About us
We develop intelligent solutions for reliable and efficient energy control
Our services:
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Advanced control strategies for industrial power electronics, electric drives, and power generation
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Digital twin development for power electronics and model-based design (MBD)
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Synthesized data for predictive maintenance using digital twins
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Fault investigations in electromechanical systems using MBD
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Optimization study for BESS-based microgrids, enabling up to 20% CAPEX savings
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Energy Management System (EMS) development for BESS-based microgrids
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HIL (Hardware-in-the-Loop) testbeds development (SW, HW) and RCP (Rapid Control Prototyping)
Experience.Hardware:
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HIL and RCP hardware:
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Typhoon HIL: HIL404, HIL604, HIL606
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dSPACE: SCALEXIO, Microlabbox
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Speedgoat Performance Real-Time Target Machine
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Advantech PCI extension boards + Simulink Desktop Real-Time
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Embedded systems (automatic C-code generation using Simulink):
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Texas Instruments processors C2000: F28388D, F28379D, F28027, F2812
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NXP ARM Cortex-M3
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FPGA programing using Simulink:
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Xilinx Kintex-7
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Xilinx Kintex UltraScale+
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Linux hardware:
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Raspberry Pi 4
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Cloud interface:
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Grafana
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Experience.Software:
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Matlab:
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Simulink
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Simscape (Specialized Power Systems, Electrical, Driveline etc)
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Control System Toolbox
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Robust Control Toolbox
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Simulink Control Design
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Simulink Design Optimization
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Simulink Desktop Real-Time
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Simulink Real-Time
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Stateflow
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Embedded Coder
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C2000 Microcontroller Blockset
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HDL Coder
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Instrument Control Toolbox
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Powertrain Blockset
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Statistics and Machine Learning Toolbox
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Predictive Maintenance
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App Designer
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Typhoon HIL:
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Schematic editor
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HIL SCADA
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Additional tools
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PLECS:
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Standalone software
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PLECS Blockset
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Control System Design:
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Power Electronics:
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Battery energy storage systems (AFE, PFC for SiC- and IGBT-based applications, including grid-forming and grid-following control)
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AC and DC electric drives
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Energy generation systems (MPPT, excitation systems of generators)
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Electrical converters on different topology
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Energy management systems for microgrids
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Features:
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Feed-back PID control / Feed-forward control
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Predictive control
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Decoupling matrix for feedback controllers calculated using H-infinity optimization method. This is one of approaches provides the robustness of the control system
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Additional stabilization channels
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Injection special signals for on-line parameters identification
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Control system tuning and improving performances
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Plant parameters estimation using measured data
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HIL testing and RCP approaches
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