A Preview Steering Autopilot Control Algorithm for Four-Wheel-Steering Passenger Vehicles

1992 ◽  
Vol 114 (3) ◽  
pp. 401-408 ◽  
Author(s):  
A. Y. Lee
Keyword(s):  
Control Algorithm ◽  
Vision System ◽  
Control Law ◽  
Tracking Problem ◽  
Computer Vision System ◽  
Passenger Vehicles ◽  
Lane Tracking ◽  
Simulation Results ◽  
Almost All ◽  
Future Information

This paper addresses the control law design of a preview steering autopilot for a four-wheel-steering vehicle to perform automatic lane tracking. In the concept, an on-board computer vision system is used in lieu of the driver’s vision to track the roadway. The steering autopilot design is formulated as an optimal, discrete-time preview path tracking problem under the “perfect measurement” assumption. Simulation results indicate that the tracking performance of the steering autopilot was improved by preview relative to that calculated for an autopilot without preview. These results also indicate the existence of an effective preview time with which almost all the benefits of previewing future information can be obtained. This effective preview time is about three times the reciprocal of the autopilot’s bandwidth. Our study also indicates that preview steering autopilots can tolerate the use of actuators with a lower bandwidth than those designed without preview information.

Iterative Learning Impedance Control in Gait Rehabilitation Robot

2014 ◽  
Vol 494-495 ◽  
pp. 1084-1087
Author(s):  
Fu Cheng Cao ◽  
Hai Xin Sun ◽  
Li Rong Wang
Keyword(s):  
Iterative Learning Control ◽  
Control Algorithm ◽  
Closed Loop ◽  
Impedance Control ◽  
Iterative Learning ◽  
Gait Rehabilitation ◽  
Control Law ◽  
Rehabilitation Robot ◽  
Simulation Results ◽  
Impedance Parameters

An iterative learning impedance control algorithm is presented to control a gait rehabilitation robot. According to the circumstances of the patient, the appropriate rehabilitation target impedance parameters are set. With the adoption of iterative learning control law, the impedance error in the closed loop is guaranteed to converge to zero and the iterative trajectories follow the desired trajectories over the entire operation interval. The effectiveness of the proposed method is shown through numerical simulation results.

scholarly journals Bearing-Only Adaptive Formation Control Using Back-Stepping Method

2021 ◽  
Vol 2 ◽  
Author(s):  
Sulong Li ◽  
Qin Wang ◽  
Enci Wang ◽  
Yangyang Chen
Keyword(s):  
Formation Control ◽  
Control Algorithm ◽  
Adaptive Estimation ◽  
Design Method ◽  
Order System ◽  
Control Law ◽  
Barbalat’S Lemma ◽  
Simulation Results ◽  
Unknown Disturbance ◽  
Negative Gradient

In this paper, the bearing-only formation control problem of a class of second-order system with unknown disturbance is investigated, where the control law merely depends on the relative bearings between neighboring agents. In order to offset the effect of unknown disturbance on the system, adaptive estimation is introduced. In the design of the control law, the back-stepping design method and the negative gradient method are used. The Barbalat’s lemma is used to prove the global stability of the system. The simulation results prove the effectiveness of the proposed formation control algorithm.

scholarly journals A new experimental ground vehicle with hybrid control and hybrid vision sensor

2010 ◽  
Vol 8 (03) ◽  
Author(s):  
J. M. Rendón-Mancha ◽  
G. Sanahuja ◽  
P. Castillo ◽  
R. Lozano
Keyword(s):  
Control Algorithm ◽  
Hybrid Control ◽  
Vision System ◽  
Sampling Period ◽  
Control Law ◽  
Continuous Control ◽  
Ground Vehicle ◽  
The Stability ◽  
Real Time Application ◽  
Made In

This paper presents a new hybrid control algorithm based on saturation functions and its real-time application to a ground vehicle. The hybrid control is developed from a nonlinear continuous control law and the objective is to obtain the optimal sampling period to apply the controller in real experiences. The stability analysis was made in discrete time. The experimental platform is composed of a remote control toy car and a vision system. The vision system is built using a simple webcam and a diode laser. This system is fast, accurate, inexpensive and easy to implement. Simulations and experiments show the stability and robustness of the closed-loop system. The proposed control law performance is compared with a linear control algorithm.

Study on Power Flow and H∞ Robust Control in Raft Hybrid Vibration Isolation System

2003 ◽  
Author(s):  
Weimin Mao ◽  
Yueyun Cao ◽  
Shijian Zhu
Keyword(s):  
Robust Control ◽  
Control Algorithm ◽  
Power Flow ◽  
Vibration Isolation ◽  
Control Law ◽  
Isolation System ◽  
Vibration Isolation System ◽  
Passive Isolation ◽  
Simulation Results ◽  
Better Than

The raft hybrid vibration isolation system is studied. The control law of the system is designed with H∞ robust control theory. The power flow in the raft hybrid vibration isolation system is investigated. In order to verify the raft hybrid vibration isolation system numerical simulation is carried out. The simulation results show that the control algorithm is effective and robust, and that the isolation effectiveness of the hybrid vibration isolation system is much better than that of the passive isolation system in the whole frequency domain.

scholarly journals Measurement of Gem Colour Using a Computer Vision System: A Case Study with Jadeite-Jade

Minerals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 791
Author(s):  
Sufei Zhang ◽  
Ying Guo
Keyword(s):  
Computer Vision ◽  
Regression Model ◽  
Vision System ◽  
Expert Group ◽  
Group Test ◽  
System A ◽  
Real Objects ◽  
Practical Tool ◽  
Almost All

This paper introduces computer vision systems (CVSs), which provides a new method to measure gem colour, and compares CVS and colourimeter (CM) measurements of jadeite-jade colour in the CIELAB space. The feasibility of using CVS for jadeite-jade colour measurement was verified by an expert group test and a reasonable regression model in an experiment involving 111 samples covering almost all jadeite-jade colours. In the expert group test, more than 93.33% of CVS images are considered to have high similarities with real objects. Comparing L*, a*, b*, C*, h, and ∆E* (greater than 10) from CVS and CM tests indicate that significant visual differences exist between the measured colours. For a*, b*, and h, the R2 of the regression model for CVS and CM was 90.2% or more. CVS readings can be used to predict the colour value measured by CM, which means that CVS technology can become a practical tool to detect the colour of jadeite-jade.

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.

Colour assessment of milk and milk products using computer vision system and colorimeter

2021 ◽  
pp. 105084
Author(s):  
Bojana Milovanovic ◽  
Ilija Djekic ◽  
Jelena Miocinovic ◽  
Bartosz G. Solowiej ◽  
Jose M. Lorenzo ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Computer Vision System ◽  
Milk Products

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

scholarly journals Task Planner for Robotic Disassembly of Electric Vehicle Battery Pack

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 387
Author(s):  
Martin Choux ◽  
Eduard Marti Bigorra ◽  
Ilya Tyapin
Keyword(s):  
Computer Vision ◽  
Electric Vehicles ◽  
Measurement Errors ◽  
Vision System ◽  
Lithium Ion ◽  
Battery Pack ◽  
Computer Vision System ◽  
Electric Vehicle Battery ◽  
Robotic Disassembly ◽  
Total Average

The rapidly growing deployment of Electric Vehicles (EV) put strong demands on the development of Lithium-Ion Batteries (LIBs) but also into its dismantling process, a necessary step for circular economy. The aim of this study is therefore to develop an autonomous task planner for the dismantling of EV Lithium-Ion Battery pack to a module level through the design and implementation of a computer vision system. This research contributes to moving closer towards fully automated EV battery robotic dismantling, an inevitable step for a sustainable world transition to an electric economy. For the proposed task planner the main functions consist in identifying LIB components and their locations, in creating a feasible dismantling plan, and lastly in moving the robot to the detected dismantling positions. Results show that the proposed method has measurement errors lower than 5 mm. In addition, the system is able to perform all the steps in the order and with a total average time of 34 s. The computer vision, robotics and battery disassembly have been successfully unified, resulting in a designed and tested task planner well suited for product with large variations and uncertainties.

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