Adaptive backstepping sliding mode control based on nonlinear disturbance observer for trajectory tracking of robotic manipulator

Mustafa, Aquib; Dhar, Narendra Kumar; Agrawal, Pooja; Yerma, Nishchal K.

doi:10.1109/iccre.2017.7935036

Cited by 15 publications

(8 citation statements)

References 15 publications

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“…In this section, a feedback tracking controller is proposed to realize trajectory tracking through the backstepping method. 25,30 For the tracked vehicle, tracking the desired trajectory is equal to following a virtual reference tracked vehicle from the initial position. The trajectory of the reference tracked vehicle is given and the kinematic model also satisfies the non-holonomic constraints represented by (x r , y r , θ r ).…”

Section: Motion Controller Designmentioning

confidence: 99%

“…There are a number of researches on the tracking control techniques of non-holonomic mobile units at home and abroad. 25,27 Backstepping method is employed here to design a discontinuous trajectory tracking controller for its fast and asymptotically trajectory tracking performance. However, there will be a large position deviation under certain initial errors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Motion Control and Trajectory Planning for Obstacle Avoidance of the Mobile Parallel Robot Driven by Three Tracked Vehicles

Shentu¹,

Xie²,

Liu³

et al. 2020

Robotica

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SUMMARY This paper proposes a mobile parallel robot (MPR) and focuses on obstacle avoidance. When analyzing the collision-free trajectories, the coupling constraints caused by the parallel mechanism and the obstacle should be emphatically solved. The solution is to divide the problem into two steps. First, the genetic algorithm is employed to search and optimize the feasible trajectories under the mechanism constraint of the MPR. Then the trajectory tracking controller is designed to make the tracked vehicles move cooperatively and track a trajectory asymptotically. Finally, simulations and experiments are carried out to verify the effectiveness of the solution.

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Section: Motion Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Motion Control and Trajectory Planning for Obstacle Avoidance of the Mobile Parallel Robot Driven by Three Tracked Vehicles

Shentu¹,

Xie²,

Liu³

et al. 2020

Robotica

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show abstract

“…However, a disturbance observer is employed to explore the information about the characteristic of external disturbance and estimate it; consequently, it improves the performance of controllers. Variants of disturbance observers, such as fractional‐order disturbance observer [12, 13], self‐learning disturbance observer [14], disturbance observer‐based integral backstepping control [15], disturbance observer‐based backstepping SMC [16], and disturbance observer‐based global SMC [17] have been used to estimate the disturbance and improve the controller. However, the existing research results do not guarantee the prescribed finite time convergence of disturbance approximation error to zero.…”

Section: Introductionmentioning

confidence: 99%

Adaptive prescribed‐time disturbance observer using nonsingular terminal sliding mode control: Extended Kalman filter and particle swarm optimization

Vahidi-Moghaddam

Rajaei

Ayati

et al. 2020

IET Control Theory & Appl

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In this study, adaptive prescribed finite-time stabilisation of uncertain single-input and single-output non-linear systems is considered in the presence of unknown states, unknown parameters, external load disturbance, and non-symmetric input saturation. A prescribed finite time disturbance observer is designed to approximate the unmeasured external disturbance. Also, a non-singular prescribed finite time terminal sliding mode control is proposed for the closed-loop control of the system with the non-symmetric input saturation. Extended Kalman filter algorithm is employed for the real-time estimations of the states and unknown parameters of the system. Moreover, a particle swarm optimisation algorithm is used to obtain the design parameters of the proposed disturbance observer and controller. To show the performance of designed control scheme, the proposed approach is employed to guarantee prescribed finite time stabilisation of non-linear vibration of a non-local strain gradient nanobeam. The Galerkin projection method is used to reduce the non-dimensional form of the governing non-linear partial differential equation of Euler-Bernoulli nanobeam to the ordinary differential equation. Finally, numerical simulations are performed to illustrate the effectiveness and performance of the developed adaptive control scheme for the vibration control of nanobeam in comparison with the conventional sliding mode control.

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“…The forward movement of the manipulator is described in the form of a curve, which indicates the movement of the centre of the robot from the start to the target point The curve indicating the orientation of the grip forms the rotational path of the robot. In turn, the manipulator's movement trajectory consists of a set of points that describe the robot's forward movement path and the rotational path of the grip as a function of time [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Designing intelligent system for planning robot manipulator real-time movement in unknown dynamic environment

Nemeiksyte

Osadčuks

2020

19th International Scientific Conference Engineering for Rural Development Proceedings

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Uncertainty caused by presence of unknown static and dynamic obstacles in the robot's operating area while detecting biological objects and expressed by obstacle detection sensor error level, as well as alternating locations of such obstacles result in the need to develop methods of planning and controlling robot movement. Essence of these methods: after a robot is given a task during the process of planning, a safe trajectory of movement is designed in real time considering the possible robot configurations, as well as information concerning the environment that was detected by the sensors. The desired robot configurations are then formed during the process when the trajectory is generated, that is, time functions. The obtained trajectory is the key control factor that shapes appropriate signals to generate torque, which ensures that the robot moves along a safe trajectory with the least possible error to reach the destination point. Therefore, the subject of research in this article is a robotic arm intended for detection and elimination-destruction of biological objects, and the goal is to develop a method of designing an intelligent system for planning robot manipulator real-time movement in an unknown dynamic environment and perform computer simulation with the obtained system in the V-REP and MatLAB environments. Based on the above, the missing parameters for the experimental mobile robot have been calculated in the article and a model of a robotic arm has been developed to analyse the peculiarities and problems of using an intelligent planning system. As a result of the research performed in the article, significant data have been obtained, based on which a method of planning mobile robot movement in an unknown dynamic environment using an intelligent planning system was proposed allowing to improve the accuracy and efficiency of movement planning.

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Adaptive backstepping sliding mode control based on nonlinear disturbance observer for trajectory tracking of robotic manipulator

Cited by 15 publications

References 15 publications

Motion Control and Trajectory Planning for Obstacle Avoidance of the Mobile Parallel Robot Driven by Three Tracked Vehicles

Motion Control and Trajectory Planning for Obstacle Avoidance of the Mobile Parallel Robot Driven by Three Tracked Vehicles

Adaptive prescribed‐time disturbance observer using nonsingular terminal sliding mode control: Extended Kalman filter and particle swarm optimization

Designing intelligent system for planning robot manipulator real-time movement in unknown dynamic environment

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