Non-linear model-free control of flapping wing flying robot using iPID

2016 ◽  
Author(s):  
Aneesh N. Chand ◽  
Michihiro Kawanishi ◽  
Tatsuo Narikiyo
Keyword(s):  
Linear Model ◽  
Flapping Wing ◽  
Model Free ◽  
Non Linear ◽  
Model Free Control ◽  
Flying Robot

Model-Free Control of a Hovering Flapping-Wing Microrobot

2014 ◽  
Vol 77 (1) ◽  
pp. 95-111 ◽  
Author(s):  
Néstor O. Pérez-Arancibia ◽  
Pierre-Emile J. Duhamel ◽  
Kevin Y. Ma ◽  
Robert J. Wood
Keyword(s):  
Flapping Wing ◽  
Model Free ◽  
Model Free Control

Model-free control of a flapping-wing flying microrobot

2013 ◽  
Author(s):  
Nestor O. Perez-Arancibia ◽  
Pierre-Emile J. Duhamel ◽  
Kevin Y. Ma ◽  
Robert J. Wood
Keyword(s):  
Flapping Wing ◽  
Model Free ◽  
Model Free Control

scholarly journals Influence of the Porosity of Polymer Foams on the Performances of Capacitive Flexible Pressure Sensors

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1968 ◽  
Author(s):  
Sylvie Bilent ◽  
Thi Hong Nhung Dinh ◽  
Emile Martincic ◽  
Pierre-Yves Joubert
Keyword(s):  
Experimental Data ◽  
Linear Model ◽  
Dielectric Material ◽  
Pressure Sensors ◽  
Volume Ratio ◽  
Measurement Range ◽  
Polymer Foams ◽  
First Order ◽  
Non Linear ◽  
Flexible Pressure Sensors

This paper reports on the study of microporous polydimethylsiloxane (PDMS) foams as a highly deformable dielectric material used in the composition of flexible capacitive pressure sensors dedicated to wearable use. A fabrication process allowing the porosity of the foams to be adjusted was proposed and the fabricated foams were characterized. Then, elementary capacitive pressure sensors (15 × 15 mm2 square shaped electrodes) were elaborated with fabricated foams (5 mm or 10 mm thick) and were electromechanically characterized. Since the sensor responses under load are strongly non-linear, a behavioral non-linear model (first order exponential) was proposed, adjusted to the experimental data, and used to objectively estimate the sensor performances in terms of sensitivity and measurement range. The main conclusions of this study are that the porosity of the PDMS foams can be adjusted through the sugar:PDMS volume ratio and the size of sugar crystals used to fabricate the foams. Additionally, the porosity of the foams significantly modified the sensor performances. Indeed, compared to bulk PDMS sensors of the same size, the sensitivity of porous PDMS sensors could be multiplied by a factor up to 100 (the sensitivity is 0.14 %.kPa−1 for a bulk PDMS sensor and up to 13.7 %.kPa−1 for a porous PDMS sensor of the same dimensions), while the measurement range was reduced from a factor of 2 to 3 (from 594 kPa for a bulk PDMS sensor down to between 255 and 177 kPa for a PDMS foam sensor of the same dimensions, according to the porosity). This study opens the way to the design and fabrication of wearable flexible pressure sensors with adjustable performances through the control of the porosity of the fabricated PDMS foams.

Analysis of Single Buffer Random Polling System With State-Dependent Input Process and Server/Station Breakdowns

2018 ◽  
Vol 9 (1) ◽  
pp. 22-50 ◽  
Author(s):  
Thomas Y.S. Lee
Keyword(s):  
Steady State ◽  
Linear Model ◽  
Repair Process ◽  
Polling System ◽  
Steady State Analysis ◽  
Relaxation System ◽  
Polling Model ◽  
State Dependent ◽  
Non Linear ◽  
State Analysis

Models and analytical techniques are developed to evaluate the performance of two variations of single buffers (conventional and buffer relaxation system) multiple queues system. In the conventional system, each queue can have at most one customer at any time and newly arriving customers find the buffer full are lost. In the buffer relaxation system, the queue being served may have two customers, while each of the other queues may have at most one customer. Thomas Y.S. Lee developed a state-dependent non-linear model of uncertainty for analyzing a random polling system with server breakdown/repair, multi-phase service, correlated input processes, and single buffers. The state-dependent non-linear model of uncertainty introduced in this paper allows us to incorporate correlated arrival processes where the customer arrival rate depends on the location of the server and/or the server's mode of operation into the polling model. The author allows the possibility that the server is unreliable. Specifically, when the server visits a queue, Lee assumes that the system is subject to two types of failures: queue-dependent, and general. General failures are observed upon server arrival at a queue. But there are two possibilities that a queue-dependent breakdown (if occurs) can be observed; (i) is observed immediately when it occurs and (ii) is observed only at the end of the current service. In both cases, a repair process is initiated immediately after the queue-dependent breakdown is observed. The author's model allows the possibility of the server breakdowns/repair process to be non-stationary in the number of breakdowns/repairs to reflect that breakdowns/repairs or customer processing may be progressively easier or harder, or that they follow a more general learning curve. Thomas Y.S. Lee will show that his model encompasses a variety of examples. He was able to perform both transient and steady state analysis. The steady state analysis allows us to compute several performance measures including the average customer waiting time, loss probability, throughput and mean cycle time.

scholarly journals Author Correction: Reliance on model-based and model-free control in obesity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lieneke K. Janssen ◽  
Florian P. Mahner ◽  
Florian Schlagenhauf ◽  
Lorenz Deserno ◽  
Annette Horstmann
Keyword(s):  
Model Based ◽  
Model Free ◽  
Model Free Control

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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