scholarly journals Multiple Model ILC for Continuous-Time Nonlinear Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Xiaoli Li ◽  
Kang Wang ◽  
Yang Li
Keyword(s):  
Continuous Time ◽  
Iterative Learning Control ◽  
Fixed Time ◽  
Time Interval ◽  
Multiple Model ◽  
Control Effectiveness ◽  
System A ◽  
And Control ◽  
Asymptotical Convergence ◽  
System Operating

Multiple model iterative learning control (MMILC) method is proposed to deal with the continuous-time nonlinear system with uncertain and iteration-varying parameters. In this kind of control strategy, multiple models are established to cover the uncertainty of system; a switching mechanism is used to decide the most appropriate model for system in current iteration. For system operating iteratively in a fixed time interval with uncertain or jumping parameters, this kind of MMILC can improve the transient response and control property greatly. Asymptotical convergence is demonstrated theoretically, and the control effectiveness is illustrated by numerical simulation.

scholarly journals Welding Process Tracking Control Based on Multiple Model Iterative Learning Control

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Xiaoli Li ◽  
Jian Liu ◽  
Linkun Wang ◽  
Kang Wang ◽  
Yang Li
Keyword(s):  
Tracking Control ◽  
Iterative Learning Control ◽  
Welding Process ◽  
Learning Control ◽  
Iterative Learning ◽  
Time Interval ◽  
Multiple Model ◽  
Gas Tungsten Arc ◽  
Multiple Model Adaptive Control ◽  
Precision Tracking

The welding of the same parts has same welding trajectory, so welding process has strong repeatability. In this paper, aiming at the repeatability of welding process, an iterative learning controller is designed to achieve the control of weld quality. Due to the extremely variable welding environment and the presence of noise interferences and load disturbances, it is easy to cause the jumping change in parameters and even the structure of the welding system. Therefore, the idea of multiple model adaptive control (MMAC) is introduced into iterative learning control (ILC), and a multiple model iterative learning control (MMILC) algorithm is designed according to model of weld pool dynamic process in gas tungsten arc welding (GTAW). Besides, the convergence of the algorithm is analyzed for two cases: fixed parameters and jumping parameters. It turns out that the MMILC can not only utilize the repetitive information effectively in the welding process to achieve high precision tracking control of weld seam in limited time interval, but also realize the multiple model switching according to different working conditions to improve the welding quality.

Efficacy of Ovsynch and Ovsynch Plus Protocol for Improvement of Fertility in Postpartum Sahiwal Cows

2019 ◽  
Vol 14 (04) ◽  
Author(s):  
J. P. Lakher ◽  
M. K. Awasthi ◽  
J. R. Khan ◽  
M. R. Poyam
Keyword(s):  
Fixed Time ◽  
Conception Rate ◽  
Control Group ◽  
Group Iii ◽  
Treatment Groups ◽  
Group I ◽  
Early Postpartum ◽  
The Status ◽  
Sahiwal Cows ◽  
And Control

The present study was conducted to investigate the efficacy of Ovsynch and Ovsynch plus protocol in postpartum (day 60) Sahiwal cows (n=18). Animals were randomly divided into three equal groups, viz., Ovsynch group Ovsynch plus group and Control group. Animals of group I (n = 6) were treated with traditional Ovsynch protocol. The animals (n = 6) of group II were treated with Ovsynch plus protocol which consisted of an initial intramuscular injection of eCG (Folligon) @ 250 IU on day 60 postpartum followed 3 days later by GPG (Ovsynch) protocol. In group-III Control, no treatment was given to animals (n = 6). Treated animals were inseminated at a fixed time between 14 and 20 hrs after second GnRH injection, irrespective of estrus detection. Blood samples were collected from each animal on days 50 and 60 postpartum to determine the status of cyclicity in animals based on serum concentrations of progesterone (P4). A third blood sample was collected on the day of prostaglandin treatment to determine the response of first GnRH injection. Four animals each were cyclic, and two were acyclic in both treatment groups. Four animals each responded to first GnRH treatment in both treatment groups. Similarly, two animals each got conceived giving conception rate of 50% (2/4) in each treatment. In the control group, one out of 6 animals got conceived yielding 16.66 % conception rate (1/6) during the study period. It may be thus concluded that Ovsynch and Ovsynch plus protocol may be used during the early postpartum period to improve the reproductive efficiency in postpartum Sahiwal cows.

Utilization of remote sensing for estimation of scale of cutting and growing of forest zones

2017 ◽  
Vol 920 (2) ◽  
pp. 57-60
Author(s):  
F.E. Guliyeva
Keyword(s):  
Remote Sensing ◽  
Fixed Time ◽  
Time Interval ◽  
Time Points ◽  
Average Value ◽  
Time Period ◽  
Remote Estimation ◽  
The Given ◽  
Forest Cutting

The study of results of relevant works on remote sensing of forests has shown that the known methods of remote estimation of forest cuts and growth don’t allow to calculate the objective average value of forests cut volume during the fixed time period. The existing mathematical estimates are not monotonous and make it possible to estimate primitively the scale of cutting by computing the ratio of data in two fixed time points. In the article the extreme properties of the considered estimates for deforestation and reforestation models are researched. The extreme features of integrated averaged values of given estimates upon limitations applied on variables, characterizing the deforestation and reforestation processes are studied. The integrated parameter, making it possible to calculate the averaged value of estimates of forest cutting, computed for all fixed time period with a fixed step is suggested. It is shown mathematically that the given estimate has a monotonous feature in regard of value of given time interval and make it possible to evaluate objectively the scales of forest cutting.

scholarly journals Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality

Psychometrika ◽  
2021 ◽  
Author(s):  
Oisín Ryan ◽  
Ellen L. Hamaker
Keyword(s):  
Network Analysis ◽  
Discrete Time ◽  
Continuous Time ◽  
Centrality Measures ◽  
Time Interval ◽  
Direct Effects ◽  
Network Approach ◽  
Var Models ◽  
Auto Regressive ◽  
Conceptual Shift

AbstractNetwork analysis of ESM data has become popular in clinical psychology. In this approach, discrete-time (DT) vector auto-regressive (VAR) models define the network structure with centrality measures used to identify intervention targets. However, VAR models suffer from time-interval dependency. Continuous-time (CT) models have been suggested as an alternative but require a conceptual shift, implying that DT-VAR parameters reflect total rather than direct effects. In this paper, we propose and illustrate a CT network approach using CT-VAR models. We define a new network representation and develop centrality measures which inform intervention targeting. This methodology is illustrated with an ESM dataset.

scholarly journals Period-Life of a Branching Process with Migration and Continuous Time

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 868
Author(s):  
Khrystyna Prysyazhnyk ◽  
Iryna Bazylevych ◽  
Ludmila Mitkova ◽  
Iryna Ivanochko
Keyword(s):  
Random Process ◽  
Generating Function ◽  
Continuous Time ◽  
Branching Process ◽  
Probability Generating Function ◽  
Time Interval ◽  
The Moment ◽  
First Time ◽  
Critical Branching Process ◽  
Number Of Particles

The homogeneous branching process with migration and continuous time is considered. We investigated the distribution of the period-life τ, i.e., the length of the time interval between the moment when the process is initiated by a positive number of particles and the moment when there are no individuals in the population for the first time. The probability generating function of the random process, which describes the behavior of the process within the period-life, was obtained. The boundary theorem for the period-life of the subcritical or critical branching process with migration was found.

Modeling human-like longitudinal driver model for intelligent vehicles based on reinforcement learning

2021 ◽  
pp. 095440702098357
Author(s):  
Ju Xie ◽  
Xing Xu ◽  
Feng Wang ◽  
Haobin Jiang
Keyword(s):  
Reinforcement Learning ◽  
Comprehensive Evaluation ◽  
Path Following ◽  
Intelligent Vehicles ◽  
Driver Model ◽  
Control Center ◽  
Training Performance ◽  
Learning Agents ◽  
System A ◽  
And Control

The driver model is the decision-making and control center of intelligent vehicle. In order to improve the adaptability of intelligent vehicles under complex driving conditions, and simulate the manipulation characteristics of the skilled driver under the driver-vehicle-road closed-loop system, a kind of human-like longitudinal driver model for intelligent vehicles based on reinforcement learning is proposed. This paper builds the lateral driver model for intelligent vehicles based on optimal preview control theory. Then, the control correction link of longitudinal driver model is established to calculate the throttle opening or brake pedal travel for the desired longitudinal acceleration. Moreover, the reinforcement learning agents for longitudinal driver model is parallel trained by comprehensive evaluation index and skilled driver data. Lastly, training performance and scenarios verification between the simulation experiment and the real car test are performed to verify the effectiveness of the reinforcement learning based longitudinal driver model. The results show that the proposed human-like longitudinal driver model based on reinforcement learning can help intelligent vehicles effectively imitate the speed control behavior of the skilled driver in various path-following scenarios.

Automated sequencing batch bioreactor under extreme peaks of 4-chlorophenol

2003 ◽  
Vol 47 (10) ◽  
pp. 175-181 ◽  
Author(s):  
G. Buitrón ◽  
M.-E. Schoeb ◽  
J. Moreno
Keyword(s):  
Dissolved Oxygen ◽  
Metabolic Activity ◽  
Automated System ◽  
Stable Operation ◽  
High Concentration ◽  
Batch Bioreactor ◽  
On Line ◽  
The Moment ◽  
And Control ◽  
System Operating

The operation of a sequencing batch bioreactor is evaluated when high concentration peaks of a toxic compound (4-chlorophenol, 4CP) are introduced into the reactor. A control strategy based on the dissolved oxygen concentration, measured on line, is utilized. To detect the end of the reaction period, the automated system search for the moment when the dissolved oxygen has passed by a minimum, as a consequence of the metabolic activity of the microorganisms and right after to a maximum due to the saturation of the water (similar to the self-cycling fermentation, SCF, strategy). The dissolved oxygen signal was sent to a personal computer via data acquisition and control using MATLAB and the SIMULINK package. The system operating under the automated strategy presented a stable operation when the acclimated microorganisms (to an initial concentration of 350 mg 4CP/L), were exposed to a punctual concentration peaks of 600 mg 4CP/L. The 4CP concentrations peaks superior or equals to 1,050 mg/L only disturbed the system from a short to a medium term (one month). The 1,400 mg/L peak caused a shutdown in the metabolic activity of the microorganisms that led to the reactor failure. The biomass acclimated with the SCF strategy can partially support the variations of the toxic influent since, at the moment in which the influent become inhibitory, there is a failure of the system.

Design and Simulation of Pedal Simulator in Brake by Wire System

2014 ◽  
Vol 556-562 ◽  
pp. 1358-1361 ◽  
Author(s):  
Wen Bo Zhu ◽  
Fen Zhu Ji ◽  
Xiao Xu Zhou
Keyword(s):  
Simulation Models ◽  
Control Algorithms ◽  
Brake Pedal ◽  
Braking System ◽  
Pedal Force ◽  
Performance Requirements ◽  
System A ◽  
Pedal Feel ◽  
And Control ◽  
Wire System

Wire of the brake pedal is not directly connected to the hydraulic environment in the braking By-wire system so the driver has no direct pedal feel. Then pedal simulator is an important part in the brake-by-wire system. A pedal force simulator was designed based on the traditional brake pedal curve of pedal force and pedal travel, AMESim and Matlab / Simulink were used as a platform to build simulation models and control algorithms. The simulation results show that the pedal stroke simulator and the control strategy meet the performance requirements of traditional braking system. It can be used in brake by wire system.

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