Trajectory tracking control of a car-trailer system

Divelbiss, A.W.; Wen, John T.

doi:10.1109/87.572125

Cited by 135 publications

(71 citation statements)

References 8 publications

(11 reference statements)

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“…Motivated by the aforementioned ideas, the hierarchical control approach in mobile robotics (see [86,104,105,115]), and use of DC/DC converter-DC motor systems (see [116,117]), the purpose of the present paper is threefold. First, it aims, to introduce a three-level hierarchical controller that considers dynamics of the three subsystems that compose a WMR to solve, in a more complete way, the trajectory tracking task.…”

Section: Discussion and Contributionmentioning

confidence: 99%

“…In this subsection, controllers designed in Sections 4.1, 4.2, and 4.3 are integrated using a hierarchical approach (see [86,104,105,[115][116][117]) to solve the trajectory tracking task for a differential drive WMR when dynamics associated with each one of subsystems composing the WMR are considered (see Figure 1). Using the kinematic models associated with a differential drive WMR (1) and a reference robot (3), it was found that Complexity 7 velocity profiles and , ensuring ( , , ) → ( * , * , * ), are given by (8) and (9), respectively.…”

Section: Hierarchical Tracking Controlmentioning

confidence: 99%

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Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

et al. 2017

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The trajectory tracking task in a wheeled mobile robot (WMR) is solved by proposing a three-level hierarchical controller that considers the mathematical model of the mechanical structure (differential drive WMR), actuators (DC motors), and power stage (DC/DC Buck power converters). The highest hierarchical level is a kinematic control for the mechanical structure; the medium level includes two controllers based on differential flatness for the actuators; and the lowest hierarchical level consists of two average controllers also based on differential flatness for the power stage. In order to experimentally validate the feasibility of the proposed control scheme, the hierarchical controller is implemented via a Σ-Δ-modulator in a differential drive WMR prototype that we have built. Such an implementation is achieved by using MATLAB-Simulink and the real-time interface ControlDesk together with a DS1104 board. The experimental results show the effectiveness and robustness of the proposed control scheme.

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Section: Discussion and Contributionmentioning

confidence: 99%

Section: Hierarchical Tracking Controlmentioning

confidence: 99%

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

et al. 2017

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“…For controlling the UAV, we use a Linear Quadratic Regulator (LQR) based system [34]. The LQR problem formulation is similar to that in [35] and the resulting optimization problem is solved using DP [36]. The control policy returns a target cell location at each time step.…”

Section: Implementation-to Implement the Dynamics We Define A 6-d Stmentioning

confidence: 99%

Persistent Surveillance Using Multiple Unmanned Air Vehicles

Nigam¹,

Kroo²

2008

2008 IEEE Aerospace Conference

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Abstract-Search and exploration using multiple autonomous sensing platforms has been extensively studied in the fields of controls and artificial intelligence. The task of persistent surveillance is different from a coverage or exploration problem, in that the target area needs to be continuously searched, minimizing the time between visitations to the same region. This difference does not allow a straightforward application of most exploration techniques to the problem, although ideas from these methods can still be used. In this research we investigate techniques that are scalable, reliable, efficient, and robust to problem dynamics. These are tested in a multiple unmanned air vehicle (UAV) simulation environment, developed for this program.A semi-heuristic control policy for a single UAV is extended to the case of multiple UAVs using two methods. One is an extension of a reactive policy for a single UAV and the other involves allocation of sub-regions to individual UAVs for parallel exploration. An optimal assignment procedure (based on auction algorithms) has also been developed for this purpose. A comparison is made between the two approaches and a simplified optimal result. The reactive policy is found to exhibit an interesting emergent behavior as the number of UAVs becomes large. The control policy derived for a single UAV is modified to account for actual aircraft dynamics (a 3 degree-of-freedom nonlinear dynamics simulation is used for this purpose) and improvements in performance are observed. Finally, we draw conclusions about the utility and efficiency of these techniques.

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“…[9][10][11][12] It can, however, introduce errors that, while not an issue in some applications, can cause a significant problem if the precise location of the trailer is desired. It was assumed earlier that the geometry of the system is known.…”

Section: Iib Limitations Of the Current Methodsmentioning

confidence: 99%

UGV Trailer Position Estimation Using a Dynamic Base RTK System

Travis

Hodo

Bevly

et al. 2008

AIAA Guidance, Navigation and Control Conference and Exhibit

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In this paper, an algorithm for a dynamic base real-time kinematic (DRTK) GPS is presented and a novel application to the guidance and control of a mobile robot pulling a trailer is discussed. The DRTK system is used to estimate the relative position between the robot and trailer in the autonomous system described, and the results are compared to traditional methods utilizing an optical encoder. Geometry error is analytically predicted and the influence on trailer position is shown. Experimental results show a marginal accuracy improvement over a properly calibrated encoder based system but a significant improvement when calibration errors are present.

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Trajectory tracking control of a car-trailer system

Cited by 135 publications

References 8 publications

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

Tracking Control for Mobile Robots Considering the Dynamics of All Their Subsystems: Experimental Implementation

Persistent Surveillance Using Multiple Unmanned Air Vehicles

UGV Trailer Position Estimation Using a Dynamic Base RTK System

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