Actuator Control System Using Biological Muscle Model
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Solution Overview
Problem
Current actuator technologies for prosthetics and robotics lack the ability to mimic the complex, nonlinear behavior of biological muscle actuation, particularly in terms of force generation and energy storage, which is crucial for natural movement and efficiency.
Innovation Solution
The development of an actuator control system that utilizes a mathematical model of biological muscle actuation, specifically modeling titin as a filament winding around actin, incorporating a contractile element, viscous damping, and a spring in series and parallel configurations, to generate forces and control movements similar to biological muscles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional motorized actuators are used, then the device can perform basic movement functions, but it cannot mimic the complex nonlinear behavior of biological muscle actuation
Solution Approach 1:
The patent applies the copying principle by creating a mathematical model that replicates the nonlinear behavior of biological muscle actuation. The control algorithm copies the force-velocity relationship, energy storage characteristics, and titin filament winding dynamics of real muscles, allowing the actuator to mimic biological movement patterns without requiring complex mechanical structures.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting control parameters based on the mathematical model of muscle actuation. The system varies force generation parameters, damping coefficients, and spring constants to replicate different muscle states and movement conditions, enabling adaptive behavior across various operating ranges.
2Adaptability or versatility
If a simple control algorithm is used, then the device is easier to control, but it cannot simulate the nonlinear properties of muscle actuation
Solution Approach 1:
The patent introduces a mathematical model as an intermediary between the simple motorized actuator and the desired complex muscle-like behavior. This intermediary layer translates simple control inputs into sophisticated force generation patterns that mimic muscle actuation, including nonlinear elasticity, viscosity, and energy storage/release mechanisms.
Solution Approach 2:
The patent replaces complex mechanical muscle-mimicking structures with a computational approach. Instead of using intricate mechanical linkages, springs, and dampers to physically replicate muscle behavior, the system uses a mathematical model within the control algorithm to simulate these effects through software-based force generation and damping control.
3Productivity
If biological muscle modeling is implemented, then movement becomes more natural and efficient, but energy consumption increases due to complex control computations
Solution Approach 1:
The mathematical model of muscle actuation enables the actuator to self-regulate its energy consumption by mimicking the natural efficiency characteristics of biological muscles. The model automatically adjusts force generation and energy storage based on movement requirements, optimizing energy usage without requiring external intervention or complex power management systems.
Solution Approach 2:
The system performs preliminary energy storage in the modeled spring element before actual movement is required. By pre-charging the elastic energy storage mechanism through the mathematical model, the actuator can execute movements more efficiently by releasing stored energy rather than continuously consuming power, similar to how biological muscles store and release elastic energy.
4Reliability
If a mathematical model with multiple elements (contractile element, viscous damping, spring) is used, then the actuation behavior becomes more accurate, but the device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the muscle actuation model into distinct functional elements: a contractile element for force generation, a viscous damping element for resistance control, and a spring element for energy storage. Each element is modeled separately with its own mathematical relationships, allowing the complex overall behavior to be constructed from simpler, well-understood components.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for more natural and efficient movement by simulating the nonlinear properties of muscle actuation, enhancing the performance of prosthetics and robotic devices in tasks such as walking and stair ascent, while reducing energy consumption and improving compliance with varying forces.
Implementation Method 1
a spring in series with the contractile element through a pulley and simultaneously in parallel with the contractile element
Implementation Method 2
a viscous damping element in parallel with the contractile element
Data Source
AI summary
An actuator control system includes a motorized joint having first and second members rotatable relative to one another. An actuator is coupled with the motorized joint and is configured to rotate the first member relative to the second member in response to an input including a voltage, a current, or any combination thereof. A controller is coupled with the actuator and is configured to control the input using a control algorithm. The control algorithm controls the input based upon a mathematical model of biological muscle actuation that models titin as a filament which winds around actin during muscle actuation. In implementations the mathematical model includes mathematical representations of a contractile element, a viscous damping element in parallel with the contractile element, and a spring in series with the contractile element through a pulley and simultaneously in parallel with the contractile element.