Feedback control of the neuromusculoskeletal system in a forward dynamics simulation of stair locomotion

Abstract The aim of this study is to employ feedback control loops to provide a stable forward dynamics simulation of human movement under repeated position constraint conditions in the environment, particularly during stair climbing. A ten-degrees-of-freedom skeletal model containing 18 Hill-type musculotendon actuators per leg was employed to simulate the model in the sagittal plane. The postural tracking and obstacle avoidance were provided by the proportional—integral—derivative controller according to the modulation of the time rate change of the joint kinematics. The stability of the model was maintained by controlling the velocity of the body's centre of mass according to the desired centre of pressure during locomotion. The parameters of the proposed controller were determined by employing the iterative feedback tuning approach to minimize tracking errors during forward dynamics simulation. Simultaneously, an inverse-dynamics-based optimization was employed to compute a set of desired musculotendon forces in the closed-loop simulation to resolve muscle redundancy. Quantitative comparisons of the simulation results with the experimental measurements and the reference muscles' activities illustrate the accuracy and efficiency of the proposed method during the stable ascending simulation.