Motion Optimization for Musculoskeletal Dynamics: A Flatness-Based Polynomial Approach

作     者：Richter, Hanz Warner, Holly 

作者机构：Cleveland State Univ Dept Mech Engn Cleveland OH 44115 USA 

出 版 物：《IEEE TRANSACTIONS ON AUTOMATIC CONTROL》 (IEEE自动控制汇刊)

年 卷 期：2021年第66卷第7期

页      面：3289-3295页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 

基　　金：National Science Foundation, Cyber-Physical Systems Program Direct For Computer & Info Scie & Enginr Division Of Computer and Network Systems Funding Source: National Science Foundation 

主　　题：Muscles Optimization Force Dynamics Optimal control Tendons Trajectory Biomechanics computational efficiency cyber-physical systems mathematical programming motion planning optimal control 

摘      要：A new approach for trajectory optimization of musculoskeletal dynamic models is introduced. The model combines rigid-body and muscle dynamics described with a Hill-type model driven by neural control inputs. The objective is to find input and state trajectories that are optimal with respect to a minimum-effort objective and meet constraints associated with musculoskeletal models. The measure of effort is given by the integral of pairwise average forces of the agonist-antagonist muscles. The concepts of flat parameterization of nonlinear systems and sum-of-squares optimization are combined to yield a method that eliminates the numerous set of dynamic constraints present in collocation methods. With terminal equilibrium, optimization reduces to a feasible linear program, and a recursive feasibility proof is given for more general polynomial optimization cases. The methods of the article can be used as a basis for fast, and efficient solvers for hierarchical, and receding-horizon control schemes. Two simulation examples are included to illustrate the proposed methods.