Object tracking and following six-legged robot system using Kinect camera based on Kalman filter and backstepping controller

Gulalkari, Amruta Vinod; Pratama, Pandu Sandi; Hoang, Giang; Kim, Dae Hwan; Jun, Bong Huan; Kim, Sang Bong

doi:10.1007/s12206-015-1144-4

Cited by 11 publications

(4 citation statements)

References 3 publications

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“…A simple control scheme based on nonlinear control theory is employed to force the WT to extract the maximum power from the wind regardless of the operating conditions. Among the different nonlinear control strategies that have received a lot of attention in recent years in various applications, we can mention synergistic control (SC) [28][29][30][31] and backstepping control (BS) [32][33][34][35]. Because these control techniques can be applied directly to the nonlinear model of the system to be controlled, in this work, we have chosen to use them alongside the OTC-MPPT to control a boost converter and improve the efficiency of the studied WTE.…”

Section: Introductionmentioning

confidence: 99%

Experimental Analysis of a New Low Power Wind Turbine Emulator Using a DC Machine and Advanced Method for Maximum Wind Power Capture

Boudjemai,

Ardjoun,

Chafouk

et al. 2023

IEEE Access

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This paper presents a new design of an experimental low power Wind Turbine Emulator (WTE) which has the advantage of being simple and easy to implement in practice. The proposed emulator takes into account the effect of Wind Turbine (WT) inertia as well as the nonlinearities in the system which make it suitable for all types of WTs. An efficient Maximum Power Point Tracking (MPPT) algorithm based on synergetic and backstepping nonlinear control theory has also been proposed to allow the WT to extract maximum power under a wide range of operating conditions. This is achieved by regulating the current at the input of the boost converter through these controllers. Furthermore, these nonlinear controllers considerably reduce the complexity of the design of the control scheme. Several experimental

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Section: Introductionmentioning

confidence: 99%

Experimental Analysis of a New Low Power Wind Turbine Emulator Using a DC Machine and Advanced Method for Maximum Wind Power Capture

Boudjemai,

Ardjoun,

Chafouk

et al. 2023

IEEE Access

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“…The tuning process of different controllers such as PID and FOPID need to be highly taken care of to present the best performance of autonomous robotic systems. Thus, many researchers proposed different controller approaches such as the state-dependent Riccati equation [6], Kalman filter and backstepping design [7], adaptive neural network design [8], a neural approximation based on model predictive tracking control [9], genetic algorithm (GA) and fuzzy approach [10,11].…”

Section: Introductionmentioning

confidence: 99%

An adaptive neuro-fuzzy based on a fractional-order proportional integral derivative design for a two-legged robot with an improved swarm algorithm

Wassef

Hadi

2023

Eng. rev. (Online)

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In this paper, an adaptive neuro-fuzzy based on fractional-order proportional-integral-derivative (ANFFOPID) controller with an improved slime mould algorithm (ISMA) for the two-legged robot (TLR) is proposed to achieve the minimum angular displacement error of the joint motors. Achieving such error is considered a challenging and time-consuming process due to the gain values set for the FOPID controller. Thus the neural-fuzzy network is used to provide the FOPID input signals by the adaptive magnitude gains. The adaptive mechanism depends on the ISMA to train the neural network weights. The outstanding properties of the ANFFOPID controller are evaluated by comparing the proposed controller with other existing work that is modified chaotic invasive weed optimization based on neural network (MCIWO-NN) for various walking terrains that are flat surface, stair ascending, and stair descending. Finally, the results obtained show the effectiveness of the ANFFOPID controller.

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“…A third approach used a standard Kalman filter to assist in object tracking [5]. A mobile robot was equipped with a Microsoft Kinect camera to identify a candidate object, and Kalman filtering was used to help correctly estimate the relative distance to the object for the robot trajectory.…”

Section: Introductionmentioning

confidence: 99%

Development of a Control and Estimation Strategy for a Six-Link Robot Manipulator

Hall¹,

Lee²,

Gadsden³

2020

Progress in Canadian Mechanical Engineering. Volume 3

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This paper covers the ongoing approach of creating new combinations of robot controllers with filtering techniques. It outlines the need for such a system and a current controller system that uses filtering techniques to improve accuracy. It also explains how the proposed approach differs from the systems in literature. This paper outlines how the system is designed and tested. It explains the approach taken to design a system, and how the performance of the system will be measured. Finally, it explains progress that has been achieved, as well as recommendations for future work.

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Object tracking and following six-legged robot system using Kinect camera based on Kalman filter and backstepping controller

Cited by 11 publications

References 3 publications

Experimental Analysis of a New Low Power Wind Turbine Emulator Using a DC Machine and Advanced Method for Maximum Wind Power Capture

Experimental Analysis of a New Low Power Wind Turbine Emulator Using a DC Machine and Advanced Method for Maximum Wind Power Capture

An adaptive neuro-fuzzy based on a fractional-order proportional integral derivative design for a two-legged robot with an improved swarm algorithm

Development of a Control and Estimation Strategy for a Six-Link Robot Manipulator

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