RESUMO
In traditional hydraulic robotics, actuators must be sized for the highest possible load, resulting in significant energy losses when operating in lower force regimes. Variable recruitment fluidic artificial muscle (FAM) bundles offer a novel bio-inspired solution to this problem. Divided into individual MUs, each with its own control valve, a variable recruitment FAM bundle uses a switching control scheme to selectively bring MUs online according to load demand. To date, every dynamic variable recruitment study in the literature has considered homogeneous bundles containing MUs of equal size. However, natural mammalian muscle MUs are heterogeneous and primarily operate based on Henneman's size principle, which states that MUs are recruited from smallest to largest. Is it better for a FAM variable recruitment bundle to operate according to this principle, or are there other recruitment orders that result in better performance? What are the appropriate criteria for switching between recruitment states for these different recruitment orders? This chapter seeks to answer these questions by performing two case studies exploring different bundle MU size distributions, analyzing the tradeoffs between tracking performance and energetics, and determining how these tradeoffs are affected by different MU recruitment order and recruitment state transition thresholds. The only difference between the two test cases is the overall force capacity (i.e., total size) of the bundle. For each test case, a Pareto frontier for different MU size distributions, recruitment orders, and recruitment state transition thresholds is constructed. The results show that there is a complex relationship between overall bundle size, MU size distributions, recruitment orders, and recruitment state transition thresholds corresponding to the best tradeoffs change along the Pareto frontier. Overall, these two case studies validate the use of Henneman's Size Principle as a variable recruitment strategy, but also demonstrate that it should not be the only method considered.
RESUMO
Biological musculature employs variable recruitment of muscle fibers from smaller to larger units as the load increases. This orderly recruitment strategy has certain physiological advantages like minimizing fatigue and providing finer motor control. Recently fluidic artificial muscles (FAM) are gaining popularity as actuators due to their increased efficiency by employing bio-inspired recruitment strategies such as active variable recruitment (AVR). AVR systems use a multi-valve system (MVS) configuration to selectively recruit individual FAMs depending on the load. However, when using an MVS configuration, an increase in the number of motor units in a bundle corresponds to an increase in the number of valves in the system. This introduces greater complexity and weight. The objective of this paper is to propose, analyze, and demonstrate an orderly recruitment valve (ORV) concept that enables orderly recruitment of multiple FAMs in the system using a single valve. A mathematical model of an ORV-controlled FAM bundle is presented and validated by experiments performed on a proof-of-concept ORV experiment. The modeling is extended to explore a case study of a 1-DOF robot arm system consisting of an electrohydraulic pressurization system, ORV, and a FAM-actuated rotating arm plant and its dynamics are simulated to further demonstrate the capabilities of an ORV-controlled closed-loop system. An orderly recruitment strategy was implemented through a model-based feed forward controller. To benchmark the performance of the ORV, a conventional MVS with equivalent dynamics and controller was also implemented. Trajectory tracking simulations on both the systems revealed lower tracking error for the ORV controlled system compared to the MVS controlled system due to the unique cross-flow effects present in the ORV. However, the MVS, due to its independent and multiple valve setup, proved to be more adaptable for performance. For example, modifications to the recruitment thresholds of the MVS demonstrated improvement in tracking error, albeit with a sacrifice in efficiency. In the ORV, tracking performance remained insensitive to any variation in recruitment threshold. The results show that compared to the MVS, the ORV offers a simpler and more compact valving architecture at the expense of moderate losses in control flexibility and performance.
