forces are completely liberated, so that it is really possible to realize capitalism.

Development of automation technology

Equipment with different degrees of "automation" function has existed since ancient times. China's ancient south guide car, wooden ox and flowing horse, dripping water from a copper pot, European timepieces and some hand-operated machines all reflect the wisdom of the people and all have some "automatic" flavor. The automatic device, which aims to replace or enhance people's intelligent function, so as to ensure the realization of the predetermined goal under uncertain conditions, should belong to the centrifugal governor on the steam engine invented by Watt at the earliest. It consciously uses the feedback principle to keep the rotating speed within a certain range when the boiler pressure and load change [3].

The 20th century is a century of rapid development of automation technology, which is closely related to the development of control science and technology. As the theoretical basis of automation technology, it experienced several important development periods in the 20th century: for example, Lyapunov stability theory and the concept of PID control law in the early 20th century; Feedback amplifier in 1920s: Nyquist diagram and Bode diagram in 1930s; Wiener's cybernetics in the 1940s; Boehlmann's dynamic theory and Pontryagin maximum principle in 1950s: in 1960s, Kalman filter, system state space method, controllability and observability of the system; Self-tuning control and adaptive control in 1970s; Robust control of system uncertainty in 1980s: intelligent control theory based on intelligent information processing in 1990s [4].

In addition, the rapid development of electronic information science, especially computer science, undoubtedly provides a broad development stage for automation. For example, in the 1920s, the development of electronic information technology provided various powerful signal processing means, which made the automatic control and information processing technology leap forward and gradually formed a new discipline-automation.

In 1950s and 1960s, the increasingly widespread application of digital computers greatly improved the ability of complex numerical calculation and simple logical judgment, and was especially suitable for information processing and automatic control based on accurate mathematical models. It makes automation technology truly applied to all fields from industrial production to aerospace. However, due to the insufficient functions of the "old-fashioned" computers at that time, some more complicated problems still could not be solved well.

Since 1970s and 1980s, various new computers have appeared one after another. These computers have more comprehensive functions: they can access and calculate images, sounds and other information at high speed, make qualitative and fuzzy reasoning and judgment on data and symbols, and tolerate local errors or faults while maintaining overall excellent performance. People can store "expert knowledge" in these computers, so that they can better handle unprecedented situations and meet the higher requirements of automation technology.

In short, automation technology developed rapidly in the 20th century with the deepening of research in this field and the far-reaching influence of the development of other disciplines. Moreover, it can be seen that this development momentum shows no signs of slowing down. Therefore, we have reason to believe that in the near future, automation technology will stand out from many emerging disciplines, thus better improving the production structure system of human beings and becoming the most influential technical science in the future society.

2. The basic concept of automation

So what exactly is "automation"?

Simply put, automation is to control with various components and instruments without people [2].

It began with people using machines to automatically realize various operations according to fixed procedures, freeing human beings from heavy, monotonous and repetitive labor. But that's not enough. In order to further liberate manpower, it is required that machines constantly improve their ability to automatically maintain necessary functions in an uncertain or changing environment in order to achieve predetermined goals. Therefore, the automation system must be open, constantly get information from the external environment and make necessary analysis, processing, judgment, decision-making, adjustment and control [3].

Therefore, automation technology studies how to extend people's functions of information acquisition, processing and decision control through various technical tools and systems (including computers), so as to better guide production and improve production capacity, production level and labor productivity.

3. The content and application of automation technology

According to different theoretical approaches, technical means and processing objects, the content of automation can be roughly divided into six parts: control theory, engineering system and control, system science and system engineering, pattern information processing, intelligent system and knowledge engineering, robotics and robotics [3].

In order to have a deeper understanding of automation, the following briefly introduces the research objects and application fields of each part.

3. 1 engineering system and control

Engineering system and control study the control and design of various engineering systems. From a single automatic control device to the automation of a production process, and then to the integration of control, management and business decision-making of the whole factory and enterprise, it is the content of its research [3].

Engineering system and control technology are widely used in various fields of manufacturing industry. Among them, the most influential and promising is the modern integrated manufacturing system (CIMS). In the broadest sense, CIMS can include the whole process of enterprise management, from long-term planning, market analysis, R&D strategy, product planning, design and production, resource allocation, to specific planning and scheduling at the workshop level, supervision and control of production activities, quality control, product inspection, to sales service and market feedback [3].

Such a comprehensive and comprehensive automatic production process can enable enterprises to better meet market requirements with more efficient and better service, improve enterprise efficiency and enhance their commercial competitiveness. (In China, no company has fully quoted this system, the gap ~)

3.2 Control theory

Control theory studies how to make the system run normally and have predetermined functions by actively collecting and applying information according to the characteristics of the controlled object and environment [3].

Control theory has played an important role in the progress of human science and technology in the 20th century, and has a positive impact on solving many challenging problems in today's society, providing a scientific ideological methodology and laying a theoretical foundation for realizing automation in many industrial fields.

Now it has been successfully applied and penetrated into many fields such as industrial and agricultural production, science and technology, military, biomedicine, social economy and human life.

3.3 Systems Science and Systems Engineering

In the most general sense, system science studies the motion law, behavior characteristics and how to design and control various systems with certain overall functions, which are composed of interacting and interrelated things according to a certain structure [3].

It is mainly used in many branches of disciplines, such as operations research, cybernetics and information theory, and has become an important research field of automation and developed vigorously.

3.4 Mode information processing

Pattern recognition, also known as pattern information processing, its original meaning is to study the processing, description and classification of image, text, sound and other pattern information generally accepted by human sensory organs by computers. In a broader sense, pattern recognition can also refer to any process of judging and classifying the conceptual characteristics of general things [3].

The application direction of pattern recognition includes computer vision, character and text recognition, speech recognition and understanding. China is in a leading position in the field of pattern recognition, and many China scholars have made important contributions to it.

3.5 Robots and Robotics Technology

Robot is a special automatic machine, which has a motion mechanism similar to human limbs, and can receive sensory information such as vision, hearing and touch, and complete various machine operation functions under the command of the processor [3].

Robots can not only liberate human beings from harsh conditions and tedious work, but also have irreplaceable advantages in strength, accuracy and speed, as well as the ability to survive and work in special environments.

Because of this, robot technology has been widely used in industry, national defense and science and technology, and has effectively promoted the development of related disciplines and technical fields, thus making it an active and attractive research field in modern automation disciplines.

3.6 artificial intelligence

The research of artificial intelligence is mainly about how to use machines to imitate some aspects of human intelligence activities and expand the functions of the human brain [3].

The rapid development and great progress of modern science and technology put forward new and higher requirements for control and system science, and automatic control theory is facing new development opportunities and severe challenges. Traditional control theory has encountered many problems in solving some uncertain, complex and changeable problems. This requires the construction of such a machine, so that it can respond in real time in a complex and changeable environment, make flexible judgments and decisions, and realize a higher level of intelligent control of the automation system. Simply put, one of the ways of automatic control is to realize the intelligentization of the control system [5].

As a frontier science, artificial intelligence has developed rapidly, among which the most influential branches are expert system based on "knowledge expression" and "complex system with simple processor"-artificial neural network. These fields not only have profound epistemological significance and far-reaching influence on the development of many scientific and technological fields, but also have been widely used in automatic control, information processing and the application of computers in judgment, decision-making and problem solving, showing strong vitality.

4. How to learn automation

Learning new things and knowledge begins with understanding it, but it is not enough. When you really understand a subject, it is more important to really enter the subject and learn it.

As a combination of theory and technology, the learning method of automation specialty is very different from that of pure theoretical knowledge and pure practical technology. So how to learn automation? Personally, I think the following points are worthy of attention.

I. Mathematics

Mathematics, as an indispensable theoretical tool for almost all engineering knowledge, should first arouse our great attention.

A person who is good at mathematics is not necessarily outstanding in professional knowledge, but a person with a strong major must have a solid foundation in mathematics. The reason is simple: "If a worker wants to do a good job, he must sharpen his tools first". How can an electrician complete a circuit inspection without necessary instruments? How can a doctor cure a dying patient without the necessary medical materials? How can an old man sitting by the lake catch fish without a fishing rod, hook and line in his hand? Similarly, how can a person with a weak mathematical foundation learn automation well?

Therefore, the study of automation major should put the study of mathematics in the first place.

2. Professional theoretical knowledge

Without profound and extensive professional theoretical knowledge, it is impossible to achieve something in this major. Why did Newton become a mathematician and physicist instead of an "automatic chemist"? It is determined by his professional theoretical knowledge.

Secondly, there are many disciplines of automation, so we should first have a general plan for our own development direction, and then go to a higher level of learning. Not seeking everything, but making a breakthrough; Don't generalize, but have a deep understanding to make yourself not only "broad" but also "refined" in professional knowledge. Only in this way can we get a better ranking in the future talent battlefield.

Three. practice

Automation major is not only a theory, but also a technology widely used in production practice, so theoretical practice is indispensable for automation learning.

"Practice is the only criterion for testing truth". Only when a theory is applied to practice can it show its true colors. As far as automation is concerned, professional learning ultimately points to work. Therefore, strengthening the theoretical practice in the learning stage is undoubtedly beneficial to the future work.

Four. Knowledge updating

As a new frontier discipline, automation is undergoing great changes almost every day. If you really want to learn automation major well, at least make sure that you can keep up with the development of the times. We should be highly sensitive to the rapidly developing scientific and technological knowledge and have the basic quality of lifelong learning. "Never too old to learn" should not be just a beautiful slogan. In the process of learning automation, we should really melt it into our own blood and always meet the impact of new ideas with full enthusiasm.

Do you think it's okay?