Toward lower limbs movement restoration with input–output feedback linearization and model predictive control through functional electrical stimulation

2012 ◽  
Vol 20 (2) ◽  
pp. 182-195 ◽  
Author(s):  
S. Mohammed ◽  
P. Poignet ◽  
P. Fraisse ◽  
D. Guiraud
Keyword(s):  
Electrical Stimulation ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Functional Electrical Stimulation ◽  
Output Feedback ◽  
Feedback Linearization ◽  
Lower Limbs ◽  
Input Output

scholarly journals Convergence Guaranteed Nonlinear Constraint Model Predictive Control via I/O Linearization

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Xiaobing Kong ◽  
Xiangjie Liu ◽  
Xiuming Yao
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Output Feedback ◽  
Feedback Linearization ◽  
Optimal Solution ◽  
Quadratic Program ◽  
Control Input ◽  
Input Output ◽  
Nonlinear Constraint ◽  
Constraint Model

Constituting reliable optimal solution is a key issue for the nonlinear constrained model predictive control. Input-output feedback linearization is a popular method in nonlinear control. By using an input-output feedback linearizing controller, the original linear input constraints will change to nonlinear constraints and sometimes the constraints are state dependent. This paper presents an iterative quadratic program (IQP) routine on the continuous-time system. To guarantee its convergence, another iterative approach is incorporated. The proposed algorithm can reach a feasible solution over the entire prediction horizon. Simulation results on both a numerical example and the continuous stirred tank reactors (CSTR) demonstrate the effectiveness of the proposed method.

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