Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels

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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INTEGRAL SLIDING MODE CONTROL FOR TRAJECTORY TRACKING CONTROL OF ROBOTIC MANIPULATORS USING AN ADAPTIVE TWISTING ALGORITHM

Journal of Science and Technology Issue on Information and Communications Technology ◽

10.31130/ict-ud.2019.88 ◽

2019 ◽

Vol 17 (12.2) ◽

pp. 42

Author(s):

Anh Tuan Vo ◽

Ngoc Hoai An Nguyen ◽

Duy Duong Pham

Keyword(s):

Sliding Mode Control ◽

Trajectory Tracking ◽

Tracking Control ◽

Control Method ◽

Sliding Mode ◽

Robotic Manipulators ◽

Trajectory Tracking Control ◽

Integral Sliding Mode Control ◽

Integral Sliding Mode ◽

Mode Control

This paper proposes an integral sliding mode for trajectory tracking control of robotic manipulators. Our proposed control method is developed on the foundation of the benefits in both integral sliding mode control and adaptive twisting control algorithm, such as high robustness, high accuracy, estimation ability, and chattering elimination. In this paper, the proposed integral sliding mode controller is designed with the elimination of the reaching phase to offer better trajectory tracking precision and to stabilize the robot system. To reduce the calculation burden along with chattering rejection, an adaptive twisting controller with only one simple adaptive rule is employed to estimate the upper-boundary values of the lumped uncertainties. Accordingly, the requirement of their prior knowledge is removed and then decrease the computation complexity. Consequently, this control method provides better trajectory tracking accuracy to handle the dynamic uncertainties and external disturbances more strongly. The system global stability of the control system is guaranteed by using Lyapunov criteria. Finally, simulated examples are performed to analyze the effectiveness of our control approach for position pathway tracking control of a 2-DOF parallel manipulator.

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Robust Trajectory Tracking Control of a Mobile Robot Combining PDC and Integral Sliding Mode Control

The Journal of the Korean Institute of Information and Communication Engineering ◽

10.6109/jkiice.2015.19.7.1694 ◽

2015 ◽

Vol 19 (7) ◽

pp. 1694-1704

Author(s):

Min-soo Park ◽

Seung-kyu Park ◽

Ho-kyun Ahn ◽

Gun-pyong Kwak ◽

Tae-sung Yoon

Keyword(s):

Sliding Mode Control ◽

Mobile Robot ◽

Trajectory Tracking ◽

Tracking Control ◽

Sliding Mode ◽

Trajectory Tracking Control ◽

Integral Sliding Mode Control ◽

Integral Sliding Mode ◽

Mode Control

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Adaptive fuzzy radial basis function neural network integral sliding mode tracking control for heavy vehicle electro-hydraulic power steering systems

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407019846378 ◽

2019 ◽

Vol 234 (2-3) ◽

pp. 872-886

Author(s):

Heng Du ◽

Lin Wang ◽

Jinda Chen ◽

Hui Huang ◽

Yunchao Wang

Keyword(s):

Sliding Mode Control ◽

Tracking Control ◽

Sliding Mode ◽

Hydraulic Power ◽

Integral Sliding Mode Control ◽

Integral Sliding Mode ◽

Adaptive Fuzzy ◽

Mode Control ◽

Power Steering ◽

Hydraulic Power Steering

Due to parametric uncertainties, unknown nonlinearities, and dynamic external disturbances, it is a challenging and valuable task for heavy vehicle electro-hydraulic power steering systems to realize high-precision tracking control. To cope with this complex nonlinear tracking control problem, the integral sliding mode control is an extremely potential control method, which has strong robustness to model uncertainties and unknown disturbances, and can effectively reduce the steady-state error in tracking control process. However, the inherent chattering phenomenon of integral sliding mode control seriously affects its control performance. In order to suppress the chattering while ensuring robustness, adaptive fuzzy technique is adopted as an effective auxiliary means, which can not only deal with the inherent chattering problem of integral sliding mode control and a priori knowledge of the disturbance upper bound in controller design but also dynamically adjust the parameters in the fuzzy rules. Moreover, the designed adaptive fuzzy–integral sliding mode control scheme still needs the precise mathematical models of the control systems. But it is difficult to obtain the model for heavy vehicle electro-hydraulic power steering systems with highly complex and coupling properties. Therefore, to further improve the method, this paper presents a novel adaptive fuzzy–radial basis function neural network–integral sliding mode control method for the complex systems to achieve timely and accurate steering angle tracking control. In addition to the advantages of adaptive fuzzy–integral sliding mode control, the modified controller no longer requires the precise mathematical models of heavy vehicle electro-hydraulic power steering systems and realizes the continuous adaptive updating of weights. Finally, the effectiveness and superiority of the proposed control scheme is illustrated by comparisons and extensive simulations.

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