Pressure and Force Dynamics in Artificial Muscle Actuators: A State-Space and Optimization-Based Approach

This two-part investigation explores the dynamic behavior of braided pneumatic actuators (BPAs) under bio-inspired pulse modulation, with the aim of improving their biomimetic force output and control. The first study examines the effect of pulse length and inter-pulse timing on BPA performance, revealing that force output is highly sensitive to the temporal structure of input pulses mirroring biological muscle behavior. Using dual-pulse actuation schemes, the results demonstrate that force responses exceed the additive contributions of individual pulses, with peak amplification occurring consistently at a 27 ms inter-pulse gap. Shorter pulse lengths (10–20 ms) yielded the highest normalized force increases, up to 3.55 times greater than a single pulse, highlighting the nonlinear summation properties of BPAs under pulse modulation. Building on these findings, the second study develops a state-space model to predict pressure dynamics based on valve actuation inputs, incorporating three spring-damper-mass systems to represent the distributed air volume and its mechanical effects. Parameters were optimized via Particle Swarm Optimization (PSO), achieving predictive pressure errors between 5-16% across three muscle lengths (600 mm, 310 mm, and 140 mm). A nonlinear model was then used to correlate pressure with force output, with fitting errors below 3%. Key insights indicate that longer BPAs yield higher peak forces and smoother decay profiles due to their larger internal volumes, while shorter BPAs respond more rapidly but require higher pulse frequencies to sustain force output. Together, these works establish a foundation for the real-time control and simulation of BPAs using biologically inspired actuation patterns. The combination of empirical pulse modulation data and validated dynamic models enables more adaptable and efficient actuator control strategies, applicable to soft robotics and human-assistive devices.

Publication Details

Journal
PDXScholar (Portland State University)
Published
2025-08-28
Primary Topic
Geochemistry and Geologic Mapping
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article
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article

Pressure and Force Dynamics in Artificial Muscle Actuators: A State-Space and Optimization-Based Approach

PDXScholar (Portland State University)
Geochemistry and Geologic Mapping
article

Pressure and Force Dynamics in Artificial Muscle Actuators: A State-Space and Optimization-Based Approach

article en

Abstract

This two-part investigation explores the dynamic behavior of braided pneumatic actuators (BPAs) under bio-inspired pulse modulation, with the aim of improving their biomimetic force output and control. The first study examines the effect of pulse length and inter-pulse timing on BPA performance, revealing that force output is highly sensitive to the temporal structure of input pulses mirroring biological muscle behavior. Using dual-pulse actuation schemes, the results demonstrate that force responses exceed the additive contributions of individual pulses, with peak amplification occurring consistently at a 27 ms inter-pulse gap. Shorter pulse lengths (10–20 ms) yielded the highest normalized force increases, up to 3.55 times greater than a single pulse, highlighting the nonlinear summation properties of BPAs under pulse modulation. Building on these findings, the second study develops a state-space model to predict pressure dynamics based on valve actuation inputs, incorporating three spring-damper-mass systems to represent the distributed air volume and its mechanical effects. Parameters were optimized via Particle Swarm Optimization (PSO), achieving predictive pressure errors between 5-16% across three muscle lengths (600 mm, 310 mm, and 140 mm). A nonlinear model was then used to correlate pressure with force output, with fitting errors below 3%. Key insights indicate that longer BPAs yield higher peak forces and smoother decay profiles due to their larger internal volumes, while shorter BPAs respond more rapidly but require higher pulse frequencies to sustain force output. Together, these works establish a foundation for the real-time control and simulation of BPAs using biologically inspired actuation patterns. The combination of empirical pulse modulation data and validated dynamic models enables more adaptable and efficient actuator control strategies, applicable to soft robotics and human-assistive devices.

PDXScholar (Portland State University)
Openalex Percentile: Top 32%
Geochemistry and Geologic Mapping
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