Will Machine Learning replace control theory?

No! Still Machine learning has to learn a lot to challenge traditional control theory ( branch of applied mathematics). Nothing in mathematics can be replaced by machine learning.

Is control theory used in Machine Learning?

Control Theory provide useful concepts and tools for Machine Learning. Conversely Machine Learning can be used to solve large control problems. Deep learning which extends supervised learning, can be viewed as a control problem.

What is reinforced learning in machine learning?

Reinforcement learning is a machine learning training method based on rewarding desired behaviors and/or punishing undesired ones. In general, a reinforcement learning agent is able to perceive and interpret its environment, take actions and learn through trial and error.

Is control Engineering dying?

TL;DR: No. Control Theory isn’t a dying field. The controls community has just evolved to work at the intersection with related areas such as game theory, machine learning and application areas such as biology etc.

How are systems theory and machine learning tightly coupled?

Systems theory and machine learning may not be “tightly” coupled in any obvious way, but if you “take a step back” you find that they are both studied under the umbrella field of complex systems.

How can machine learning help in automatic control?

The machine learning algorithms can lead to significant advances in automatic control. The biggest single advance occurred nearly four decades ago with the introduction of the Expectation-Maximization (EM) algorithm for training Hidden Markov Models (HMMs) [1].

Where does machine learning belong in the systems theory taxonomy?

In this “taxonomy” by H. Sayama, Systems Theory is it’s own sub-category and machine learning can be found within the sub-category of Evolution and Adaptation: Make smart AI workforce decisions. Knowing when and where to leverage humans in the loop is key to reducing the # of failed AI projects.

Can deep learning replace conventional neural networks in control system design?

In control system, conventional neural networks are well documented and used as a tool for controller design [7], system identification [8], auto-tuning [9], and compensator [10]. In contrary, the deep learning is not used yet, although it is more effective algorithm than conventional neural network, especially in big data.