Our specific control system approach will eventually integrate with our geospatial data mapping software on the Cesium platform that will allow us to later integrate real environment information collected by vehicles and other sources that can provide real time data like airspace activity. This will also allow for elaborate flight planning and unparalleled real time situational awareness of any vehicle from cars, planes, drones to rockets. This level of situational awareness coupled will the vehicle sensor fusion will inherently give great coordination and allow for the data collection of swarms to be compiled into a real time environment model.
Ground Control Station simulation showing active controls over the vehicle (left) and world view for flight visualization (right)
Ground Control Station simulation demonstrating swarm coordination (left) and real-time environmental model forming (right)
Draft layout subject to change
BCav Systems DAQ Control Prototype
Custom designed PCB utilizing 2 Qty 8-Channel differential 24-Bit ADCs that each have 4 GPIO expansion pins that I use to drive a total of 8 Solid State Relays (SSR). These ADC’s will be used to directly read analog signals of 0.5V - 5V for all our pressure sensors in the propulsion system. Our thermocouples will be amplified by an external amplifier before hooking into this mainboard allowing it to read both pressures and temperatures.
Accompanying the array of DAQ sensors is the NEO-M8U Untethered Dead Reckoning (UDR) chip produced by U-Blox. This powerful unit will be used to derive the vehicle's relative position with great accuracy. A pressure sensor has also been added to provide the capability of recovery system control output with ease.
Each SSR has a very low power consumption of 1mA, resistance to mechanical vibration, and a large power throughput rating of 60V @ 4A on average peaking up to 9A.
This board still depends on the Raspberry Pi processor. and connection abilities. I do plan to give the board its own processor in the future.