Continuous finite‐time control for uncertain robot manipulators with integral sliding mode

Zhang, Liyin; Liu, Linzhi; Wang, Zeng; Xia, Yuquan

doi:10.1049/iet-cta.2017.1361

Cited by 94 publications

(106 citation statements)

References 32 publications

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“…Another advantage of OISMC is that such control scheme can be easily designed for a multivariable system without amplifying unmatched uncertainty [40]. In this paper, the control law of OISMC is described as: (23) By combining the basic LQR control in u_o and a switching control part (u swOISMC ), u OISMC can be rewritten as: (24) where δ O is a scalar gain matrix to enforce the sliding motion, and s OISMC is the integral sliding function of OISMC. s OISMC can be defined as: (25) where F=(B T B) -1 B T such that the matrix FB becomes nonsingular and does not amplify the effect of unmatched uncertainty.…”

Section: Optimal Integral Sliding Mode Controlmentioning

confidence: 99%

“…As many researchers have studied the position tracking problem, various modern controls have been developed to satisfy tracking performance, such as model predictive control (MPC) [20], computed torque control (CTC) [21], adaptive control [22,23], and sliding mode control (SMC), as in [3,24]. In comparison to CTC, MPC offers low sensitivity against model imperfection.…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Study of LQR and Integral Sliding Mode Control Strategies for Position Tracking Control of Robotic Manipulators

Norsahperi

Danapalasingam

2020

Int. j. electr. comput. eng. syst. (Online)

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This paper provides a systematic comparative study of position tracking control of nonlinear robotic manipulators. The main contribution of this study is a comprehensive numerical simulation assessing position tracking performances and energy consumption of integral sliding mode control (ISMC), a linear-quadratic regulator with integral action (LQRT ), and optimal integral sliding mode control (OISMC) under three conditions; namely, Case I) without the coupling effect, Case II) with the coupling effect on Link 1 only, and Case III) with the coupling effect on Link 2 only. The viability of the concept is evaluated based on three performance criteria, i.e., the step-response characteristics, position tracking error, and energy consumption of the aforementioned controllers. Based upon the simulation study, it has been found that OISMC offers performances almost similar to ISMC with more than 90% improvement of tracking performance under several cases compared to LQRT; however, energy consumption is successfully reduced by 3.6% in comparison to ISMC. Energy consumption of OISMC can be further reduced by applying optimization algorithms in tuning the weighting matrices. This paper can be considered significant as a robotic system with high tracking accuracy and low energy consumption is highly demanded to be implemented in smart factories, especially for autonomous systems.

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Section: Optimal Integral Sliding Mode Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comparative Study of LQR and Integral Sliding Mode Control Strategies for Position Tracking Control of Robotic Manipulators

Norsahperi

Danapalasingam

2020

Int. j. electr. comput. eng. syst. (Online)

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“…It provides robustness and stability. In the literature, it is endowed that SMC is efficacious in controlling the extensive series of plants including discrete-time systems, non-linear highly coupled uncertain systems and MIMO (multiple-input multipleoutput) system [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. As SMC provide robustness and stability; so in surgical robots, there is a requirement of SMC.…”

Section: Sliding Mode Control For Robotic Manipulatormentioning

confidence: 99%

“…In PID-SMC, the PID [10][11][12][13][14][15][16][17] based sliding surface includes the derivative part along with integral term to minimize the error i.e. specified by:…”

Section: Sliding Mode Control For Robotic Manipulatormentioning

confidence: 99%

“…Therefore, the blending of FOPID and SMC will be advantageous in enhancing the performance and robustness to the system. But chattering is still the major impediment to the application of SMC and extremely deteriorates the tracking performance of the controlled manipulator [2][3][4][5][6][7][8][9][10]. Hence, in this paper the smoothing FOPID-SMC for robotic-assisted surgery has been proposed that alleviates the chattering and increases the precision compared to conventional SMC.…”

Section: Introductionmentioning

confidence: 99%

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Design of Smoothing FOPID Sliding Mode Controlled Robotic Manipulator for Robotic-Assisted Surgery

Sachan¹,

Swarnkar²,

Nema³

2019

IJRTE

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Robotic-assisted surgery (RAS) is a mode of technical advancement in the medical field that utilizes robotic articulation to aid surgeries. The fine-motion and precise control of robotic manipulator is prerequisite in surgical applications. In this paper, the improved control methodology for controlling the 3DOF (degree of freedom) robotic manipulator's motion named as smoothing fractional order proportional integral derivativesliding mode control (FOPID-SMC) for the attainment of finest results by eliminating the perturbations has been showcased. The performance of smoothing FOPID-SMC controller in robotic manipulator is compared with the conventional SMC controllers. The simulation results prominently illustrate the efficacy of the proposed methodology, and superior tracking and robust performance with alleviated chattering compared to the classical methodologies. Index Terms: DOF (Degree of freedom), FOPID-SMC, Robotic-assisted surgery (RAS), Robotic manipulator, SMCI.

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Task space control of the robot manipulators with adaptive fuzzy global fast terminal sliding mode control in presence of dynamic and kinematic uncertainties

Soltanpour,

Zaare

2023

Adaptive Control & Signal

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SummaryBasic features such as convergence time and speed, number‐action control coefficients, free chattering, and proof of stability are significant in the design process and sliding mode control (SMC) efficiency. In this article, we propose an adaptive fuzzy global fast terminal SMC (AFGFTSMC) to handle the mentioned features in the task space control of the robot manipulator in the presence of dynamic and kinematic uncertainties. First, perturbed joint space dynamic equations of the system are transferred to task space, and a broad range of uncertainties are considered there. Then, a global fast terminal SMC (GFTSMC) is proposed for robot manipulators in task space, in which a flexible sliding surface improves the convergence time. Next, to have an intelligent adjustment of the sliding surface coefficients, which leads to a much faster convergence rate, a fuzzy approximator with just seven fuzzy rules is presented. In the following, to access the boundaries of the existing uncertainties, an adaptive fuzzy approximator is proposed, which has five fuzzy rules and only one adaptive law, increases the system's robustness, and eliminates the effect of chattering. Mathematical proof shows that the task space closed‐loop control system under the proposed AFGFTSMC and in the presence of dynamic and kinematic uncertainties has a finite‐time global asymptotic stability. The theoretical evidence and simulation results, which are conducted on a 2‐link robot manipulator, confirm the good efficiency of the proposed controller.

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Continuous finite‐time control for uncertain robot manipulators with integral sliding mode

Cited by 94 publications

References 32 publications

A Comparative Study of LQR and Integral Sliding Mode Control Strategies for Position Tracking Control of Robotic Manipulators

A Comparative Study of LQR and Integral Sliding Mode Control Strategies for Position Tracking Control of Robotic Manipulators

Design of Smoothing FOPID Sliding Mode Controlled Robotic Manipulator for Robotic-Assisted Surgery

Task space control of the robot manipulators with adaptive fuzzy global fast terminal sliding mode control in presence of dynamic and kinematic uncertainties

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