Tracking Control of Differential-Drive Wheeled Mobile Robots Using a Backstepping-Like Feedback Linearization

Chwa, Dongkyoung

doi:10.1109/tsmca.2010.2052605

Cited by 145 publications

(86 citation statements)

References 23 publications

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“…However, the opposite is true if the robot's main mission is to track a desired trajectory. The performance index J(K, ζ) depends on the feedback control gain matrix K(t) and the measurement noise ζ(t) through the state variable q(t) as it is clear from the feedback system (8). Note that the cost function (11) is similar to the performance measure defined in Bolza type problem, where φ t f , q(t f ) represents the terminal cost and t, q(t) represents the running cost [35].…”

Section: Optimal Feedback Control Lawmentioning

confidence: 99%

“…Before deriving the necessary conditions of optimality, we present the following Lemma for the robot's feedback model (8).…”

Section: Optimal Feedback Control Lawmentioning

confidence: 99%

“…Thus, the necessary conditions of optimality are given by the integral inequality (21), the costate dynamics (24), and the state equation (8). In other words, the choice of K ∈ K ad determines the optimality conditions (21), (24), and (8).…”

Section: Optimal Feedback Control Lawmentioning

confidence: 99%

“…Nevertheless, this technique does not take into account the actuator constraints. An alternative solution based on backstepping-like feedback linearization was provided in [8]. Despite its satisfactory performance, this technique might not be as effective when applied to nonlinear systems, where states are partially-observed.…”

Section: Introductionmentioning

confidence: 99%

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Mobile robot trajectory tracking using noisy RSS measurements: An RFID approach

Miah

Gueaieb

2014

ISA Transactions

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Most mobile robot navigation techniques that depend on reference RF beacons rely on approximating line-of-sight (LOS) distances between these beacons and the robot. The approximation of LOS is mostly performed using received signal strength (RSS) measurements of signals propagating between the robot and RF beacons. However, to date, relying on RSS measurements for approximating LOS distance remains a significant challenge. Accurate mapping between RSS measurements and LOS distance is almost impossible to achieve in an indoor reverberant environment. In this paper, we design a partially-observed feedback controller for a differential drive mobile robot (DDMR) where the feedback signal is in the form of noisy RSS measurements emitted from radio frequency identification (RFID) tags placed in the environment. The proposed controller does not require an accurate mapping between the LOS distance and the RSS measurements from RFID tags. In addition, it takes into account the robot's actuator (speed) constraints. Unlike many other previously devised solutions, the proposed control scheme does not require the linearization of the nonlinear DDMR model. The performance of this method is demonstrated through both numerical simulations and real-time experiments.

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Section: Optimal Feedback Control Lawmentioning

confidence: 99%

“…Before deriving the necessary conditions of optimality, we present the following Lemma for the robot's feedback model (8).…”

Section: Optimal Feedback Control Lawmentioning

confidence: 99%

Section: Optimal Feedback Control Lawmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mobile robot trajectory tracking using noisy RSS measurements: An RFID approach

Miah

Gueaieb

2014

ISA Transactions

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“…For wheeled mobile robots, conventional control laws have been applied for solving tracking problems [58,30,32,43,1,23,49] and stabilization problems [3,17,51,54,8]. For example, see [29,28,39,48,12,14] for backstepping methods [11,24,53] for sliding mode control, [9,34,18] for moving horizon H ∞ tracking control coupled with disturbance effect, and [47] for transverse function approach. A vector-field orientation feedback control method for a differentially driven wheeled vehicle has been demonstrated in [46].…”

Section: Introductionmentioning

confidence: 99%

RFID-Based Mobile Robot Trajectory Tracking and Point Stabilization Through On-line Neighboring Optimal Control

Miah

Gueaieb

2014

J Intell Robot Syst

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In this manuscript, we propose an on-line trajectorytracking algorithm for nonholonomic Differential-Drive Mobile Robots (DDMRs) in the presence of possibly large parametric and measurement uncertainties. Most mobile robot tracking techniques that depend on reference RF beacons rely on approximating line-of-sight (LOS) distances between these beacons and the robot. The approximation of LOS is mostly performed using Received Signal Strength (RSS) measurements of signals propagating between the robot and RF beacons. However, accurate mapping between RSS measurements and LOS distance remains a significant challenge and is almost impossible to achieve in an indoor reverberant environment. This paper contributes to the development of a neighboring optimal control strategy where the two major control tasks, trajectory tracking and point stabilization, are solved and treated as a unified manner using RSS measurements emitted from Radio Frequency IDentification (RFID) tags. The proposed control scheme is divided into two cascaded phases. The first phase provides the robot's nominal control inputs (speeds) and its trajectory using full-state feedback. In the second phase, we design the neighboring optimal controller, where RSS measurements are used to better estimate the robot's pose by employing an optimal filter. Simulation and experimental results are presented to demonstrate the performance of the proposed optimal feedback controller for solving the stabilization and trajectory tracking problems using a DDMR. Keywords Mobile robot navigation · RFID systems · optimal control · trajectory tracking · robot stabilization · nonholonomic systems. Frequently Used Symbols K(t)Feedback control gain at time t H K Hamiltonian's gradient with respect to K s Number of RFID tags in the environment ψ Costate variable (Lagrange multiplier)Robot's actual and desired pose at time t q j t ∈ R 3 jth tag position in 3D space t 0 ,t f Initial and final time instantsRobot's control input vector at time t ξ (t) Robot's actuator noise at time t ζ (t)Measurement noise vector at time t (·) o , (·) ε , (·) ad Optimal, perturb, admissible value of (·) L Lebesgue measurable function space ν T dJ(·) Gateaux (directional) derivative of J in direction ν 1 Introduction

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A Saturating Extension of an Output Feedback Controller for Internally Damped Euler‐Lagrange Systems

Shojaei¹,

Chatraei²

2015

Asian Journal of Control

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In this research, a novel extension of the passivity-based output feedback trajectory tracking controller is developed for internally damped Euler-Lagrange systems with input saturation. Compared with the previous output feedback controllers, this new design of a combined adaptive controller-observer system will reduce the risk of actuator saturation effectively via generalized saturation functions. Semi-global uniform ultimate boundedness stability of the tracking errors and state estimation errors is guaranteed by Lyapunov stability analysis. An application of the proposed saturated output feedback controller is the stabilization of a nonholonomic wheeled mobile robot with saturated actuators towards desired trajectories. Simulation results are provided to illustrate the efficiency of the proposed controller in dealing with the actuator saturation.

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Tracking Control of Differential-Drive Wheeled Mobile Robots Using a Backstepping-Like Feedback Linearization

Cited by 145 publications

References 23 publications

Mobile robot trajectory tracking using noisy RSS measurements: An RFID approach

Mobile robot trajectory tracking using noisy RSS measurements: An RFID approach

RFID-Based Mobile Robot Trajectory Tracking and Point Stabilization Through On-line Neighboring Optimal Control

A Saturating Extension of an Output Feedback Controller for Internally Damped Euler‐Lagrange Systems

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