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... to my personal web page. My name is DobromiƂ Duda and using often alternative nick name as Antypodish.

Here I am presenting range of my life involvements and commitments, over prolong period of time. From hobby, to study, to work.

I have range of interests, from robotics, artificial intelligence (AI), programming (various languages), web designing, via 2D and 3D graphics, to photography and travelling, to name just few.

This website was created initially many years ago, as part of my hobby, with learning web design in mind, rather than using ready to go templates. Hence it contains lots of experimental features. Since then, it evolved by much. Yet I am aware, it may be far from ideal, but is functional never the less. I have some projects however, where ready solutions were rather used, for fast implementations.

My mind is rather technically oriented and I love new tech. Not that I can not do something less techy from time to time :)

Many things I present here, is part of my hobby. But I also got here some extra bits, reaching beyond that scope too.


Since you are on my home page and you can see only few latest updates, I suggest jump to project section and feel free to explore one of available categories, of your interest. Hope you may find something interesting, or even inspiring.


Beyond that, I would like to thank you for your time, visiting my website :)




Author: Antypodish
Posted: 2020-05-25 22:57:22

Default power grid system response without neural network


System reacting immediately to power demand change



Red dashed line, indicates changes in power demand, in span of 24 hours.
Light blue line indicates total power generation, with visible power deficiency at peak times 5-10 AM and 15-19 PM, caused by late response of power generation, by large (blue dashed line) and small (purple dashed line) power stations.
Each power station has own time response, of how fast it can change its output.


While for untrained system example, total power generation cost is lower, than for neural network trained system, in normal cases, positive power demand (green dashed / pink lines) would cause blackouts.
Possible solution, is to increase absolute margin, at which power must be generated. Or encourage system, to increase power production earlier, before peaks.

NN can come with an aid, to assist with a problem.

Trained data using Genetic Neural Network


It need to be noted, that there is place for improvement, on training this system.



Neural network trained systems shows, that no positive power deficiency is present, at cost of higher power output.
However, system attempts to respond to power demand changes, specially by predicting peak times.
System also reacts, to changes of solar power generation output, by reducing power generation from small and large power station.



Example of 80 simultaneously trained Power Grid systems.



NN uses 3 sets of layers. 26 nodes in input layer, which takes current power production - power demand, total power generation cost, and 24 inputs as on / off state per each hour.

2 nodes in output layer, which corresponds to power generation setpoint.

Hidden layer, of vary count of nodes, depending on trained net. Number of hidden layer nodes is independent from design definition and its setup can dynamically change during training. NN Training depending on complexity and parameters, may last from few minutes, to few hours.






Author: Antypodish
Posted: 2019-07-31 22:57:22

Room



Mobile





Author: Antypodish
Posted: 2019-07-31 22:16:47

ITP - Current to Preasure



Kaytola Flow Meters



Pneumatic Valve








Author: Antypodish
Posted: 2019-07-31 22:07:34

GEM80



PILOT80 - GEMCAD



HPCi



Mitsubishi



Siemens S7








Author: Antypodish
Posted: 2019-07-31 21:58:43

WAGO 750 I-O - MBE driver



IGS OPC



Wago - PLC registry mapping








Author: Antypodish
Posted: 2019-07-31 21:16:30

Failsafe shutdown triggers



Salt Saturators & Brain Pumps



System pumps



Network system overview



Plant startup shutdown sequence



New alarms layout - filtering feature



Links - developed schedule - automation



Trending - Data Analysis







SCADA, HPCI / GEM80 PLCs, Ethernet - COM Port Converters.


Author: Antypodish
Posted: 2019-07-31 09:33:05





Large image


Author: Antypodish
Posted: 2019-07-31 03:40:34






Author: Antypodish
Posted: 2019-07-31 01:23:44

I used Matlab and Simulink with additional libraries, to be able achieve such results, of HydroLek gripper.




Over Weekend Unity Gripper Contact Surface Project


Author: Antypodish
Posted: 2019-07-31 01:17:53

Goal of this mini over weekend project, was to test and simulate contact surface sensors. I used Unity to simulate sensors, and to find most suitable orientation for gripper, based on detected surfaces of the object. As an operator, I was changing only faces to pick, polarity and alternate option.