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Robust control is one of the topics that electronics-engineering students encounter in the course of their academic life. To some, they might find the topic enjoyable, and others might find it very challenging to grasp the concepts. It will require them to be fully engrossed in their books all day long. At times completing such assignments can be very challenging for students. It will require them to devote a great deal of time and effort to get the solutions. Unfortunately, not all have an abundance of time that could be allocated to this topic. Depending on the priority, some students need to focus their attention on extra-curricular activities. Whereas, some of them might have loads of assignments to do. But it is true beyond any doubt that all these students would require external professional help. This is the reason why online academic writing companies exist, it is to help students in whatever assignments they might have.
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Robust control

Robust control is one of the branches of control theory. As logic would dictate, it would be very advantageous if we understand what control theory is before having the slightest clue of what a robust control is. It is a bit technical, but this article will make it easier for you to understand

Control theory

Control theory has been used for almost over a century. It is a subfield of mathematics that focuses on the dynamics involved in plant and machine operations. It is a theory that has been applied to any automated process. The idea stems from the early 19th century. Based on its history we can further break down control theory into –conventional and modern control. Each of these we will discuss in this article.

Conventional control

This control system covers all the techniques developed prior to 1950. What made the conventional control a significant part of the control system was the invention of the feedback theory, which aimed at stabilizing the system. An example where the feedback theory was applied was in the flyball governor. The fly ball governor was used to stabilize locomotive engines. Another case where it was applied was in the telephone signals. However, it was limited to the distance up to which the signal could travel.
In the conventional controls, an equation was mostly applied. An example was the Laplace transformation, which could express the systems equations in algebraic form for easy manipulations.

Modern control

What adds value to modern control is the ability to use computers to solve the equations in a control system. These methods have become extremely successful, given that they could be easily applied on a computer, and the computer would solve the equations much faster and easier. In addition, computers enabled the system to be easily optimized based on certain metrics.


Well, with the applications of mathematical models, nothing is certain. In every human activity, nothing is guaranteed. There are instances that there is a great deviation from the expected results. What do we do in such instances? In a control system, there are instances that we cannot achieve what we expected. It is bound to happen. What matters is how to deal with these uncertainties.
There are three parameters that catch the attention of control system engineers. These are observability, stability, and controllability. Observability implies that all variables in the system are observed. Controllability affects how a system can be moved from one design to the other, while stability means that the responses of a system can maintain within a system bound.
There are various ways of how to reduce uncertainty in a system. A common way is using stochastic control, which is a probabilistic way of dealing with uncertainties. Uncertainties here are modeled using probability distributions.
The other method which can be utilized to deal with uncertainty is robust control. Let go on and define what robust control is

Robust control

Robust control is the sub-branch of control theory, which deals specifically with the uncertain nature of a system. Robust control provides stability if the uncertainty parameters are found within a certain bound. Their main disadvantage is that they are not sensitive to minor changes in the system.
To elaborate on a robust system, we will consider the case of a car vs. a bicycle. A bicycle is more likely to be affected by the changes in the contours of the road, but a car has a superior suspension and is not likely to be affected by the instability of the road. Therefore, we can say a car is more robust as compared to a bicycle. In short, we can say that the robustness of a system is the sensitivity to the effects not considered in the analysis.

Robust control using Matlab

Matlab is a scientific software capable of handling any challenging task that a student might have. It is installed with all the functions that you might require. Once you have Matlab in your computer system, you will not have the problem of having a new package each and every time for specific purposes. That is why Matlab is very superior when compared to other programming languages such as Python.
The robust control toolbox app in Matlab provides you with all the necessary functions that you will need for a control assignment. The toolbox allows you to perform a robustness analysis. In addition, you can also model and simulate a system.

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