FPGAs for power electronics
Abaxor engineering has a long history of power electronics projects based on FPGAs. We can therefore excel in this field due to our broad experience.
The short switching times of modern power transistors can be used effectively through the use of FPGAs' computational performance. FPGAs can count and switch every clock cycle, where processors may only accommodate this by instructions and interrupts. With this behaviour, jitter is effectively reduced. The parallel processing in FPGAs allows the signal processing, the automatic sequence control (FSM), and the monitoring and control of signals to be computed concurrently. These features make FPGAs a perfect platform for the implementation of algorithms like switching amplifiers or regulators, or piezo controllers.
Controllers for piezo actuators
Piezo actuators exhibit strongly non-linear characteristics. Hence, commonly used controllers for linear systems are not applicable for them. DSPs, which are often used to control piezos, provide a good support for linear algorithms like FIR filters because the required multiply-accumulate operations can be directly mapped to hardware. FPGAs provide a better fit to non-linear algorithms due to the large degrees of freedom in their configuration. Even low-cost FPGAs with still more than ten hardware multipliers offer more computational power than DSPs. Therefore, FPGAs permit more complex algorithms and enable new, more efficient control concepts.
Controllers for switching regulators
Today's constraints on switching regulators are constantly increasing: higher desired currents and less ripple at smaller output voltages and a higher integration density are required. Digital controllers ease the realization of these growing demands. FPGAs provide a higher computational power because of their truly parallel execution units. Monitoring functions can be implemented in the FPGA and utilize its short response times. The integration density of the switching regulator increases, and the PCB design decreases in complexity.