Applications of Laplace mathematical transforms in automatic control
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This post was last edited by hjbjl on 2012-5-2 23:17. In the study of automatic control, teachers always emphasize the application of the Laplace mathematical transform; however, in practical experience, I have hardly seen any use of this transform； I’d appreciate it if an expert could provide a brief overview of the application of Laplace transforms in the automation industry, as well as any recommended textbooks.
In practical work, there is basically no need to use such mathematics to solve the tasks at hand! In fact, the Laplace transform is primarily used in the stability analysis of control systems, such as for complex controls like decoupling, and it requires a high level of foundational knowledge! Those I am waiting for certainly wouldn’t dare to enter such a refined place! Bro, it’s better to do more practical things – don’t make it so complicated! You see, even I, a graduate engineer, am left confused – how unsatisfying!
I see. I was wondering – mainly, during that control systems course, everything seemed so confusing to me. It’s one of the core professional foundation courses, and I’ve always wanted to understand what’s going on, which is why I keep trying to figure it out. It seems that this basic professional course is just a formality too
It’s probably our teacher who tricked us, because the lessons were very boring and hard to understand, yet the teacher insisted that we had to master them. To this day I still don’t understand it; I just want someone to explain why things have to be done this way. I’ve been worried that I haven’t learned this well. Seek knowledge
The concepts related to automatic control courses are quite complex, as automatic control is indeed a highly specialized field with intricate theories. However, for ordinary instrument operators today, only the basic principles are necessary; many of the more complex theories are likely to be used only by those engaged in research and design. Therefore, it’s difficult to see the application of such advanced theoretical knowledge in practical situations:victory:
Yes, when I first started learning *, I was really worried that I wouldn’t be able to master it. It seems there’s no need to worry. I really don’t understand why the textbook authors make it so difficult; it puts a psychological burden on us right from the start of our learning process.
Since they are all called textbooks, they are of course designed based on the characteristics of that particular field. Many theoretical concepts are covered in them; just like in physics, which is also relevant in everyday life!
Your teacher is also an expert at bluffing; they have no real experience. A good teacher would never act like that. What kind of teacher are they if they can’t explain things clearly to their students? Hahaha.
It can’t be called tricking people – what you’re doing is giving too much emphasis to applications and too little to the fundamentals. Without mathematical theory, self-control isn’t possible. Researching new problems requires certain mathematical support; if one wants to improve oneself, it’s necessary to study the basic knowledge carefully. I’ve been taking courses on self-control recently, where I’ve been exposed to concepts like complex functions and Laplace transforms. Mathematics is used to describe various phenomena such as electrical and mechanical movements, and it’s really interesting. These mathematical tools are needed when solving problems.
Those in graduate school upstairs rarely use this kind of mathematical knowledge, but how do we make use of it? Could you provide some examples? These things are too dull; it’s impossible to understand them without any practical applications.
This post was last edited by huio1983 on 2012-5-2 19:01. In production data analysis and data mining within ERP systems, the control modules used in DCS and PLCs are developed based on mathematical theories; it’s just that we cannot see the interior of those modules. Although one does not engage in design work, understanding the underlying mechanisms of control processes still requires knowledge of relevant mathematics.