1,721,032 research outputs found
Robust Control Design for Electrical Stimulation Electrode Arrays
No full textElectrical stimulation electrode arrays are an emerging technology that enables muscles to be artificiallyactivated to assist human motion for orthotic or therapeuticpurposes. This paper develops robust performance marginsquantifying feedback controller tracking performance in thepresence of disturbance and modeling mismatch. These are thenapplied to formulate control design procedures that address the practical difficulty of obtaining an accurate model
Newton-method based iterative learning control for robot-assisted rehabilitation using FES
No full textPrecise control of useful movement is critical in providing effective upper limb stroke rehabilitation using functional electrical stimulation (FES). To address the lack of accuracy currently available in clinical practice, this paper develops a general framework based on iterative learning control, an advanced model-based approach that has been successfully employed in three clinical treatment trials. An upper limb model is first developed to encompass unconstrained movements of the upper arm, with, in line with clinical need, additional assistance incorporated via a general class of robotic support mechanism. An iterative learning scheme is then developed to enable a subset of joint angles to be controlled via stimulation of an arbitrary set of muscles. This scheme is the first ILC approach which explicitly addresses coupled multivariable nonlinear dynamics in rehabilitation, enforcing convergence over multiple repetitions of a reaching task. Experiments with six participants confirm practical utility and performance
A Novel Design Framework for Point-to-Point ILC Using Successive Projection
No full textA novel design approach is proposed for point-to-point iterative learning control (ILC), enabling system constraints to be satisfied while simultaneously addressing the requirement for high-performance tracking. It is shown that point-to-point ILC design can be formulated and solved using a successive projection first proposed by J. von Neumann, allowing a number of new point-to-point ILC algorithms to be developed and analyzed. To illustrate this framework, two new algorithms are derived with different convergence and computational properties for the constrained point-to-point ILC design problem. The proposed algorithms are validated on a robotic arm with experimental results demonstrating their effectiveness
Phase-lead based iterative learning control implemented experimentally on a non-minimum phase plant
No full text
Further results on the experimental evaluation of iterative learning control algorithms for non-minimum phase plants
No full textThis paper builds on previous work in which simple structure ILC algorithms were experimentally evaluated on a non-minimum phase plant. The phase-lead update law, the most promising of those implemented, is examined using an established performance criterion. The use of a forgetting factor is found to overcome the problem of instability, but at the expense of increased final error. This is verified through experimentation. The phase-lead algorithm is improved using additional phase-leads to remove the instability and improve convergence and final error. This technique is generalized to produce an optimization routine which leads to greatly improved results. The learning law utilizing the plant adjoint is found to fit naturally into this framework and practical results are presented to compare their respective performance. This algorithm, which requires a model of the plant, is reformulated into one which does not. Results are presented using this technique and practical guidelines are produced and tested to improve its performance. A simple method of increasing the learning at higher frequencies is proposed and practical limitations are addressed and verified experimentally. All the algorithms tested are compared with respect to their performance, practicality and robustness
Progress and open questions in the identification of electrically stimulated human muscle for stroke rehabilitation
No full text- …
