Under the term "automatic control" most people imagine an industrial automated production line, a "smart house", a car, which can park itself and so on. This is however not our field of scope. Neither it is some "smart gadgets", robotic vacuum cleaners, smart apps for smartphones, nor touchscreen displays with Bluetooth and WIFI. Nowadays, the mainstream trend is heading this way and it seems to us, that the global knowledge is drifting away more and more from the underlaying physics nature.
We specialize in an applications, where a hard-real time control is needed. Applications requiring virtually latency free response, not in an order of seconds, nor miliseconds and sometimes neither microseconds. We apply in the fields demaning for very close cooperation: the machine versus the control unit. E.g. In our control of traction motors with DTC, the reaction time is only up to tens of nanoseconds. All this requires the ability to combine engineering in many fields: from design if an output stage, which carries tens of kilowatts, through designing measurement precision analog circuits with AD converters, DSP, FPGA gate arrays, programming and design of operating systems, and finally, to design controllers using control theory. During the development , we try to understand the physical nature of the problem and we constantly adapt our system to allow the control and the plant to really work together.
From the properties and structure of competing products is very often to see how their engineers solve some of the problems that may arise in the operation. Let's look at an example for motor control. If they are are experiencing overloading or even malfunctio of the power stage due to unforeseen circumstances, it is usualy solved by strengthening (oversizing) the output stage, or slowing the command response. This is a classic and apparently effective approach to solve such a problem, and we see this every day in competing produdcts, no matter if it is an industrial controller, EV or UAV controller. However, this "quick" solution implies numerous disadvantages to which their users have become used to, and they don't even expect that it could behave very differently. Really solving this problem, however, means lot more effort in the development. In this area we would like to have something to offer.
By our competitors we very frequently encounter this opinion:
"Once it works, so why to change?" ... Because it can work even better.
In science and technology, we say:
"In practice, the machine works, thanks to our technical feeling, but we do not really understand its essence."
"In theory we will describe the machine with an equation and thereby understand the essence too much, and therefore, nothing really works."
We are trying to find the golden ratio between these two approaches and to fill up the missing gap in between the academic theory and the industry practice.