State Estimation Controls Engineer at Virgin Hyperloop
The 21st century challenges are here, and we need 21st century solutions. As we continue to progress hyperloop from home, we are actively hiring for open roles. The interview process will continue online to ensure safety during the COVID-19 pandemic.
Stay safe and be well,
The Virgin Hyperloop team
The Electromagnetic Systems division is responsible for the design and development of the Hyperloop Propulsion Motor, Levitation and Guidance Systems. These systems are electromechanical in nature and are designed by a highly cross-functional team of exceptional engineers in the areas of Electromagnetics, Mechanical Design, Heat Transfer, Materials Science, Testing, Controls, Embedded Systems, and Electrical System Modeling. We are seeking candidates with broad skillsets and various levels of experience to join our team of qualified, diverse individuals and work on one of the most challenging transportation applications on Earth, from right here at our Los Angeles facility.
State estimation and sensor fusion design for control of pod motion. This entails grouping multiple redundant sensors for the purposes of throttling, braking, docking, levitation, and guidance in safety critical systems. The candidate will work in the Vehicle Motion Control Group and ultimately be responsible for generating the set of state estimators that will provide accurate and precise feedback to control the motion of the pod. Candidate will also generate and codify the safe operating regimes and high-level safety algorithms for the pod from the perspective of the feedback for the propulsion motor, braking systems, levitation and guidance modules.
- Development of fault tolerant safety critical motion sensor architecture, selection and integration with FBW system of passenger rated vehicle (small gap non-contact displacement, IMU, LIDAR and other rangefinding). These sensors will comprise the full set of required sensors for flight
- Protection and monitoring functions and algorithm generation
- State estimation algorithms generation
- Managing interfaces with embedded systems team, safety and systems team, flight controls algorithm team, mechanical design team and power electronics team
- Design, implementation, experimentation, and optimization of state estimation and sensor fusion techniques for the purposes of motion control
- Safety and reliability analysis of state estimation and feedback techniques
- Design of voting algorithms for redundant/resilient feedback systems
- Interface with other Controls Engineers, Embedded Systems, Propulsion and Power Electronics teams.
- Works well in a team
- Enjoys collaboration with in domains outside of area of expertise
- Quick learner
- Able to step out of comfort zone (technically and professionally) frequently
- Thrives in an environment where requirements and expectations shift rapidly
MINIMUM REQUIRED EXPERIENCE:
- Minimum of a Master’s degree focused on controls or digital signal processing
- Experience with implementation of statistical estimation techniques (Kalman, extended Kalman, scented/unscented Kalman; other observer based methods)
- Experience with implementation of sensor fusion with heterogenous sensors for vehicle/aircraft motion control
- Experience with digital signal processing and sensor fusion
- Experience with implementation of classic, optimal, robust, and adaptive control techniques and implementation (loop-shaping, Lyapunov, H-infinity, sliding mode control, LQG/LTR, model adaptive identification controllers, fuzzy-logic, etc)
- Expert in Matlab, Simulink, Stateflow
- Experience with configuration management tools (GIT or similar)
- Deep understanding of mechanical, electromagnetic and power electronics systems
Additional background in the following would be helpful:
- Power electronics, electromagnetic transducers, and vehicle dynamics analysis and modeling
- MIMO control of highly redundant systems
- Low level implementation of digital controllers
- Flexible mode analysis in the context of motion control
- Validating computational models through experimental data analysis and system identification
- Experience with systems and controls documentation (Logical flow charts, sequence diagrams, etc.)
- Completion of at least two commercial vehicle programs (manned/un-manned; drones or transportation) or motion control products (in robotics, automation/fabrication, machine tools) with a leadership role in sensor integration and calibration.
- PhD in Mechatronics or EE with emphasis on state estimation and control