scholarly journals Data-driven predictive control for the swing process of a cutter suction dredger

2021 ◽  
Vol 2121 (1) ◽  
pp. 012033
Author(s):  
Chengxi Yu ◽  
Menghong Yu ◽  
Wei Yuan
Keyword(s):  
Predictive Control ◽  
Physical Modeling ◽  
Measured Data ◽  
Data Driven ◽  
Working Process ◽  
Data Simulation ◽  
Output Data ◽  
Final Yield ◽  
Simulation Results ◽  
Control Application

Abstract The working process of cutter suction dredger is complex, so it is difficult to establish accurate model by traditional physical modeling method. The final yield of cutter suction dredger is directly related to the density of the slurry in the pipeline, while the density is controlled by the swing process. Therefore, by analyzing the measured data of the dredger, it establishes the swing process mathematical model based on subspace theory. The algorithm is based on input–output data, simulation results show the algorithm is effective for the control application.

scholarly journals ONLINE PARAMETER IDENTIFICATION OF RICE TRANSPLANTER MODEL BASED ON IPSO-EKF ALGORITHM

2020 ◽  
Vol 61 (2) ◽  
pp. 25-34 ◽  
Author(s):  
Yibo Li ◽  
Hang Li ◽  
Xiaonan Guo
Keyword(s):  
Parameter Identification ◽  
Measured Data ◽  
Model Parameters ◽  
Identification Algorithm ◽  
Output Data ◽  
Swarm Optimization ◽  
Model Based ◽  
Simulation Results ◽  
Filtering Effect ◽  
Ipso Algorithm

In order to improve the accuracy of rice transplanter model parameters, an online parameter identification algorithm for the rice transplanter model based on improved particle swarm optimization (IPSO) algorithm and extended Kalman filter (EKF) algorithm was proposed. The dynamic model of the rice transplanter was established to determine the model parameters of the rice transplanter. Aiming at the problem that the noise matrices in EKF algorithm were difficult to select and affected the best filtering effect, the proposed algorithm used the IPSO algorithm to optimize the noise matrices of the EKF algorithm in offline state. According to the actual vehicle tests, the IPSO-EKF was used to identify the cornering stiffness of the front and rear tires online, and the identified cornering stiffness value was substituted into the model to calculate the output data and was compared with the measured data. The simulation results showed that the accuracy of parameter identification for the rice transplanter model based on the IPSO-EKF algorithm was improved, and established an accurate rice transplanter model.

scholarly journals Input-output Data-driven Modeling and MIMO Predictive Control of an RCCI Engine Combustion

2021 ◽  
Vol 54 (20) ◽  
pp. 406-411
Author(s):  
Behrouz Khoshbakht Irdmousa ◽  
Jeffrey Donald Naber ◽  
Javad Mohammadpour Velni ◽  
Hoseinali Borhan ◽  
Mahdi Shahbakhti
Keyword(s):  
Predictive Control ◽  
Data Driven ◽  
Input Output ◽  
Output Data ◽  
Engine Combustion ◽  
Data Driven Modeling

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

scholarly journals A modular framework to generate robust biped locomotion: from planning to control

2021 ◽  
Vol 3 (9) ◽  
Author(s):  
Mohammadreza Kasaei ◽  
Ali Ahmadi ◽  
Nuno Lau ◽  
Artur Pereira
Keyword(s):  
Numerical Simulations ◽  
Predictive Control ◽  
Biped Locomotion ◽  
Input Output ◽  
Dynamics Model ◽  
Biped Robots ◽  
The Core ◽  
Simulation Results ◽  
Reference Trajectories ◽  
Modular Framework

AbstractBiped robots are inherently unstable because of their complex kinematics as well as dynamics. Despite many research efforts in developing biped locomotion, the performance of biped locomotion is still far from the expectations. This paper proposes a model-based framework to generate stable biped locomotion. The core of this framework is an abstract dynamics model which is composed of three masses to consider the dynamics of stance leg, torso, and swing leg for minimizing the tracking problems. According to this dynamics model, we propose a modular walking reference trajectories planner which takes into account obstacles to plan all the references. Moreover, this dynamics model is used to formulate the controller as a Model Predictive Control (MPC) scheme which can consider some constraints in the states of the system, inputs, outputs, and also mixed input-output. The performance and the robustness of the proposed framework are validated by performing several numerical simulations using MATLAB. Moreover, the framework is deployed on a simulated torque-controlled humanoid to verify its performance and robustness. The simulation results show that the proposed framework is capable of generating biped locomotion robustly.

scholarly journals A Comparison of Different Data-driven Procedures to Determine the Bunching Window

2021 ◽  
Vol 49 (2) ◽  
pp. 262-293
Author(s):  
Vincent Dekker ◽  
Karsten Schweikert
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Income Distribution ◽  
Prior Information ◽  
Structural Breaks ◽  
Data Driven ◽  
Taxable Income ◽  
Counterfactual Models ◽  
Simulation Results ◽  
Second Procedure

In this article, we compare three data-driven procedures to determine the bunching window in a Monte Carlo simulation of taxable income. Following the standard approach in the empirical bunching literature, we fit a flexible polynomial model to a simulated income distribution, excluding data in a range around a prespecified kink. First, we propose to implement methods for the estimation of structural breaks to determine a bunching regime around the kink. A second procedure is based on Cook’s distances aiming to identify outlier observations. Finally, we apply the iterative counterfactual procedure proposed by Bosch, Dekker, and Strohmaier which evaluates polynomial counterfactual models for all possible bunching windows. While our simulation results show that all three procedures are fairly accurate, the iterative counterfactual procedure is the preferred method to detect the bunching window when no prior information about the true size of the bunching window is available.

Design of 25-Gb/s Half-Rate Clock and Data Recovery Circuit for Optical Communication

2013 ◽  
Vol 385-386 ◽  
pp. 1278-1281 ◽  
Author(s):  
Zheng Fei Hu ◽  
Ying Mei Chen ◽  
Shao Jia Xue
Keyword(s):  
Optical Communication ◽  
Input Data ◽  
Clock And Data Recovery ◽  
Cmos Technology ◽  
Data Recovery ◽  
Phase Detector ◽  
Voltage Controlled Oscillator ◽  
Output Data ◽  
Data Phase ◽  
Simulation Results

A 25-Gb/s clock and data recovery (CDR) circuit with 1:2 demultiplexer which incorporates a quadrature LC voltage-controlled-oscillator and a half-rate bang-bang phase detector is presented in this paper. A quadrature LC VCO is presented to generate the four-phase output clocks. A half-rate phase detector including four flip-flops samples the 25-Gb/s input data every 20 ps and alignes the data phase. The 25-Gb/s data are retimed and demultiplexed into two 12.5-Gb/s output data. The CDR is designed in TSMC 65nm CMOS Technology. Simulation results show that the recovered clock exhibits a peak-to-peak jitter of 0.524ps and the recovered data exhibits a peak-to-peak jitter of 1.2ps. The CDR circuit consumes 121 mW from a 1.2 V supply.

Study of Rider Model for Motorcycle Racing Simulation

2020 ◽  
Author(s):  
Masatsugu Nishimura ◽  
Yoshitaka Tezuka ◽  
Enrico Picotti ◽  
Mattia Bruschetta ◽  
Francesco Ambrogi ◽  
...  
Keyword(s):  
Predictive Control ◽  
Running Speed ◽  
Steering Angle ◽  
Conventional Model ◽  
Linear Region ◽  
New Model ◽  
Constant Radius ◽  
Simulation Results ◽  
Braking Force ◽  
Motorcycle Dynamics

Various rider models have been proposed that provide control inputs for the simulation of motorcycle dynamics. However, those models are mostly used to simulate production motorcycles, so they assume that all motions are in the linear region such as those in a constant radius turn. As such, their performance is insufficient for simulating racing motorcycles that experience quick acceleration and braking. Therefore, this study proposes a new rider model for racing simulation that incorporates Nonlinear Model Predictive Control. In developing this model, it was built on the premise that it can cope with running conditions that lose contact with the front wheels or rear wheels so-called "endo" and "wheelie", which often occur during running with large acceleration or deceleration assuming a race. For the control inputs to the vehicle, we incorporated the lateral shift of the rider's center of gravity in addition to the normally used inputs such as the steering angle, throttle position, and braking force. We compared the performance of the new model with that of the conventional model under constant radius cornering and straight braking, as well as complex braking and acceleration in a single (hairpin) corner that represented a racing run. The results showed that the new rider model outperformed the conventional model, especially in the wider range of running speed usable for a simulation. In addition, we compared the simulation results for complex braking and acceleration in a single hairpin corner produced by the new model with data from an actual race and verified that the new model was able to accurately simulate the run of actual MotoGP riders.

Modeling the Microwave Transmissivity of Row Crops

2021 ◽  
Vol 36 (6) ◽  
pp. 816-823
Author(s):  
Jeil Park ◽  
Praveen Gurrala ◽  
Brian Hornbuckle ◽  
Jiming Song
Keyword(s):  
Soil Moisture ◽  
Analytical Solutions ◽  
Periodic Boundary ◽  
Periodic Boundary Conditions ◽  
Measured Data ◽  
Row Crops ◽  
Satellite Retrieval ◽  
Unit Cells ◽  
Simulation Results ◽  
Agricultural Regions

We develop a method to model the microwave transmissivity of row crops that explicitly accounts for their periodic nature as well as multiple scattering. We hypothesize that this method could eventually be used to improve satellite retrieval of soil moisture and vegetation optical depth in agricultural regions. The method is characterized by unit cells terminated by periodic boundary conditions and Floquet port excitations solved using commercial software. Individual plants are represented by vertically oriented dielectric cylinders. We calculate canopy transmissivity, reflectivity, and loss in terms of S-parameters. We validate the model with analytical solutions and illustrate the effect of canopy scattering. Our simulation results are consistent with both simulated and measured data published in the literature.

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