Biological System Control / Biocontrol
Amir Veisi; Hadi Delavari
Volume 15, Issue 2 , August 2021, , Pages 127-139
Abstract
Coronavirus, or Covid 19, is a contagious disease caused by the coronavirus and is a threat to the health and economy of countries. Although vaccine production and distribution are currently underway, but non-pharmacological interventions are still being implemented as an important and fundamental strategy ...
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Coronavirus, or Covid 19, is a contagious disease caused by the coronavirus and is a threat to the health and economy of countries. Although vaccine production and distribution are currently underway, but non-pharmacological interventions are still being implemented as an important and fundamental strategy to control the spread of the virus in countries around the world. Now, according to the existing conditions, having a suitable dynamic model of this disease will provide information to the relevant authorities about the behavior, prevalence, speed of transmission, and other parameters. Various mathematical modeling methods have been proposed to analyze the transmission patterns of this new disease. In this paper, using fractional calculus, the dynamics of Covid 19 will be investigated. One of the major advantages of fractional calculus, which can be very effective in modeling and controlling epidemics, is its long-term memory property. With a dynamic model of virus transmission and prevalence, focusing on a control strategy based on non-pharmacological interventions can be important. In this paper, a new adaptive fractional order sliding mode controller is proposed for non-pharmacological decisions. The proposed method in this paper for controlling non-pharmacological interventions is an adaptive fractional order active sliding mode control, which can have a good performance due to its robustness against parameter uncertainty and system disturbances.
Bioelectrics
Hamid Heydari Nejad; Hadi Delavari
Volume 9, Issue 4 , February 2015, , Pages 327-339
Abstract
The patients with Type 1 diabetes need strict blood glucose level control because the body’s production and use of insulin are impaired and hence this increases the blood glucose level. In this paper, a fractional order sliding mode control and an adaptive fractional order sliding mode control ...
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The patients with Type 1 diabetes need strict blood glucose level control because the body’s production and use of insulin are impaired and hence this increases the blood glucose level. In this paper, a fractional order sliding mode control and an adaptive fractional order sliding mode control are proposed to regulate the blood glucose in the presence of the parameter variations and meal disturbance. The Bergman minimal model is used to design the proposed controllers. The proposed controllers are appropriate for making the insulin delivery pumps in closed loop control of diabetes. The proposed controllers attenuate the effect of chattering. The fractional adaptive sliding mode control makes the controller immune to disturbance and uncertainties and the fractional calculus provides robustness performance. Finally the results are compared with some other methods such as backstepping sliding mode control and fractional order sliding mode control methods. Simulation results show that the proposed controllers are able to reject both uncertainties and disturbance with a chattering free control law.
Neuro-Muscular Engineering
Abed Khorasani; Abbas Erfanian Omidvar
Volume 5, Issue 3 , June 2011, , Pages 245-255
Abstract
During the last decade, functional neuromuscular stimulation (FNS) has been proposed as a potential technique for restoring motor function in paralyzed limbs. A major challenge to restoring a desired functional limb movement through the use of intramuscular stimulation is the development of a robust ...
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During the last decade, functional neuromuscular stimulation (FNS) has been proposed as a potential technique for restoring motor function in paralyzed limbs. A major challenge to restoring a desired functional limb movement through the use of intramuscular stimulation is the development of a robust control strategy for determining the stimulation patterns. A major impediment to stimulating the paralyzed limbs and determining the stimulation pattern has been the highly non-linear, time-varying properties of electrically stimulated muscle, muscle fatigue, large latency and time constant which limit the utility of pre-specified stimulation pattern and open-loop FES control system. In this paper we present a robust strategy for multi-joint control through intramuscular stimulation in which the system parameters are adapted online and the controller requires no offline training phase. The method is based on the combination of sliding mode control with fuzzy logic and neural control. Extensive experiments on three rats are provided to demonstrate the robustness, stability, and tracking accuracy of the proposed method. The results show that the proposed strategy can provide accurate tracking control with fast convergence.
Neuro-Muscular Engineering
Amir Homayoun Jafari; Seyed Mohammad Reza Hashemi Golpayegani; Farzad Towhidkhah; Ali Fallah
Volume -2, Issue 1 , July 2005, , Pages 57-70
Abstract
A hierarchical structure model with three levels is presented for modeling motor control in skill movements. At each level, based on accuracy and quality of control, a specific controller is activated. At first level, control concepts are qualitative. The duty of the first level is to provide stability ...
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A hierarchical structure model with three levels is presented for modeling motor control in skill movements. At each level, based on accuracy and quality of control, a specific controller is activated. At first level, control concepts are qualitative. The duty of the first level is to provide stability of system, based on the received qualitative information from second level such as the decrement or increment of error. A self-organized controller at first level is used to generate qualitative control commands, and it plays an encouragement-punishment role to keep the stability of system by sending discrete commands to the second level. This controller only contributes at control action when the controller of second level can not preserve stability individually. At second level, control concepts are quantitative. The duty of the second level is adaptation and control of system accurately. The received information at this level generally comes from sensory and visual feedbacks, and it includes more accurate concepts of control action - like the amount of movement error. A model based on the predictive controller at second level generates quantitative control commands and indeed, determines trajectory of movement accurately. A fuzzy switch combines the control commands of first and second levels, based on the sliding mode strategy, to provide a robust control. At third level, this command is interpreted and then is applied to the involved muscles in movement. The received information at this level is generally the contribution of muscles in performing movement and the effects of environment on the movement, which comes from sensory feedbacks. The presented model with this hierarchical structure has a proper ability to control and keep the stability of system. The simulation results confirm this subject.
