Abstract
Pneumatic muscle actuators (PMAs) own compliant characteristics and are suitable for use in rehabilitation equipment. This paper introduces a rehabilitation robot driven by PMAs devised in the Rehabilitation and Medical Robot Laboratory. Considering high nonlinearities inside PMAs, a single neuron tuned PID controller is carefully designed. Experimental setup is built up and trials are performed. Results demonstrate the proposed advanced PID algorithm can achieve better capacity in position tracking than the conventional PID controller.
Highlights
Features of physiological function recession in aging process include decreased limb flexibility, osteoporosis, muscle atrophy, and significant decline in loading capacity of bone tissue. e incidence of acute cardiovascular and cerebrovascular diseases and that of neurological diseases in the aged keep at a high level, and most of these patients have symptoms of hemiplegia [1, 2]
To validate the effectiveness of the proposed single neuron tuned PID algorithm, several trials are conducted under different excitation
It is generally known that passive rehabilitation therapy is used for serious dyskinesia of limbs and must operate
Summary
Features of physiological function recession in aging process include decreased limb flexibility, osteoporosis, muscle atrophy, and significant decline in loading capacity of bone tissue. e incidence of acute cardiovascular and cerebrovascular diseases and that of neurological diseases in the aged keep at a high level, and most of these patients have symptoms of hemiplegia [1, 2]. Quantity of patients with limb dyskinesia caused by other diseases, sports injury, and traffic accidents is increasing rapidly For these patients, besides early surgical treatments and necessary medications, correct and scientific rehabilitation training plays an important role in restoration and improvement of limb motion functions [3]. Wu et al designed a three-degrees-of-freedom lower rehabilitation robot involving hip, knee, and ankle joints and proposed an adaptive robust subcontroller for the robot to handle system uncertainties and disturbances from patients [14] Banala et al developed a robot-assisted gait training algorithm and used a force-field controller to achieve more effective training [15]. Complexity limb rehabilitation robot, and gradient descent algorithm was adopted to tune impedance parameters to guarantee force controlling effect [30].
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