Real Time Estimation and Prediction of Wave Excitation Forces on a Heaving Body

2015 ◽  
Author(s):  
Bradley A. Ling ◽  
Belinda A. Batten
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Average Power ◽  
Time Estimation ◽  
Wave Climate ◽  
Domain Model ◽  
Recursive Least Squares ◽  
Levelized Cost Of Electricity ◽  
Wide Range ◽  
Excitation Force

Wave energy converters (WECs) face many technical challenges before becoming a cost-competitive source of renewable energy. The levelized cost of electricity could be decreased by implementing real-time control strategies to increase average power produced by a WEC. These control strategies typically require knowledge of the immediate future excitation force, caused by the waves. This paper presents a disturbance prediction methodology that is independent of the local wave climate and can be implemented on a wide range of devices. A time-domain model of a generic heaving WEC is developed with the Cummins equations. The model is simulated with measured water surface elevation data collected off the Oregon Coast. A simplified linear frequency-invariant state-space model is used in conjunction with a Kalman filter to estimate the current excitation force with measurements of the WEC’s motion. Future excitation forces are then predicted multiple steps in the future with a recursive least squares filter. The results show this approach makes accurate predictions of excitation force over short time horizons (up to 15 seconds), but accurate predictions become infeasible for longer horizons.

scholarly journals Transport modeling: An artificial immune system approach

2006 ◽  
Vol 16 (1) ◽  
pp. 3-30
Author(s):  
Dusan Teodorovic ◽  
Jovan Popovic ◽  
Panta Lucic
Keyword(s):  
Immune System ◽  
Real Time ◽  
Traffic Control ◽  
System Approach ◽  
Artificial Immune System ◽  
Control Strategies ◽  
Transportation Systems ◽  
Artificial Immune ◽  
Real Time Traffic ◽  
Wide Range

This paper describes an artificial immune system approach (AIS) to modeling time-dependent (dynamic, real time) transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions) that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies) for different antigens (different traffic "scenarios"). This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

Longitudinal Motion Based Lightweight Vehicle Payload Parameter Real-Time Estimations

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Xiaoyu Huang ◽  
Junmin Wang
Keyword(s):  
Real Time ◽  
Estimation Method ◽  
Time Estimation ◽  
Location Estimation ◽  
Torque Control ◽  
Recursive Least Squares ◽  
Longitudinal Motion ◽  
Unknown Parameters ◽  
Payload Mass ◽  
Planar Location

This paper proposes a longitudinal motion based payload parameter estimator (PPE) design for four-wheel-independently driven lightweight vehicles (LWVs), whose dynamics and control are substantially affected by their payload variations due to the LWVs' significantly reduced sizes and weights. Accurate and real-time estimation of payload parameters, including payload mass and its onboard planar location, will be helpful for LWV control (particularly under challenging driving conditions) and load monitoring. The proposed estimation method consists of three steps in sequential: tire effective radius identification for undriven wheels at constant speed driving; payload mass estimation during acceleration–deceleration period; and payload planar location estimation (PPLE). The PPLE is divided into two parts: a tire nominal normal force estimator (NNFE) based on a recursive least squares algorithm using signals generated by the redundant inputs, and a parameter calculator combining these estimated nominal normal forces. The prototype LWV is a lightweight electric ground vehicle (EGV) with separable torque control of the four wheels enabled by four in-wheel motors, which allow redundant input injections in the designed maneuvers. Experimental results obtained on an EGV road test show that the proposed PPE is capable of accurately estimating payload parameters, and it is independent of other unknown parameters such as tire-road friction coefficient.

Integrated Real-Time Transit Signal Priority Control for High-Frequency Segregated Transit Services

2015 ◽  
Vol 2533 (1) ◽  
pp. 28-38 ◽  
Author(s):  
Felipe Delgado ◽  
Juan Carlos Muñoz ◽  
Ricardo Giesen ◽  
Nigel H. M. Wilson
Keyword(s):  
Real Time ◽  
Control Strategy ◽  
High Frequency ◽  
Control Strategies ◽  
Transit Signal Priority ◽  
Operational Conditions ◽  
Traffic Lights ◽  
Wide Range ◽  
Transit Services ◽  
Capacity Constrained

Bus bunching affects transit operations by increasing passenger waiting time and variability. To tackle this phenomenon, a wide range of control strategies has been proposed. However, none of them have considered station and interstation control together. In this study station and interstation control were tackled to determine the optimal vehicle control strategy for various stops and traffic lights in a single service transit corridor. The strategy minimized the total time that users must devote to making a trip, taking into account delays for transit and general traffic users. Based on a high-frequency, capacity-constrained, and unscheduled service (no timetable) for which real-time information about bus position (GPS) and bus load (automated passenger counter) is available, this study focused on strategies for traffic signal priority in the form of green extension considered together with holding buses at stops and limiting passenger boarding at stops. The decisions on transit signal priority were made according to a rolling horizon scheme in which effects over the whole corridor were considered in every single decision. The proposed strategy was evaluated in a simulated environment under different operational conditions. Results showed that the proposed control strategy achieves reductions in the excess delay for transit users close to 61.4% compared with no control, while general traffic increases only by 1.5%.

A Simplified Gas-Liquid Flow Model for Kick Mitigation and Control During Drilling Operations

2015 ◽  
Author(s):  
Ulf Jakob F. Aarsnes ◽  
Adrian Ambrus ◽  
Ali Karimi Vajargah ◽  
Ole Morten Aamo ◽  
Eric van Oort
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Pressure Profile ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Two Phase ◽  
Hyperbolic Pde ◽  
Phase Dynamics ◽  
First Order ◽  
And Control

Real-time estimation of annular pressure profile and formation pressure is crucial for the execution and planning of a well control operation, especially when drilling formations with narrow pore and fracture pressure margins. A simple transient multi-phase simulator, capable of accurately representing gas and liquid dynamics while minimizing complexity and computational requirements, is highly desirable for real-time kick mitigation and control applications. Such a simulator is presented here in the form of a coupled ODE-PDE model composed of a first order ODE and a first order hyperbolic PDE. This model is shown to retain the dominating two-phase dynamics encountered during gas kick incidents. As a particular application, we demonstrate the use of the model in design of switched control algorithms for kick handling in a Managed Pressure Drilling setting. A Recursive Least Squares algorithm is employed for estimation of unknown model parameters.

Efficiency of a turbidity-based, real-time control strategy applied to a retention tank: a simulation study

2011 ◽  
Vol 64 (7) ◽  
pp. 1533-1539 ◽  
Author(s):  
C. Lacour ◽  
C. Joannis ◽  
M. Schuetze ◽  
G. Chebbo
Keyword(s):  
Real Time ◽  
Flow Rate ◽  
Control Strategy ◽  
Control Strategies ◽  
Dynamic Control ◽  
Real Time Control ◽  
The Third ◽  
Time Control ◽  
Wide Range ◽  
Two Parameters

This paper compares several real-time control (RTC) strategies for a generic configuration consisting of a storage tank with two overflow facilities. Two of the strategies only make use of flow rate data, while the third also introduces turbidity data in order to exercise dynamic control between two overflow locations. The efficiency of each strategy is compared over a wide range of system setups, described by two parameters. This assessment is performed by simulating the application of control strategies to actual measurements time series recorded on two sites. Adding turbidity measurements into an RTC strategy leads to a significant reduction in the annual overflow pollutant load. The pollutant spills spared by such a control strategy strongly depend on the site and on the flow rate based strategy considered as a reference. With the datasets used in this study, values ranging from 5 to 50% were obtained.

Payload Parameter Real-Time Estimation for Lightweight Vehicles

2011 ◽  
Author(s):  
Xiaoyu Huang ◽  
Junmin Wang
Keyword(s):  
Real Time ◽  
Estimation Method ◽  
Load Condition ◽  
Time Estimation ◽  
Torque Control ◽  
Recursive Least Squares ◽  
The Road ◽  
Dynamics And Control ◽  
Real Time Estimation ◽  
Tire Forces

This paper proposes a payload parameter estimation method for lightweight vehicles (LWVs), whose dynamics and control are substantially affected by their payload variations due to the LWVs’ significantly reduced sizes and weights. Accurate and real-time estimation of payload parameters, including payload mass and its onboard planar location, will be helpful for controller designs and load condition monitoring. The proposed payload parameter estimator (PPE) is divided into two parts: tire nominal normal force estimator (NNFE) based on a recursive least squares (RLS) algorithm using signals measured from LWV constant speed maneuvers, and parameter calculator based on estimated nominal normal forces. The prototype LWV is an electric ground vehicle with separable torque control of the four wheels by in-wheel motors, which allow redundant input injections in the designed maneuvers. Simulation results, based on a CarSim® model, show that the proposed PPE is capable of accurately and quickly estimating payload parameters, and is independent of the road condition as long as the tire forces are kept within their linear ranges.

Suppression of Vibration by Using Antiresonance Point of a Dynamic Vibration Absorber

2007 ◽  
Author(s):  
Hidetoshi Okaguchi ◽  
Hiroshi Yabuno
Keyword(s):  
Real Time ◽  
Natural Frequency ◽  
Control Method ◽  
Excitation Frequency ◽  
Time Estimation ◽  
Dynamic Vibration Absorber ◽  
Main System ◽  
Wide Range ◽  
Dynamic Absorber ◽  
And Control

The conventional passive dynamic absorber reduces the amplitude of the main system when the natural frequency of the absorber corresponds to the excitation frequency. The dynamic absorber produces two resonance peak. In this paper, we propose a control method of the semi-active dynamic absorber to reduce the amplitude of the main system to zero over the wide range of excitation frequency. The proposed controller has the system of real time estimation of excitation frequency by applying adaptive filter. When the excitation frequency varies, the frequency is estimated by the controller in real time and control signal is generated according to the estimated frequency. As a result, the natural frequency of the absorber is changed in real time and the amplitude of the main system is kept to zero over the wide range of excitation frequency. The performance of the proposed control method is experimentally discussed.

scholarly journals Real-time motion tracking of cognitive Baxter robot based on differential inverse kinematics

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110240
Author(s):  
Shaobo Li ◽  
Xingxing Zhang ◽  
Jing Yang ◽  
Qiang Bai ◽  
Jianjun Hu ◽  
...  
Keyword(s):  
Real Time ◽  
Inverse Kinematics ◽  
Motion Tracking ◽  
Control Method ◽  
Time Estimation ◽  
Automatic Target Recognition ◽  
The Real ◽  
Time Motion ◽  
Wide Range ◽  
Real Time Tracking

The tracking motion of the robot is realized based on a specific robot or relying on an expensive movement acquisition system. It has the problems of complex control procedures, lack of real-time performance, and difficulty in achieving secondary development. We propose a robot real-time tracking control method based on the control principle of differential inverse kinematics, which fuses the position and joint angle information of the robot’s actuators to realize the real-time estimation of the user’s movement during the tracking process. The motion coordinates of each joint of the robot are calculated and the coordinate conversion between man and machine is realized with the combination of the Kinect sensor and the robot operating system. We have demonstrated the robustness and accuracy of the tracking method through the real-time tracking experiment of the Baxter robot. Our research has a wide range of application value, such as automatic target recognition, demonstration teaching, and so on. It provides an important reference for the research in the field of cognitive robots.

scholarly journals A Comparative Study to Find a Suitable Model for an Improved Real-Time Monitoring of The Interventions to Contain COVID-19 Outbreak in The High Incidence States of India

2020 ◽  
Author(s):  
Amrutha G.S ◽  
Abhibhav Sharma ◽  
Anudeepti Sharma
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Control Strategies ◽  
Infected Individual ◽  
Time Estimation ◽  
World Health ◽  
Suitable Model ◽  
The Real ◽  
High Incidence

Background On March 11, 2020, The World Health Organization (WHO) declared coronavirus disease (COVID-19) as a global pandemic. There emerged a need for reliable models to estimate the imminent incidence and overall assessment of the outbreak, in order to develop effective interventions and control strategies. One such vital metrics for monitoring the transmission trends over time is the time-dependent effective reproduction number (Rt). Rt is an estimate of secondary cases caused by an infected individual at a time during the outbreak, given that a certain population proportion is already infected. Misestimated Rt is particularly concerning when probing the association between the changes in transmission rate and the changes in the implemented policies. In this paper, we substantiate the implementation of the instantaneous reproduction number (Rins) method over the conventional method to estimate Rt viz case reproduction number (Rcase), by unmasking the real-time estimation ability of both methodologies using credible datasets. Materials & Methods We employed the daily incidence dataset of COVID-19 for India and high incidence states to estimate Rins and Rcase. We compared the real-time projection obtained through these methods by corroborating those states that are containing a high number of COVID19 cases and are conducting high and efficient COVID-19 testing. The Rins and Rcase were estimated using R0 and EpiEstim packages respectively in R software 4.0.0. Results Although, both the Rins and Rcase for the selected states were higher during the lockdown phases (March 25 - June 1, 2020) and subsequently stabilizes co-equally during the unlock phase (June 1- August 23, 2020), Rins demonstrated variations in accordance with the interventions while Rcase remained generalized and under- & overestimated. A larger difference in Rins and Rcase estimates were also observed for states that are conducting high testing. Conclusion Of the two methods, Rins elucidated a better real-time progression of the COVID-19 outbreak conceptually and empirically, than that of Rcase. However, we also suggest considering the assumptions corroborated in the implementations which may result in misleading conclusions in the real world.

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