Asymptotic Properties of the Discrete Minimum Variance Output Feedback Control Law.

1977 ◽  
Author(s):  
Albert B. Chammas ◽  
Cornelius T. Leondes
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Asymptotic Properties ◽  
Output Feedback Control ◽  
Minimum Variance ◽  
Control Law

Predictor-Based Adaptive Output Feedback Control: Application to Functional Electrical Stimulation of a Human Arm Model

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Chuong H. Nguyen ◽  
Alexander Leonessa
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
Output Feedback ◽  
Reference System ◽  
Mimo Systems ◽  
Output Feedback Control ◽  
Control Law ◽  
Human Arm ◽  
System Output ◽  
Asme Paper

A simulation study to control the motion of a human arm using muscle excitations as inputs is presented to validate a recently developed adaptive output feedback controller for a class of unknown multi-input multi-output (MIMO) systems. The main contribution of this paper is to extend the results of Nguyen and Leonessa (2014, “Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems,” ASME Paper No. DSCC2014-6214; 2014, “Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Linear Systems: Experimental Results,” ASME Paper No. DSCC2014-6217; and 2015, “Adaptive Predictor-Based Output Feedback Control for a Class of Unknown MIMO Systems: Experimental Results,” American Control Conference, pp. 3515–3521) by combining a recently developed fast adaptation technique and a new controller structure to derive a simple approach for a class of high relative degree uncertain systems. Specifically, the presented control approach relies on three components: a predictor, a reference model, and a controller. The predictor is designed to predict the systems output for any admissible control input. A full state feedback control law is then derived to control the predictor output to approach the reference system. The control law avoids the recursive step-by-step design of backstepping and remains simple regardless of the system relative degree. Ultimately, the control objective of driving the actual system output to track the desired trajectory is achieved by showing that the system output, the predictor output, and the reference system trajectories all converge to each other. Thelen and Millard musculotendon models (Thelen, D. G., 2003, “Adjustment of Muscle Mechanics Model Parameters to Simulate Dynamic Contractions in Older Adults,” ASME J. Biomech. Eng., 125(1), pp. 70–77; Millard, M, Uchida, T, Seth, A, and Delp, Scott L., 2013, “Flexing Computational Muscle: Modeling and Simulation of Musculotendon Dynamics,” ASME J. Biomech. Eng., 135(2), p. 021005) are used to validate the proposed controller fast tracking performance and robustness.

scholarly journals Dynamic output nonfragile reliable control for nonlinear fractional-order glucose–insulin system

2020 ◽  
Vol 25 (2) ◽  
Author(s):  
Rathinasamy Sakthivel ◽  
Hari Hara Subramanian Divya ◽  
Saminathan Mohanapriya ◽  
Yong Ren
Keyword(s):  
Blood Glucose ◽  
Feedback Control ◽  
Fractional Order ◽  
Output Feedback ◽  
Output Feedback Control ◽  
Disturbance Attenuation ◽  
Control Law ◽  
Reliable Control ◽  
Dynamic Output Feedback ◽  
Dynamic Output

The main intention of this paper is to scrutinize the problem of internal model-based dynamic output feedback nonfragile reliable control problem for fractional-order glucose–insulin system. Specifically, a robust control law that represents the insulin injection rate is designed in order to regulate the level of glucose in diabetes treatment in the existence of meal disturbance or external glucose infusion due to improper diet. By the construction of suitable Lyapunov functional, a novel set of sufficient conditions is derived with the aid of linear matrix inequalities for obtaining the required dynamic output feedback control law. In particular, the designed controller ensures the robust stability and disturbance attenuation performance against meal disturbance of the glucose–insulin system. Numerical simulation results are performed to verify the advantage of the developed design technique. Specifically, the irregular blood glucose level can be brought down to normal level by injecting suitable rate of insulin to the patient. The result exposes that the level of blood glucose is sustained in the identified ranges via the proposed dynamic output feedback control law. 

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