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Adaptive Task Space Non-Singular Terminal Super-Twisting Sliding Mode Control of a 7-DOF Robotic Manipulator

Wan, L., Smith, S., Pan, Y. -J., Witrant, E.

arXiv.org Artificial Intelligence

--This paper presents a new task-space Non-singular Terminal Super-Twisting Sliding Mode (NT -STSM) controller with adaptive gains for robust trajectory tracking of a 7-DOF robotic manipulator. The proposed approach addresses the challenges of chattering, unknown disturbances, and rotational motion tracking, making it suited for high-DOF manipulators in dexterous manipulation tasks. A rigorous boundedness proof is provided, offering gain selection guidelines for practical implementation. Simulations and hardware experiments with external disturbances demonstrate the proposed controller's robust, accurate tracking with reduced control effort under unknown disturbances compared to other NT -STSM and conventional controllers. The results demonstrated that the proposed NT -STSM controller mitigates chattering and instability in complex motions, making it a viable solution for dexterous robotic manipulations and various industrial applications. HE development of robust control algorithms is necessary for industrial robotic manipulators in applications such as remote surgery, cooperative multi-robot manipulation, and handling varying payloads. These applications require precise trajectory tracking, robustness to disturbances, and energy-efficient control strategies. High degree-of-freedom (DOF) manipulators offer an extensive range of motion, however, their complex nonlinear dynamics, with model uncertainties and external disturbances, pose significant control challenges.


Robust and Agile Quadrotor Flight via Adaptive Unwinding-Free Quaternion Sliding Mode Control

Yazdanshenas, Amin, Faieghi, Reza

arXiv.org Artificial Intelligence

--This paper presents a new adaptive sliding mode control (SMC) framework for quadrotors that achieves robust and agile flight under tight computational constraints. The proposed controller addresses key limitations of prior SMC formulations, including (i) the slow convergence and almost-global stability of SO(3)-based methods, (ii) the oversimplification of rotational dynamics in Euler-based controllers, (iii) the unwinding phenomenon in quaternion-based formulations, and (iv) the gain overgrowth problem in adaptive SMC schemes. Our controller is computationally efficient and runs reliably on a resource-constrained nano quadrotor, achieving 250 Hz and 500 Hz refresh rates for position and attitude control, respectively. In an extensive set of hardware experiments with over 130 flight trials, the proposed controller consistently outperforms three benchmark methods, demonstrating superior trajectory tracking accuracy and robustness with relatively low control effort. The controller enables aggressive maneuvers such as dynamic throw launches, flip maneuvers, and accelerations exceeding 3g, which is remarkable for a 32-gram nano quadrotor . The experimental codes and videos related to this paper are accessible at the following links: Code: https://github.com/A A. Motivation Quadrotors require robust control to maintain stability and precise maneuverability under disturbances and uncertainties. One widely studied method in this context is sliding mode control (SMC). One key challenge involves attitude control. As discussed in Section II, coordinate-free methods exhibit slow convergence and provide only almost global stability. The authors are with the Autonomous V ehicles Laboratory, Department of Aerospace Engineering, Toronto Metropolitan University, Toronto, Canada{amin.yazdanshenas,reza.faieghi Quaternion-based methods also face the unwinding issue, which can cause unnecessarily prolonged rotations. A second challenge is the need to know the upper bounds of uncertainties. Adaptive switching gains eliminate the need for prior knowledge of these bounds.


Robust adaptive fuzzy sliding mode control for trajectory tracking for of cylindrical manipulator

Pham, Van Cuong, Tran, Minh Hai, Nguyen, Phuc Anh, Vu, Ngoc Son, Thi, Nga Nguyen

arXiv.org Artificial Intelligence

Abstract: This research proposes a robust adaptive fuzzy sliding mode control (AFSMC) approach to enhance the trajectory tracking performance of cylindrical robotic manipulators, extensively utilized in applications such as CNC and 3D printing. The proposed approach integrates fuzzy logic with sliding mode control (SMC) to bolster adaptability and robustness, with fuzzy logic approximating the uncertain dynamics of the system, while SMC ensures strong performance. Simulation results in MATLAB/Simulink demonstrate that AFSMC significantly improves trajectory tracking accuracy, stability, and disturbance rejection compared to traditional methods. This research underscores the effectiveness of AFSMC in controlling robotic manipulators, contributing to enhanced precision in industrial robotic applications. Keywords: Adaptive Fuzzy Sliding Mode Control (AFSMC), Sliding Mode Control (SMC), Fuzzy Logic, Robotic Manipulators, Cylindrical Manipulator 1. INTRODUCTION Cylindrical robotic manipulators, combining a prismatic and a revolute joint, are extensively utilized in applications such as CNC machining, 3D printing, and assembly tasks.


Performance Evaluation of Trajectory Tracking Controllers for a Quadruped Robot Leg

Shojaei, Hossein, Rahmanei, Hamid, Sadati, Seyed Hossein

arXiv.org Artificial Intelligence

The complexities in the dynamic model of the legged robots make it necessary to utilize model-free controllers in the task of trajectory tracking. In This paper, an adaptive transpose Jacobian approach is proposed to deal with the dynamic model complexity, which utilizes an adaptive PI-algorithm to adjust the control gains. The performance of the proposed control algorithm is compared with the conventional transpose Jacobian and sliding mode control algorithms and evaluated by the root mean square of the errors and control input energy criteria. In order to appraise the effectiveness of the proposed control system, simulations are carried out in MATLAB/Simulink software for a quadruped robot leg for semi-elliptical path tracking. The obtained results show that the proposed adaptive transpose Jacobian reduces the overshoot and root mean square of the errors and at the same time, decreases the control input energy. Moreover, transpose Jacobin and adaptive transpose Jacobian are more robust to changes in initial conditions compared to the conventional sliding mode control. Furthermore, sliding mode control performs well up to 20% uncertainties in the parameters due to its model-based nature, whereas the transpose Jacobin and the proposed adaptive transpose Jacobian algorithms show promising results even in higher mass uncertainties.


Fast Finite-Time Sliding Mode Control for Chattering-Free Trajectory Tracking of Robotic Manipulators

Ranjbar, Momammad Ali

arXiv.org Artificial Intelligence

Achieving precise and efficient trajectory tracking in robotic arms remains a key challenge due to system uncertainties and chattering effects in conventional sliding mode control (SMC). This paper presents a chattering-free fast terminal sliding mode control (FTSMC) strategy for a three-degree-of-freedom (3-DOF) robotic arm, designed to enhance tracking accuracy and robustness while ensuring finite-time convergence. The control framework is developed using Newton-Euler dynamics, followed by a state-space representation that captures the system's angular position and velocity. By incorporating an improved sliding surface and a Lyapunov-based stability analysis, the proposed FTSMC effectively mitigates chattering while preserving the advantages of SMC, such as fast response and strong disturbance rejection. The controller's performance is rigorously evaluated through comparisons with conventional PD sliding mode control (PDSMC) and terminal sliding mode control (TSMC). Simulation results demonstrate that the proposed approach achieves superior trajectory tracking performance, faster convergence, and enhanced stability compared to existing methods, making it a promising solution for high-precision robotic applications.


Adaptive Twisting Sliding Control for Integrated Attack UAV's Autopilot and Guidance

Nguyen, Minh Tu, Hoang, Van Truong, Phung, Manh Duong, Doan, Van Hoa

arXiv.org Artificial Intelligence

This paper investigates an adaptive sliding-mode control for an integrated UAV autopilot and guidance system. First, a two-dimensional mathematical model of the system is derived by considering the incorporated lateral dynamics and relative kinematics of the UAV and its potential target of attack. Then, a sliding surface is derived utilizing the zero-effort miss distance. An adaptive twisting sliding mode (ATSMC) algorithm is applied to the integrated system. Simulation and comparisons have been accomplished. The results show our proposed design performs well in interception precision, even with high nonlinearity, uncertainties, disturbances, and abrupt changes in the target's movement, thanks to the adaptation strategy.


Backstepping Control of Tendon-Driven Continuum Robots in Large Deflections Using the Cosserat Rod Model

Danesh, Rana, Janabi-Sharifi, Farrokh

arXiv.org Artificial Intelligence

This paper presents a study on the backstepping control of tendon-driven continuum robots for large deflections using the Cosserat rod model. Continuum robots are known for their flexibility and adaptability, making them suitable for various applications. However, modeling and controlling them pose challenges due to their nonlinear dynamics. To model their dynamics, the Cosserat rod method is employed to account for significant deflections, and a numerical solution method is developed to solve the resulting partial differential equations. Previous studies on controlling tendon-driven continuum robots using Cosserat rod theory focused on sliding mode control and were not tested for large deflections, lacking experimental validation. In this paper, backstepping control is proposed as an alternative to sliding mode control for achieving a significant bending. The numerical results are validated through experiments in this study, demonstrating that the proposed backstepping control approach is a promising solution for achieving large deflections with smoother trajectories, reduced settling time, and lower overshoot. Furthermore, two scenarios involving external forces and disturbances were introduced to further highlight the robustness of the backstepping control approach.

  Country:
  Genre: Research Report > New Finding (1.00)
  Industry: Health & Medicine (0.46)

Adaptive Integral Sliding Mode Control for Attitude Tracking of Underwater Robots With Large Range Pitch Variations in Confined Space

Wang, Xiaorui, Sha, Zeyu, Zhang, Feitian

arXiv.org Artificial Intelligence

Underwater robots play a crucial role in exploring aquatic environments. The ability to flexibly adjust their attitudes is essential for underwater robots to effectively accomplish tasks in confined space. However, the highly coupled six degrees of freedom dynamics resulting from attitude changes and the complex turbulence within limited spatial areas present significant challenges. To address the problem of attitude control of underwater robots, this letter investigates large-range pitch angle tracking during station holding as well as simultaneous roll and yaw angle control to enable versatile attitude adjustments. Based on dynamic modeling, this letter proposes an adaptive integral sliding mode controller (AISMC) that integrates an integral module into traditional sliding mode control (SMC) and adaptively adjusts the switching gain for improved tracking accuracy, reduced chattering, and enhanced robustness. The stability of the closed-loop control system is established through Lyapunov analysis. Extensive experiments and comparison studies are conducted using a commercial remotely operated vehicle (ROV), the results of which demonstrate that AISMC achieves satisfactory performance in attitude tracking control in confined space with unknown disturbances, significantly outperforming both PID and SMC.


Radial Basis Function Neural Networks for Formation Control of Unmanned Aerial Vehicles

Bui, Duy-Nam, Phung, Manh Duong

arXiv.org Artificial Intelligence

This paper addresses the problem of controlling multiple unmanned aerial vehicles (UAVs) cooperating in a formation to carry out a complex task such as surface inspection. We first use the virtual leader-follower model to determine the topology and trajectory of the formation. A double-loop control system combining backstepping and sliding mode control techniques is then designed for the UAVs to track the trajectory. A radial basis function neural network (RBFNN) capable of estimating external disturbances is developed to enhance the robustness of the controller. The stability of the controller is proven by using the Lyapunov theorem. A number of comparisons and software-in-the-loop (SIL) tests have been conducted to evaluate the performance of the proposed controller. The results show that our controller not only outperforms other state-of-the-art controllers but is also sufficient for complex tasks of UAVs such as collecting surface data for inspection. The source code of our controller can be found at https://github.com/duynamrcv/rbf_bsmc


Quaternion-Based Sliding Mode Control for Six Degrees of Freedom Flight Control of Quadrotors

Yazdanshenas, Amin, Faieghi, Reza

arXiv.org Artificial Intelligence

Despite extensive research on sliding mode control (SMC) design for quadrotors, the existing approaches suffer from certain limitations. Euler angle-based SMC formulations suffer from poor performance in high-pitch or -roll maneuvers. Quaternion-based SMC approaches have unwinding issues and complex architecture. Coordinate-free methods are slow and only almost globally stable. This paper presents a new six degrees of freedom SMC flight controller to address the above limitations. We use a cascaded architecture with a position controller in the outer loop and a quaternion-based attitude controller in the inner loop. The position controller generates the desired trajectory for the attitude controller using a coordinate-free approach. The quaternion-based attitude controller uses the natural characteristics of the quaternion hypersphere, featuring a simple structure while providing global stability and avoiding unwinding issues. We compare our controller with three other common control methods conducting challenging maneuvers like flip-over and high-speed trajectory tracking in the presence of model uncertainties and disturbances. Our controller consistently outperforms the benchmark approaches with less control effort and actuator saturation, offering highly effective and efficient flight control.

  Country: North America > Canada > Ontario > Toronto (0.04)
  Genre: Research Report (0.50)
  Industry: Transportation > Air (0.66)