Ralph Kennel
Papers
5
Total Citations
127
H-Index
4
About
Ralph Kennel is a leading figure in advanced motor control and power electronics, whose work bridges theoretical innovation and practical industrial robotics. His primary research areas include model predictive control (MPC) for multiphase electric machines, funnel control for robotic manipulators, and high-precision frequency measurement under noisy conditions. Kennel’s most impactful contribution is his 2021 work on space-vector-optimized predictive control for dual three-phase permanent magnet synchronous machines (DTP-PMSMs), which has garnered 78 citations. This research provides a breakthrough method to suppress current harmonics in low-inductance motors, enabling faster and more efficient current response—critical for electric vehicle and industrial drive applications. He also pioneered position funnel control for rigid robotic manipulators (28 citations), a technique that guarantees prescribed transient accuracy without requiring complex system models, simplifying real-time control. Additionally, Kennel has advanced signal processing with cross-correlation frequency measurement methods for low signal-to-noise ratios (11 citations), enhancing sensor reliability in harsh environments. His work on risk assessment for active lower-limb exoskeletons (2020) further demonstrates his commitment to safe human-robot interaction. With a career spanning precise motor control to robotic safety, Kennel’s research continues to shape the next generation of intelligent, responsive electromechanical systems.
Research Focus
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Top Papers
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