Conceptualization, Modeling and Control of a Novel Coil-Less Magnetic Actuation Technology based on Reluctance Tuning

Abstract

Conventional and state-of-the-art Coil-based Hybrid Reluctance Actuators (CB-HRAs) for precision motion control are well-regarded for their high force generation but notorious for Joule heat dissipation. This coil-based heat generation problem compromises the quality and effectiveness of precision engineering applications, especially in vacuum, space and cryogenic environments. This research focuses on exploring and advancing the capabilities of the Hybrid Tunable Reluctance Actuator (HTRA) as a novel alternative for coil-less, contactless and high-force actuation. The working principle is based on reluctance tuning, i.e. changing the actuator’s internal properties to generate contactless magnetic force on a mover. This research develops methodologies to design, classify, and evaluate optimal force-generating HTRAs using analytical and numerical magnetic models. In symphony with this process, novel concepts and mathematical statements in reluctance tuning are created to explain key results and establish standard design principles for generic HTRAs. The resulting optimal HTRA design is analytically evaluated against CB-HRAs to benchmark and confirm the potential of HTRAs in force generation and power dissipation for different actuation forms. The research further progresses into numerically modeling key nonlinear magnetic effects to refine the HTRA’s design. Subsequently, numerically-verified multibody dynamical models are developed to accurately simulate inherently nonlinear and complex HTRAs, while ensuring these models can be generally extrapolated. The proof-of-concept is obtained on a manufactured HTRA setup, followed by experimental validations of the multibody dynamical models through system identification. Finally, the first linear control system for an HTRA is synthesized based on real-time data to explore its achievable bandwidths, position reference tracking abilities, and other closed-loop performance parameters using feedback, feedforward and delay compensation techniques.