Omnidirectional mobile robot robust tracking: Sliding-mode output-based control approaches

Ovalle, Luis; Ríos, Héctor; Llama, Miguel A.; Santibáñez, Víctor; Dzul, A.

doi:10.1016/j.conengprac.2019.01.002

Cited by 37 publications

(20 citation statements)

References 18 publications

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“…In a tracking control problem, the objective is to track the trajectory defined in the previous layers. [3][4][5] The feedback over the internal states of the AMR is a requirement for achieving the goal in control tracking problem. Since only a part of the states of an AMR can be measured by using the provided on-board sensors, the observer algorithms are proposed for online estimation of the unmeasured states.…”

Section: Discussionmentioning

confidence: 99%

“…At the bottom layer of the process for providing the autonomy at AMRs, there are algorithms to solve the tracking control problem and observing the internal states of the AMRs. In a tracking control problem, the objective is to track the trajectory defined in the previous layers . The feedback over the internal states of the AMR is a requirement for achieving the goal in control tracking problem.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Safaei

2020

Adaptive Control & Signal

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Summary In this article, an adaptive algorithm is proposed for online velocity estimation of the autonomous mobile robots (AMRs) without positioning data received from a Global Positioning System (GPS) module or other means for odometry. Unlike the popular Kalman and particle filters that use the measurements on vectors of global (or local) position and acceleration of a mobile robot, the proposed adaptive relative velocity estimation (ARVE) algorithm requires the scalar value of measured distance to a beacon agent and also the measurement on acceleration vector, in order to generate an online estimation of the global velocity vector of a mobile robot. Combining the ARVE algorithm with the recently proposed adaptive relative position estimation (ARPE) algorithm provides a solution for online estimation of the translational states of a mobile robot without accessing the GPS data, which makes the package applicable in both indoor and outdoor environments. The stability of the ARVE algorithm is analyzed with LaSalle‐Yoshizawa theorem. In addition, two simulation studies are provided to show the application of the proposed estimation package (ARVE+ARPE) for aerial AMRs in two cases corresponding to the stationary and moving beacon agents. In the simulation results, it is shown that the estimation package can be used in conjunction with the recently proposed adaptive model‐free control (AMFC) algorithm to achieve desired tracking objective in autonomous movement of a quadrotor, without requiring the information on the internal dynamics of the robot.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Safaei

2020

Adaptive Control & Signal

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“…Real-time tracking control has always been an essential research area in robotics [1], [2]. It is important to have the robotic system reach a certain speed that drives the robot to track its desired trajectory.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Bioinspired Backstepping Control for a Mobile Robot With Unscented Kalman Filter

Yang

Gadsden

2020

IEEE Access

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Tracking control has been an important research topic in robotics. It is critical to design controllers that make robotic systems with smooth velocity commands. In addition, the robustness of the robotic system in the presence of system and measurement noises is an important consideration as well. This paper presents a novel tracking control strategy that integrates a biologically inspired backstepping controller and a torque controller with unscented Kalman filter (UKF) and Kalman filter (KF). The bioinspired backstepping controller and torque controller are capable of avoiding and reducing the velocity jumps and overshoots that occur in conventional backstepping control and provide smooth velocity commands. The integration of KF and UKF enables the proposed control strategy capable of providing accurate state estimates. The stability and convergence of tracking errors are guaranteed by Lyapunov stability analysis. The novelty of the proposed bioinspired tracking control strategy is to take the system and measurement noises and robot dynamic constraints into the consideration. The results show that the proposed control strategy provides accurate state estimates and avoids large velocity jumps and overshoot that occurs in conventional backstepping control. This tracking control strategy is suitable for autonomous mobile robots under hard conditions with system and measurement noises.

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“…Due to the existing uncertainties and nonlinearities associated with WMRMs, it is essential to design a control scheme that can robustly and optimally control such nonlinear systems [20]. Designing an appropriate trajectory tracking control system for wheeled mobile robots is a challenging issue, and it has been investigated through various approaches such as robust control [21][22][23][24][25][26][27][28][29], adaptive control [30][31][32][33], optimal control [34][35][36][37][38][39][40], and hybrid control [40][41][42][43][44][45][46] methods. A controller designed for a WMRM should enable the robot to follow a predefined path, while tackling the existing uncertainties and disturbances.…”

Section: Introductionmentioning

confidence: 99%

“…They calculated the upper bound of uncertainties by applying an adaptive law, thus making the controller immune to uncertainties. Ovalle et al [24] designed a high-order sliding mode control system for an uncertain wheeled mobile robot (WMR). In this work, they mainly focused on system robustness rather than the minimization of control effort.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking of an uncertain wheeled mobile robotic manipulator with a hybrid control approach

Shafei

Bahrami

Talebi

2020

J Braz. Soc. Mech. Sci. Eng.

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In this paper, a novel hybrid control approach is used for trajectory-tracking control of wheeled mobile robotic manipulators (WMRMs) in the presence of model uncertainties and external disturbances. Due to the existence of nonholonomic constrains in wheeled mobile robots, the proposed controller should be able to tackle the challenge of underactuation in such systems. To attain this objective, the dynamic equations of motion for a WMRM are derived in closed form using the Gibbs-Appell (G-A) formulation, which is an efficient method for obtaining the dynamic motion equations of nonholonomic systems. Then, a novel control scheme is developed which is both optimal and robust and which enjoys updated gains under an adaptive law. In this regard, to benefit from the advantages of two distinct methods, a high-order sliding mode control (HOSMC) is employed as a robust controller with the aim of handling system uncertainties and a state-dependent Riccati equation (SDRE) is used as a nonlinear optimal controller. In order to systematically deal with system uncertainties and to avoid the manual calculation of the upper bound of uncertainties, the gain of HOSMC is updated via an adaptive law. The most important advantage of this novel approach over the existing methods is that not only is it robustly stable against external disturbances when controlling an uncertain nonlinear system but also optimal for a predefined quadratic cost function. Lyapunov stability theory is employed to verify the stability of the proposed controller. Finally, to demonstrate the superiority of this novel controller, computer simulation results for a WMRM are compared with those of an adaptive sliding mode controller. It can be observed that the proposed hybrid control approach is capable of optimizing control inputs while achieving stability for a WMRM in the presence of model uncertainties.

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Omnidirectional mobile robot robust tracking: Sliding-mode output-based control approaches

Cited by 37 publications

References 18 publications

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Enhanced Bioinspired Backstepping Control for a Mobile Robot With Unscented Kalman Filter

Trajectory tracking of an uncertain wheeled mobile robotic manipulator with a hybrid control approach

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