Machine Learning in Control System - Black keyhole

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Machine Learning in Control System

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Now we are living in the generation of Artificial intelligence which is the technology that will be domaining the future. The top countries are now highly approaching this future technology to lead the future world because who will have achieved the peak of this technology will be the leader of the future world. Artificial Intelligence is now influencing every high potential industry such as the Medical Industry, Business, Construction, Agriculture, Defence field of the country...etc. One of the fears of Artificial Intelligence is, Some people will have lost their jobs at the same time there will be many Job Opportunities will be created by Artificial Intelligence.

So Now we take look at one of the sectors of Artificial Intelligence that is Machine learning. Machine learning is the field of study that gives Machines to learn things without being explicit programming. It uses some Maths Algorithms to solve some algorithmic problems. Yes, we can make predictions, classification, Object detection, Summarization, Clustering, Recommender systems using different  Machine learning algorithms.

I have given below the Machine learning algorithms for different usage


       1. Linear regression

       2. polynomial regression

       3. Exponential regression

       4.logistic regression

       5. logarithmic regression


        1.K-nearest neighbors

         2.Decision Trees

         3. Random forest

         4. Support vector machines

         5. Naive Bayes


      1.  K-means

       2. DBScan

       3. Mean Shift

       4. Hierachial


      1. Anomaly detection

      2. sequential pattern mining

      3. Dimensionality reduction

      4. Recommendation system

If we will take industrials or control systems, there will also AI and machine learning is influencing rapidly. If we take industrial control systems it would be controlled by SCADA, PLC ,APC ,DCS, those things could able to control high voltage current consumption for a long time and consistently.

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For example, here I have taken an industrial farming sector to give an example of how machine learning would be applied to make this industry more efficient.

In this kind of farming sector they are using machine learning to predict the energy consumption, wind speed, how much energy would be produced, wind power estimation.

Unfortunately, while they use industrial sensors it may cause errors in measuring the sensor values due to over-temperature, calibration problems. these things will affect the performance of the industry for long time efficient usage so that machine learning would be applied to this kind of industry to reduce these errors. Here they are using a large amount of accuracy that is set to train the model these pre-trained models will be applied to the industrial control systems such as SCADA, PLC, and some other things which I had previously mentioned above.

Now let me take a look at how machine learning would be applied in CERN's industrial control system.

They analyze a large amount of data automatically identify errors, components deterioration, poor process Optimisation...etc.These data are grouped from different sensors, valves. In CERN's control system they are using machine learning algorithms to group the data, detect oscillations in command to devices predict signal behavior as trained neural networks to make them more precise, predict when the sensors and actuators are going to stop working, detect deviated signals from millions of other valves

The hardware parts such as valve actuators and other stuffs are connected with Programmable Logic controllers to acquire data and control those actuators. The data from the actuators will be sent to the computer clusters by the Programmable Logic controllers. Throughout the computer cluster the data will be stored in the database and will be screened on the user interface. as well as that data stored in the database will be given for the machine learning working process.

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So in finally, in control systems, while they use machine learning or deep learning in their system, it maintains their actuator's temperature more efficiently and will reduce cost and do much more duties

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