scholarly journals A Novel Longitudinal Speed Estimator for Four-Wheel Slip in Snowy Conditions

2021 ◽  
Vol 11 (6) ◽  
pp. 2809
Author(s):  
Dongmin Zhang ◽  
Qiang Song ◽  
Guanfeng Wang ◽  
Chonghao Liu
Keyword(s):  
Control Strategies ◽  
Low Cost ◽  
Estimation Error ◽  
Slip Rate ◽  
Vehicle Speed ◽  
Acceleration Sensor ◽  
Wheel Slip ◽  
Longitudinal Acceleration ◽  
Tire Rotation ◽  
Speed Estimator

This article proposes a novel longitudinal vehicle speed estimator for snowy roads in extreme conditions (four-wheel slip) based on low-cost wheel speed encoders and a longitudinal acceleration sensor. The tire rotation factor, η, is introduced to reduce the deviation between the rotation tire radius and the manufacturer’s marked tire radius. The Local Vehicle Speed Estimator is defined to eliminate longitudinal vehicle speed estimation error. It improves the tire slip accuracy of four-wheel slip, even with a high slip rate. The final vehicle speed is estimated using two fuzzy control strategies that use vehicle speed estimates from speed encoders and a longitudinal acceleration sensor. Experimental and simulation results confirm the algorithm’s validity for estimating longitudinal vehicle speed for four-wheel slip in snowy road conditions.

Fuzzy Estimation of Vehicle Speed

2005 ◽  
Author(s):  
Kyeung Heub Oh ◽  
Jin Kwon Hwang ◽  
Chul Ki Song
Keyword(s):  
Estimation Method ◽  
Experimental Result ◽  
Vehicle Speed ◽  
Wheel Slip ◽  
Worst Case ◽  
Acceleration Signal ◽  
Vehicle Velocity ◽  
Antilock Braking System ◽  
Speed Estimator ◽  
Using Data

The absolute longitudinal speed of a vehicle is estimated by using data from an accelerometer of the vehicle and wheel speed sensors of a standard 50-tooth antilock braking system. An intuitive solution to this problem is, “When wheel slip is low, calculate the vehicle velocity from the wheel speeds; when wheel slip is high, calculate the vehicle speed by integrating signal of the accelerometer.” The speed estimator weighted with fuzzy logic is introduced to implement the above concept, which is formulated as an estimation method. And the method is improved through experiments by how to calculate speed from acceleration signal and slip ratios. It is verified experimentally to usefulness o estimation speed of a vehicle. And the experimental result shows that the estimated vehicle longitudinal speed has only a 6 % worst-case error during a hard braking maneuver lasting a few seconds.

Simulated and Experimental Comparisons of Slip and Torque Control Strategies for Regenerative Braking in Instances of Parametric Uncertainties

2015 ◽  
Vol 27 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Maxime Boisvert ◽  
◽  
Philippe Micheau ◽  
Didier Mammosser
Keyword(s):  
Control Strategies ◽  
Experimental Tests ◽  
Rear Wheel ◽  
Torque Control ◽  
Regenerative Braking ◽  
Parametric Uncertainties ◽  
Vehicle Speed ◽  
Wheel Slip ◽  
Braking Control ◽  
Efficiency Map

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270003/02.jpg"" width=""340"" />Slip efficiency map & control law</div> A three-wheel hybrid recreational vehicle was studied for the purpose of regenerative braking control. In order to optimize the amount of energy recovered from electrical braking, most of the existing literature presents optimal methods which consist in defining the optimal braking torque as a function of vehicle speed. The originality of the present study is to propose a new strategy based on the control of rear wheel slip. A simulator based on MATLAB/Simulink and validated with experimental measurements compared the two strategies and their sensitivities to variations in mass, slope and road conditions. Numerical simulations and experimental tests show that regenerative braking based on a slip controller was less affected by the majority of the parametric changes. Moreover, since the slip was limited, the longitudinal stability of the vehicle was thereby improved. It thus becomes possible to ensure optimal energy recovery and vehicle stability even in instances of parametric uncertainties.

A Road Grade Recognition Method Based on Longitudinal Acceleration

2013 ◽  
Vol 339 ◽  
pp. 38-44
Author(s):  
Yao Fu ◽  
Wan Hua Ye ◽  
Yu Long Lei ◽  
Zhen Jie Liu ◽  
Hua Bing Zeng
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Dynamics Analysis ◽  
Vehicle Speed ◽  
Recognition Method ◽  
Longitudinal Dynamics ◽  
Longitudinal Acceleration ◽  
Output Torque ◽  
Road Grade ◽  
Vehicle Sensors

A road grade recognition method based on longitudinal acceleration was proposed after longitudinal dynamics analysis. The method based on longitudinal dynamics utilized a real-time engine output torque signal and the real-time vehicle speed signal to calculate road grade. The result of simulation and the vehicle field test showed that the method based on existing vehicle sensors was low cost, simple and feasible, it could identify road grade.

Speed regulation control of tractors’ new dual-flow transmission system based on slip rate resistance classification

2021 ◽  
pp. 095440702110105
Author(s):  
Guang Xia ◽  
Yan Xia ◽  
Xiwen Tang ◽  
Linfeng Zhao ◽  
Baoqun Sun
Keyword(s):  
Control Strategy ◽  
Control Algorithm ◽  
Production Efficiency ◽  
Sliding Mode ◽  
Slip Rate ◽  
Speed Control ◽  
Working Environment ◽  
Vehicle Speed ◽  
Speed Change ◽  
Simulation Results

Fluctuations in operation resistance during the operating process lead to reduced efficiency in tractor production. To address this problem, the project team independently developed and designed a new type of hydraulic mechanical continuously variable transmission (HMCVT). Based on introducing the mechanical structure and transmission principle of the HMCVT system, the priority of slip rate control and vehicle speed control is determined by classifying the slip rate. In the process of vehicle speed control, the driving mode of HMCVT system suitable for the current resistance state is determined by classifying the operation resistance. The speed change rule under HMT and HST modes is formulated with the goal of the highest production efficiency, and the displacement ratio adjustment surfaces under HMT and HST modes are determined. A sliding mode control algorithm based on feedforward compensation is proposed to address the problem that the oil pressure fluctuation has influences on the adjustment accuracy of hydraulic pump displacement. The simulation results of Simulink show that this algorithm can not only accurately follow the expected signal changes, but has better tracking stability than traditional PID control algorithm. The HMCVT system and speed control strategy models were built, and simulation results show that the speed control strategy can restrict the slip rate of driving wheels within the allowable range when load or road conditions change. When the tractor speed is lower than the lower limit of the high-efficiency speed range, the speed change law formulated in this paper can improve the tractor speed faster than the traditional rule, and effectively ensure the production efficiency. The research results are of great significance for improving tractor’s adaptability to complex and changeable working environment and promoting agricultural production efficiency.

scholarly journals An Agent-Based Crop Model Framework for Heterogeneous Soils

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 85
Author(s):  
Jorge Lopez-Jimenez ◽  
Nicanor Quijano ◽  
Alain Vande Wouwer
Keyword(s):  
Growth Models ◽  
Control Strategies ◽  
Low Cost ◽  
Soil Heterogeneity ◽  
Crop Growth ◽  
Negative Effects ◽  
Model Framework ◽  
Agent Based ◽  
Crop Growth Models ◽  
Definition Of

Climate change and the efficient use of freshwater for irrigation pose a challenge for sustainable agriculture. Traditionally, the prediction of agricultural production is carried out through crop-growth models and historical records of the climatic variables. However, one of the main flaws of these models is that they do not consider the variability of the soil throughout the cultivation area. In addition, with the availability of new information sources (i.e., aerial or satellite images) and low-cost meteorological stations, it is convenient that the models incorporate prediction capabilities to enhance the representation of production scenarios. In this work, an agent-based model (ABM) that considers the soil heterogeneity and water exchanges is proposed. Soil heterogeneity is associated to the combination of individual behaviours of uniform portions of land (agents), while water fluxes are related to the topography. Each agent is characterized by an individual dynamic model, which describes the local crop growth. Moreover, this model considers positive and negative effects of water level, i.e., drought and waterlogging, on the biomass production. The development of the global ABM is oriented to the future use of control strategies and optimal irrigation policies. The model is built bottom-up starting with the definition of agents, and the Python environment Mesa is chosen for the implementation. The validation is carried out using three topographic scenarios in Colombia. Results of potential production cases are discussed, and some practical recommendations on the implementation are presented.

Measuring battery discharge characteristics for accurate UAV endurance estimation

2020 ◽  
Vol 124 (1277) ◽  
pp. 1099-1113
Author(s):  
L. Mariga ◽  
I. Silva Tiburcio ◽  
C.A. Martins ◽  
A.N. Almeida Prado ◽  
C. Nascimento
Keyword(s):  
Low Cost ◽  
Estimation Error ◽  
Flight Time ◽  
Time Estimates ◽  
Discharge Rates ◽  
Nonlinear Optimisation ◽  
Time Calculation ◽  
Discharge Profile ◽  
Battery Discharge ◽  
Battery Discharge Characteristics

ABSTRACTThe increasing use of unmanned aerial vehicles in areas such as rescue, mapping, and transportation have made it necessary to study more accurate techniques for calculating flight time estimates. Such calculations require knowing the battery discharge profile. Simplified flight time calculation methods provide data with uncertainties as they are based solely on manufacturer datasheet information. This study presents a setup to measure the battery discharge curve using a LabVIEW interface with a low-cost acquisition system. The acquired data passes through a nonlinear optimisation algorithm to find the battery coefficients, which enables the more precise estimation of its range and endurance. The great advantage of this model is that it makes it possible to predict how the battery will discharge at different rates using just one experimental curve. The methodology was applied to three different batteries and the model was validated with different discharge rates in a controlled environment, which resulted in endurance lower than 3.0% for most conditions and voltage estimation error lower than 3.0% in operational voltage. The work also presented a methodology for estimating cruise time based on the current used during each flight stage.

Sampled-data extended state observer-based backstepping control of two-link flexible manipulator

2019 ◽  
Vol 41 (13) ◽  
pp. 3581-3599 ◽  
Author(s):  
Umesh Kumar Sahu ◽  
Bidyadhar Subudhi ◽  
Dipti Patra
Keyword(s):  
Control Strategies ◽  
Estimation Error ◽  
Experimental Studies ◽  
State Observer ◽  
Lyapunov Theory ◽  
Extended State Observer ◽  
Flexible Manipulator ◽  
Sampled Data ◽  
Extended State ◽  
Model Uncertainties

Currently, space robots such as planetary robots and flexible-link manipulators (FLMs) are finding specific applications to reduce the cost of launching. However, the structural flexible nature of their arms and joints leads to errors in tip positioning owing to tip deflection. The internal model uncertainties and disturbance are the key challenges in the development of control strategies for tip-tracking of FLMs. To deal with these challenges, we design a tip-tracking controller for a two-link flexible manipulator (TLFM) by developing a sampled-data extended state observer (SD-ESO). It is designed to reconstruct uncertain parameters for accurate tip-tracking control of a TLFM. Finally, a backstepping (BS) controller is designed to attenuate the estimation error and other bounded disturbances. Convergence and stability of the proposed control system are investigated by using Lyapunov theory. The benefits (control performance and robustness) of the proposed SD-ESO-based BS controller are compared with other similar approaches by pursuing both simulation and experimental studies. It is observed from the results obtained that SD-ESO-based BS Controller effectively compensates the deviation in tip-tracking performance of TLFM due to non-minimum phase behavior and model uncertainties with an improved transient response.

scholarly journals Shaping Streamflow Using a Real-Time Stormwater Control Network

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2259 ◽  
Author(s):  
Abhiram Mullapudi ◽  
Matthew Bartos ◽  
Brandon Wong ◽  
Branko Kerkez
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Low Cost ◽  
Control Network ◽  
Monitoring And Control ◽  
Set Point ◽  
Smart Water ◽  
Decay Times ◽  
Retention Basins ◽  
Scale Control

“Smart” water systems are transforming the field of stormwater management by enabling real-time monitoring and control of previously static infrastructure. While the localized benefits of active control are well-established, the potential for system-scale control of watersheds is poorly understood. This study shows how a real-world smart stormwater system can be leveraged to shape streamflow within an urban watershed. Specifically, we coordinate releases from two internet-controlled stormwater basins to achieve desired control objectives downstream—such as maintaining the flow at a set-point, and generating interleaved waves. In the first part of the study, we describe the construction of the control network using a low-cost, open-source hardware stack and a cloud-based controller scheduling application. Next, we characterize the system’s control capabilities by determining the travel times, decay times, and magnitudes of various waves released from the upstream retention basins. With this characterization in hand, we use the system to generate two desired responses at a critical downstream junction. First, we generate a set-point hydrograph, in which flow is maintained at an approximately constant rate. Next, we generate a series of overlapping and interleaved waves using timed releases from both retention basins. We discuss how these control strategies can be used to stabilize flows, thereby mitigating streambed erosion and reducing contaminant loads into downstream waterbodies.

scholarly journals A Deep Learning Approach for Table Tennis Forehand Stroke Evaluation System Using an IMU Sensor

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Sahar S. Tabrizi ◽  
Saeid Pashazadeh ◽  
Vajiheh Javani
Keyword(s):  
Evaluation System ◽  
Low Cost ◽  
Estimation Error ◽  
Weighted Average ◽  
Principal Component ◽  
Training System ◽  
Table Tennis ◽  
Sports Activity ◽  
Nonlinear Regression Models ◽  
Shadow Play

Psychological and behavioral evidence suggests that home sports activity reduces negative moods and anxiety during lockdown days of COVID-19. Low-cost, nonintrusive, and privacy-preserving smart virtual-coach Table Tennis training assistance could help to stay active and healthy at home. In this paper, a study was performed to develop a Forehand stroke’ performance evaluation system as the second principal component of the virtual-coach Table Tennis shadow-play training system. This study was conducted to show the effectiveness of the proposed LSTM model, compared with 2DCNN and RBF-SVR time-series analysis and machine learning methods, in evaluating the Table Tennis Forehand shadow-play sensory data provided by the authors. The data was generated, comprising 16 players’ Forehand strokes racket’s movement and orientation measurements; besides, the strokes’ evaluation scores were assigned by the three coaches. The authors investigated the ML models’ behaviors changed by the hyperparameters values. The experimental results of the weighted average of RMSE revealed that the modified LSTM models achieved 33.79% and 4.24% estimation error lower than 2DCNN and RBF-SVR, respectively. However, the R ¯ 2 results show that all nonlinear regression models are fit enough on the observed data. The modified LSTM is the most powerful regression method among all the three Forehand types in the current study.

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