Nonlinear model predictive control of functional electrical stimulation

Application of Newton/GMRES Method to Nonlinear Model Predictive Control of Functional Electrical Stimulation

Recent studies have shown that functional electrical stimulation (FES) therapy can improve the motor recovery and range of the motion of stroke patients. The state-of-the-art functional electrical stimulators are open-loop control systems, i.e., the controller is unaware of the patient’s posture and progress during the therapy. In this research, we have developed a closed-loop Newton/GMRES nonl...

Improved Optimization Process for Nonlinear Model Predictive Control of PMSM

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

Nonlinear Model Predictive Control

Genetic Feedforward-Feedback Controller for Functional Electrical Stimulation Control of Elbow Joint Angle

Background: Functional electrical stimulation (FES) is the most commonly used system for restoring functions after spinal cord injury (SCI). Objective: In this study we investigated feedback PID and feedforward-feedback P-PID controllers for regulating the elbow joint angle. Methods: The controllers were tuned based on a nonlinear muculoskeletal model containing two links, one joint with one de...

Nonparametric Nonlinear Model Predictive Control

−Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impeded by linear models due to the lack of a similarly accepted nonlinear modeling or databased technique. Aimed at solving this problem, the paper addresses three issues: (i) extending second-order Volterra nonlinear MPC (NMPC) to higher-order for improved prediction ...