scholarly journals Design and error compensation of active mechanically automated guided vehicle

2021 ◽  
Vol 22 ◽  
pp. 14
Author(s):  
Jianqiang Yan ◽  
Mi Li ◽  
Zhongxiang Chen ◽  
Yihang Li
Keyword(s):  
Error Compensation ◽  
Steering System ◽  
Automated Guided Vehicle ◽  
Steering Control ◽  
Control Cost ◽  
Directional Control ◽  
Quintic Polynomial ◽  
Control Scheme ◽  
Vehicle Trajectory ◽  
Compensation Approach

To reduce the navigation control cost, this paper proposes a mechanical guidance control scheme that uses a cam-link mechanism as a steering control mechanism for an automated guided vehicle with a fixed driving path. According to the steering principle, a mathematical model of the steering system and the driving trajectory are established. By setting the boundary conditions, the vehicle trajectory is modeled using a quintic polynomial. The contour of the directional control cam is obtained based on the equation of the vehicle trajectory. Because errors occur in actual machining and assembly processes, errors will be classified based on their impact on the trajectory. The effects of various errors on the trajectory are quantitatively determined by using simulation methods with different parameters. Furthermore, an error compensation approach is designed to reduce the influence of the error on the trajectory directly or indirectly. Finally, experiment results illustrate that the adjustment accuracy of the proposed automated guided vehicle trajectory is 2 mm.

A Study on μ-Synthesis Control for Four-Wheel Steering System to Enhance Vehicle Lateral Stability

2010 ◽  
Vol 133 (1) ◽  
Author(s):  
Guo-Dong Yin ◽  
Nan Chen ◽  
Jin-Xiang Wang ◽  
Ling-Yao Wu
Keyword(s):  
Control System ◽  
Experimental Tests ◽  
Steering System ◽  
Hardware In The Loop ◽  
Steering Control ◽  
Robust Controller ◽  
Control Scheme ◽  
Parameter Variations ◽  
Good Vehicle ◽  
Selection Of

This paper presents the design of μ-synthesis control for four-wheel steering (4WS) vehicle and an experimental study using a hardware-in-the-loop (Hil) setup. First, the robust controller is designed and the selection of weighting functions is discussed in the framework of μ-synthesis control scheme, considering the varying parameters induced by running vehicle condition. Second, in order to investigate the feasibility of the four-wheel steering control system, the 4WS vehicle control system is built using dSPACE DS1005 platform. The experimental tests are performed using the Hil setup which has been constructed using the devised rear steering actuating system. The dynamics performance is evaluated by experiment using the Hil setup under the condition of parameter variations. Finally, experimental results show that the μ-synthesis controller can enhance good vehicle lateral maneuverability.

Independent wheel control system design for highly automated driving

2021 ◽  
pp. 095440702110065
Author(s):  
Shihuan Li ◽  
Lei Wang
Keyword(s):  
Control System ◽  
Control Method ◽  
Autonomous Driving ◽  
Control System Design ◽  
Steering Control ◽  
Automated Driving ◽  
Accuracy And Precision ◽  
Actual Observation ◽  
Control Scheme ◽  
Interference Measurement

For L4 and above autonomous driving levels, the automatic control system has been redundantly designed, and a new steering control method based on brake has been proposed; a new dual-track model has been established through multiple driving tests. The axle part of the model was improved, the accuracy of the transfer function of the model was verified again through acceleration-slide tests; a controller based on interference measurement was designed on the basis of the model, and the relationships between the controller parameters was discussed. Through the linearization of the controller, the robustness of uncertain automobile parameters is discussed; the control scheme is tested and verified through group driving test, and the results prove that the accuracy and precision of the controller meet the requirements, the robustness stability is good. Moreover, the predicted value of the model fits well with the actual observation value, the proposal of this method provides a new idea for avoiding car out of control.

Differential steering-based electric vehicle lateral dynamics control with rollover consideration

2019 ◽  
Vol 234 (3) ◽  
pp. 338-348
Author(s):  
Hui Jing ◽  
Rongrong Wang ◽  
Cong Li ◽  
Jinxiang Wang
Keyword(s):  
Electric Vehicles ◽  
Measurement Problem ◽  
Low Cost ◽  
Steering System ◽  
Front Wheel ◽  
Steering Control ◽  
Lateral Velocity ◽  
Lateral Dynamics ◽  
Vehicle Rollover ◽  
Differential Steering

This article investigates the differential steering-based schema to control the lateral and rollover motions of the in-wheel motor-driven electric vehicles. Generated from the different torque of the front two wheels, the differential steering control schema will be activated to function the driver’s request when the regular steering system is in failure, thus avoiding dangerous consequences for in-wheel motor electric vehicles. On the contrary, when the vehicle is approaching rollover, the torque difference between the front two wheels will be decreased rapidly, resulting in failure of differential steering. Then, the vehicle rollover characteristic is also considered in the control system to enhance the efficiency of the differential steering. In addition, to handle the low cost measurement problem of the reference of front wheel steering angle and the lateral velocity, an [Formula: see text] observer-based control schema is presented to regulate the vehicle stability and handling performance, simultaneously. Finally, the simulation is performed based on the CarSim–Simulink platform, and the results validate the effectiveness of the proposed control schema.

scholarly journals CycleGAN for interpretable online EMT compensation

2021 ◽  
Author(s):  
Henry Krumb ◽  
Dhritimaan Das ◽  
Romol Chadda ◽  
Anirban Mukhopadhyay
Keyword(s):  
Error Compensation ◽  
Qualitative Assessment ◽  
Electromagnetic Tracking ◽  
Invasive Procedures ◽  
Phantom Experiment ◽  
X Ray ◽  
Reduce Radiation Exposure ◽  
Rotational Error ◽  
Clinical Reality ◽  
Compensation Approach

Abstract Purpose Electromagnetic tracking (EMT) can partially replace X-ray guidance in minimally invasive procedures, reducing radiation in the OR. However, in this hybrid setting, EMT is disturbed by metallic distortion caused by the X-ray device. We plan to make hybrid navigation clinical reality to reduce radiation exposure for patients and surgeons, by compensating EMT error. Methods Our online compensation strategy exploits cycle-consistent generative adversarial neural networks (CycleGAN). Positions are translated from various bedside environments to their bench equivalents, by adjusting their z-component. Domain-translated points are fine-tuned on the x–y plane to reduce error in the bench domain. We evaluate our compensation approach in a phantom experiment. Results Since the domain-translation approach maps distorted points to their laboratory equivalents, predictions are consistent among different C-arm environments. Error is successfully reduced in all evaluation environments. Our qualitative phantom experiment demonstrates that our approach generalizes well to an unseen C-arm environment. Conclusion Adversarial, cycle-consistent training is an explicable, consistent and thus interpretable approach for online error compensation. Qualitative assessment of EMT error compensation gives a glimpse to the potential of our method for rotational error compensation.

scholarly journals Adaptive Cluster Synchronization for Nondelayed and Delayed Coupling Complex Networks with Nonidentical Nodes

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ze Tang ◽  
Jianwen Feng
Keyword(s):  
Sufficient Conditions ◽  
Pinning Control ◽  
Cluster Synchronization ◽  
Linear Matrix ◽  
Control Cost ◽  
Synchronization Problem ◽  
Delayed Coupling ◽  
Control Scheme ◽  
Successful Control ◽  
Synchronization Pattern

We focus on the cluster synchronization problem for a kind of general networks with nondelayed and delayed coupling. Based on the pinning control scheme, a small fraction of the nodes in each cluster are pinned for successful control, and the states of the whole dynamical networks can be globally forced to the objective cluster states. Sufficient conditions are derived to guarantee the realization of the cluster synchronization pattern for all initial values by means of the Lyapunov stability theorem and linear matrix inequalities (LMIs). By using the adaptive update law, relative smaller control gains are obtained, and hence the control cost can be substantially lower. Numerical simulations are also exploited to demonstrate the effectiveness and validity of the main result.

Improving the Accuracy of Multi-Axis Machines Through On-Line Error Compensation Using Neural Networks

1998 ◽  
Author(s):  
Abderrazak El Ouafi ◽  
Michel Guillot ◽  
Abdellah Bedrouni
Keyword(s):  
Error Compensation ◽  
Error Modeling ◽  
Precision Engineering ◽  
Dimensional Error ◽  
New Approach ◽  
Turning Center ◽  
On Line ◽  
Dynamic Errors ◽  
Compensation Approach ◽  
Compensation Function

Abstract This research is devoted to one of the most fundamental problems in precision engineering: multi-axis machines accuracy. The paper presents a new approach designed to support the implementation of software error compensation of geometric, thermal and dynamic errors for enhancing the accuracy of multi-axis machines. The accuracy of multi-axis machines can be significantly improved using an intelligent integration of sensor information to perform the compensation function. The compensation process consists of the following major steps carried out on-line: continuous monitoring of the machine conditions using position, force, speed and temperature sensors mounted on the machine structure. Error forecasting through sensor fusion. Volumetric error synthesis and software compensation. To improve the effectiveness of error modeling, an artificial neural network is extensively applied. Implemented on a turning center, the compensation approach has enabled improvement of the machine accuracy by reducing the maximum dimensional error from 70 μm initially to less than 4 μm.

scholarly journals Model predictive control–based steering control algorithm for steering efficiency of a human driver in all-terrain cranes

2019 ◽  
Vol 11 (6) ◽  
pp. 168781401985978
Author(s):  
Ja-Ho Seo ◽  
Kwang-Seok Oh ◽  
Hong-Jun Noh
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Steering System ◽  
Driver Model ◽  
Control Technique ◽  
Change Scenario ◽  
Steering Control ◽  
Human Driver ◽  
Steering Effort

All-terrain cranes with multi-axles have large inertia and long distances between the axles that lead to a slower dynamic response than normal vehicles. This has a significant effect on the dynamic behavior and steering performance of the crane. Therefore, the purpose of this study is to develop an optimal steering control algorithm with a reduced driver steering effort for an all-terrain crane and to evaluate the performance of the algorithm. For this, a model predictive control technique was applied to an all-terrain crane, and a steering control algorithm for the crane was proposed that could reduce the driver’s steering effort. The steering performances of the existing steering system and the steering system applied with the newly developed algorithm were compared using MATLAB/Simulink and ADAMS with a human driver model for reasonable performance evaluation. The simulation was performed with both a double lane change scenario and a curved-path scenario that are expected to happen in road-steering mode.

scholarly journals Research on vehicle active steering control based on linear matrix inequality and hardware in the loop test scheme design and implement for active steering

2019 ◽  
Vol 11 (11) ◽  
pp. 168781401989210 ◽  
Author(s):  
Guangfei Xu ◽  
Peisong Diao ◽  
Xiangkun He ◽  
Jian Wu ◽  
Guosong Wang ◽  
...  
Keyword(s):  
Linear Matrix Inequality ◽  
Model Uncertainty ◽  
Control Method ◽  
Steering System ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Steering Control ◽  
Sensor Noise ◽  
Active Steering ◽  
Active Steering Control

In the research process of automotive active steering control, due to the model uncertainty, road surface interference, sensor noise, and other influences, the control accuracy of the active steering system will be reduced, and the driver’s road sense will become worse. The traditional robust controller can solve the model uncertainty, pavement disturbance and sensor noise in the design process, but cannot consider the performance enough. Therefore, this article proposes an active steering control method based on linear matrix inequality. In this method, the model uncertainty, road interference, sensor noise, yaw velocity, and slip side angle tracking errors are all considered as constraint targets, respectively, so that the performance and robust stability of the active front steering system can be guaranteed. Finally, simulation and hardware in the loop experiment are implemented to verify the effect of active front steering system under the linear matrix inequality controller. The results show that the proposed control method can achieve better robust performance and robust stability.

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