Controls Systems Engineer II

Location: Bridgeton

** Job :*
* ** 114836*
* The Leonardo DRS Land Systems business is a recognized leader in the design and integration of complex technologies into new and legacy systems and platforms for global military and commercial customers. We are a 5 year running Top Workplace in the Greater St. Louis area.

** Job Summary*
* Leonardo DRS Land Systems is seeking a full time Controls Systems Engineer responsible for the analysis, modeling, simulation, implementation support, and verification of stabilized pointing and tracking control for an Electro-Optical and Infrared (EO/IR) sensor and associated gimbal platform on combat vehicles.  This position is based out of our Bridgeton, MO facility and will have the option to work an in person or hybrid schedule.  

This candidate will develop and improve classical feedback control laws to meet technical performance requirements (stability margins, bandwidth, disturbance rejection, tracking error), and will support production verification, integration, and test of planned product improvements as the system matures in early production.  The ideal candidate is knowledgeable in classical and modern control and fosters an innovative work environment leading to improvements in product performance, quality, and productivity.

** Job Responsibilities*
* + Develop, analyze, and refine multi-axis stabilization, pointing, and tracking control laws for precision gimbal/servo systems (e.g., rate and position loops, command shaping)

+ Perform classical control design and verification using frequency-domain methods (Bode/Nyquist), root locus/loop shaping, stability margins, and performance tradeoffs (disturbance rejection vs noise amplification)

+ Create and maintain dynamic plant models capturing key effects (motor/drive dynamics, inertia, friction/backlash, sensor dynamics, structural resonances) and correlate models to test data

+ Support digital/discrete-time control implementation considerations: sampling/discretization, computational delay/latency, quantization, filtering, saturation, and anti-windup

+ Support real-time/embedded implementation of control algorithms and collaborate across software, electrical, and mechanical teams for integration and issue resolution

+ Support architectural design and requirements engineering as they relate to control performance, including allocation and verification of stabilization/tracking requirements

+ Study alternative concepts and use models and simulations to predict closed-loop system performance across operating conditions and disturbance environments

+ Support system integration and test, verification and validation, and production support activities, including test planning support, data review, and control-related corrective actions

+ Communicate effectively with engineers, management, and non-engineering support staff to evaluate technical information and issues impacting design, production, and product support

+ Strive to complete activities on time and budget

+ Perform critical trade studies focused on control performance drivers (sensors/IMU selection impacts, actuator sizing/limits, sampling rates, filtering strategies)

+ Specify and evaluate supplier components, subsystems, and services that affect closed-loop dynamics (IMUs, encoders, motors/drives, isolation/mounting elements)

+ Support the acquisition of hardware and software (or subcontractor services as needed)

+ May provide technical knowledge and assistance to other engineers and support personnel

+ Support, communicate, reinforce and defend the mission, values and culture of the organization

+ Attend appropriate engineering, customer or business meetings

** Qualifications*
* + Bachelor's degree in Engineering, Mathematics, or equivalent

+ 2+ years of experience in classical feedback control design and analysis for physical systems (servo/motion control preferred)

+ Demonstrated expertise in traditional control system theory and application: frequency-domain methods (Bode/Nyquist), root locus/loop shaping, stability margins, and performance tradeoffs

+ Working knowledge of state-space methods (cont rollability/observability, pole placement, observers/estimators) and digital control…