Efficient Control of a Non-Linear System Using a Modified Sliding Mode Control

Abbasi, Saad Jamshed; Kallu, Karam Dad; Lee, Min Cheol

doi:10.3390/app9071284

Cited by 11 publications

(7 citation statements)

References 19 publications

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“…SMC is robust and has good performance against perturbation. There are many practical applications of SMC includes; motor driver, robot position control, and underwater vehicles [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43]. In SMC the main idea is to design the sliding surface and move the system states to the designed sliding surface [44][45][46].…”

Section: Introductionmentioning

confidence: 99%

Robust Control Design for Accurate Trajectory Tracking of Multi-Degree-of-Freedom Robot Manipulator in Virtual Simulator

et al. 2022

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Robot manipulators have complex dynamics and meanwhile are affected by significant uncertainties and external disturbances (perturbation). Accordingly, it is a tedious task to determine the exact mathematical model of a robot manipulator. Therefore, accurate trajectory tracking is one of the dominant features in the design of position control for robot manipulators. In this research, the main objective is to design a robust and accurate position control for a robot manipulator even in case of without exact model. For this purpose, extended state observer (ESO) based sliding mode control (SMC) is proposed to achieve the desired goal. In ESO, the main concept is to define and estimate the assumed perturbation which includes known and un-known system dynamics, uncertainties, and external disturbances. Additionally, ESO also estimates the system states. This estimated perturbation information has been used as feedback term to compensate the effect of actual perturbation, which is combined with SMC input. The perturbation compensation has improved controller performance resulting in small position error, less sensitive to perturbation, and small switching gain required for SMC. The advantage of the proposed algorithm is that it requires only partial state information, position feedback. Thus, there is no need to identify the system parameters for nominal model before the controller design. The proposed algorithm is implemented and compared with conventional SMC, and sliding mode control with sliding perturbation observer (SMCSPO) in MATLAB SimMechanics based virtual environment. The comparison results validate the robustness of the proposed technique in the presence of perturbation and show a more reduced trajectory tracking error than the conventional SMC and SMCSPO.

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Section: Introductionmentioning

confidence: 99%

Robust Control Design for Accurate Trajectory Tracking of Multi-Degree-of-Freedom Robot Manipulator in Virtual Simulator

et al. 2022

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“…Pan et al studied the modification of the integral sliding variable degrades, and suggested that the switching element is smoothed by using a low-pass filter [21]. More works related to sliding mode control can be found in [22,23]. In [22] a SMC was designed to control a washout filter with constant impedance and nonlinear constant power loads.…”

Section: Introductionmentioning

confidence: 99%

“…More works related to sliding mode control can be found in [22,23]. In [22] a SMC was designed to control a washout filter with constant impedance and nonlinear constant power loads. In [23] a PDSMC was designed to collaborate with a sliding perturbation observer to control a robot manipulator.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, researchers either applied their work to nonlinear systems using numerically simulated results [21,24], or realized their algorithms in a linear system [20,22,23]. Although nonlinearities were considered in [22,23], they were treated as disturbances instead of dynamics themselves. This paper not only verifies our capability of controlling a nonlinear system by numerical simulations, but also realizes the algorithms in a TWVS using its original nonlinear model.…”

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confidence: 99%

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Proportional-Integral Sliding Mode Control with an Application in the Balance Control of a Two-Wheel Vehicle System

Lin

Hsiao

2020

Applied Sciences

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A balance control method, the proportional-integral sliding mode control (PISMC), is proposed to control the tilt attitude of an experimental two-wheel vehicle system (TWVS). Based on our previous work of implementing a generalized PISMC to control a linearized dynamical system, this paper extends the algorithm to a wider range: First, the control design of a weighted-control system is proposed. Secondly, our algorithm was realized and verified in a TWVS using its original nonlinear model. Thirdly, a systematical way to tune parameters are presented. The robustness of the proposed algorithm is also discussed in this paper. The simulation results of this work validate that the PISMC has better robustness to counteract the external disturbances than the conventional sliding mode control (SMC) does. Additionally, the experimental results show that the PISMC is capable of autonomously balancing the TWVS more effectively than the conventional SMC. The successful implementation of our algorithm potentially extends the implementation of the PISMC to various nonlinear and emerging systems.

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“…The second stage after the shutdown of an NPP is dismantling, and recently, this phase has become a critical problem. After the NPP disaster in Fukushima, Japan, NPP dismantling has gained worldwide attention [5]. As a result, researchers and various industries have continued to introduce new robot technologies that are feasible for NPP dismantling in which robots are mainly used for cutting and cleaning [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

DPSO and Inverse Jacobian-Based Real-Time Inverse Kinematics With Trajectory Tracking Using Integral SMC for Teleoperation

2020

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A six-degree-of-freedom robotic manipulator inverse kinematics (IK) for position control is proposed for the bilateral teleoperation process that is implemented through a joystick for nuclear power plant dismantling operations. The control strategy of the manipulator includes the use of the joystick to generate the Cartesian space trajectory followed by the IK to yield the joint space trajectory for implementing position control. In this paper, a novel technique for the IK is proposed. It involves the use of the particle swarm optimization (PSO) algorithm with the inverse Jacobian (IJ). The special case of the dual PSO is based on dividing the PSO algorithm into two such that the trajectory position and orientation are separately optimized by the algorithms, resulting in a faster convergence. In contrast, the inverse Jacobian aids in generating a smooth joint trajectory. The integral sliding mode control (ISMC) is proposed for position control because it does not require information on system dynamics. The ISMC improves the system trajectory tracking performance by using a switching gain to compensate for system dynamics and perturbations (disturbance and unmatched uncertainties), ultimately reducing the time delay. The effectiveness of the PSO combined with the IJ and the robustness of the ISMC in the teleoperation process are confirmed by the experimental results. INDEX TERMS Teleoperation, inverse kinematics, robotic manipulator, PSO, inverse Jacobian, ISMC

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Efficient Control of a Non-Linear System Using a Modified Sliding Mode Control

Cited by 11 publications

References 19 publications

Robust Control Design for Accurate Trajectory Tracking of Multi-Degree-of-Freedom Robot Manipulator in Virtual Simulator

Robust Control Design for Accurate Trajectory Tracking of Multi-Degree-of-Freedom Robot Manipulator in Virtual Simulator

Proportional-Integral Sliding Mode Control with an Application in the Balance Control of a Two-Wheel Vehicle System

DPSO and Inverse Jacobian-Based Real-Time Inverse Kinematics With Trajectory Tracking Using Integral SMC for Teleoperation

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