Control of a Five-axle, Three-steering Coupled-vehicle System and its Experimental Verification

Yamaguchi, Hiroaki; Mori, Masato; Kawakami, Atsushi

doi:10.3182/20110828-6-it-1002.01455

Cited by 6 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The predictive model predicts the posture information of the train in the future by analyzing its current posture information and the control amount of the system. According to (11), the state space is reconstructed at time k and the predictive model is given by (15).…”

Section: Predictive Model Establishmentmentioning

confidence: 99%

“…Reference [11] proposed a trajectory following feedback control strategy for a coupled vehicle with five axles and three steering axles, and the control effect was verified through experiments. A. Astolfi et al [12] established a trajectory compensation model for an articulated semi-trailer and designed a trajectory following controller for straight and circular trajectories.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Trajectory Following Control of Modern Configurable Multi-Articulated Urban Bus Based on Model Predictive Control

Shen

Zhang

2022

Sustainability

View full text Add to dashboard Cite

The configurable and multi-articulated urban bus is a new type of urban vehicle with the advantages of road vehicles and urban rail trains. However, its articulated and long body structure will bring about difficulties in steering control and trajectory following. Moreover, the following carriages easily deviate from their expected path, leading to the fishtailing and folding of the compartment. In this paper, we propose a generic framework that allows the rapid building of kinematic models for the new train. By introducing the MPC theory, we design a trajectory tracking controller for a multi-articulated vehicle with an arbitrary number of carriages. To verify our models, we establish kinematic models and a trajectory tracking controller for a multi-articulated train with different number of compositions in MATLAB. Under the double-lane-change track and serpentine road conditions, the trajectory tracking of the train is simulated. The influence of the number of carriages, velocity, and length of carriage on the trajectory tracking are further analyzed. The experimental results show the feasibility of our method. Our findings thus provide significant guidance for the design, actual configuration, and trajectory tracking control of the new multi-articulated urban bus.

show abstract

Section: Predictive Model Establishmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Trajectory Following Control of Modern Configurable Multi-Articulated Urban Bus Based on Model Predictive Control

Shen

Zhang

2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…If The task needs more than one robot, such as co-manipulation or heavy objects transport, collaborative behaviour is required for mobile robots and many robotic examples can be mentioned such as Swarmanoid with its three different robots (Foot-Bot, Hand-Bot and Eye-Bot) which is used for collaborative transport tasks [13]. Another example of cooperative transport task is demonstrated in [14] were two coupled modules are used to transport an object. In [5], a fully distributed strategy inspired by a society of insects to perform reactive box pushing task is applied.…”

Section: Introductionmentioning

confidence: 99%

Design of Collaborative, Cross & Carry Mobile RoBots "C<sup>3</sup>Bots"

Hichri

Fauroux

Adouane

et al. 2013

AMR

View full text Add to dashboard Cite

This paper presents an introduction aboutC3Botsproject which aims to design collaborative, cross and carry mobile robots. In this project it is considered to design an innovative robotic system based on modular entities with a simple mechanical architecture able to collaborate to ensure object co-manipulation and transport. The resulting multi-robot system is calledC3Bots. In this paper we present the first version of this system using a parallelogram mechanism for co-manipulation and the realized prototypes which are going to be used for first experiments.

show abstract

“…Kinematics model is very straightforward to model the vehicle behavior, but is not informative for many complicated issues like vehicle suspensions and steering system changing or the uncertainties of tire, wheel and the road friction. However, vehicle dynamics models have been used for truck-trailer forward motion [14][15][16]. Nevertheless, there are some experiences to back up the robot like vehicle or mini farm vehicle [17,18].…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Strategy Based on Fuzzy Reinforcement Learning for Backing Truck up

Goharimanesh¹,

Akbari²

2017

IJNSE

View full text Add to dashboard Cite

show abstract

Control of a Five-axle, Three-steering Coupled-vehicle System and its Experimental Verification

Cited by 6 publications

References 12 publications

Trajectory Following Control of Modern Configurable Multi-Articulated Urban Bus Based on Model Predictive Control

Trajectory Following Control of Modern Configurable Multi-Articulated Urban Bus Based on Model Predictive Control

Design of Collaborative, Cross & Carry Mobile RoBots "C<sup>3</sup>Bots"

An Intelligent Strategy Based on Fuzzy Reinforcement Learning for Backing Truck up

Contact Info

Product

Resources

About