摘要
给出了离散系统D 型迭代学习控制算法收敛的一种充分条件 ,并加以证明 .采用D型迭代学习控制算法 ,对基于功能性神经肌肉电刺激的曲腕和曲肘运动进行了临床实验研究 ,结果表明 ,D型迭代学习算法改善了FNS肢体运动控制的跟踪性能 ,曲肘和曲腕运动轨迹平滑、稳定 ,并且刺激控制脉冲变化平缓 ,受试者无任何不良生理反应 .
A new sufficient condition proof for the convergence of D type iterative learning control algorithm is provided and the clinical experiments applied to the control of both elbow flexion and wrist flexion with function neuromuscular stimulation (FNS) is given by means of D type iterative learning control method. The results of clinical studies have demonstrated that D type iterative learning control algorithm is suitable for improving the dynamic response characteristics and stabilizing the limb motion. Furthermore, the stimulated patient does not have any bad physiological reactions because the output electrical stimulation pluses vary gently.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2001年第3期409-413,共5页
Control Theory & Applications
