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

Norsahperi, Nor Mohd Haziq; Danapalasingam, Kumeresan A.

doi:10.32985/ijeces.10.2.3

Cited by 4 publications

(3 citation statements)

References 39 publications

(72 reference statements)

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“…Numerical simulations were conducted on a two-link robot manipulator by Norsahperi & Danapalasingam (2019) to examine the efficiency of various control approaches. They utilized trajectory tracking and energy consumption as performance measures.…”

Section: Introductionmentioning

confidence: 99%

Terminal and Backstepping Sliding Mode Control with Genetic Algorithms for Robot Manipulators

TİLKİ,

ÖLGÜN

2023

SIC

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This paper presents two controllers that address the negative effects of external disturbances, parameter variations, and random noise on trajectory tracking for robot manipulators. These controllers were designed for handling variable-mass loads, uncertainties, and disturbances in the robot's dynamic equations. In order to achieve an accurate trajectory tracking and an improved disturbance rejection, Terminal Sliding Mode Control (TSMC) was employed in combination with a Neural Network (NN) with radial basis functions that modelled the unidentified system characteristics. The employed control algorithms, namely the Neural Network-Based Terminal Sliding Mode Control (NNBTSMC) and the Neural Network-Based Backstepping Terminal Sliding Mode Control (NNBBTSMC), were optimized using genetic algorithms in order to determine the optimal controller coefficients. Simulation tests were conducted on a two-link robot manipulator, and the effectiveness of the proposed controllers was demonstrated. Additionally, a comparison was made between the analysed controllers regarding their trajectory tracking performance and control inputs for the case when the manipulator payload changed over time. The simulation results showed that the NNBBTSMCWGA outperformed the traditional SMC and NNTSMC by exhibiting a higher robustness, and reduced chattering effects on the control inputs.

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Section: Introductionmentioning

confidence: 99%

Terminal and Backstepping Sliding Mode Control with Genetic Algorithms for Robot Manipulators

TİLKİ,

ÖLGÜN

2023

SIC

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“…In contrast, integrator backstepping control, supported by sliding manifolds and LQR's methods, consider flexibility as a L 2 disturbance, highlighting that LQR offers better rejection to disturbances, low oscillations, and avoids the chattering phenomenon [8], [33], [42], [43], [43]- [49]. Nevertheless, LQR Journal of Robotics and Control (JRC) ISSN: 2715-5072 744 needs to offer a suitable rise time and setting time for two timescales, specifically for velocity changing, where relevant flexibility situations cause motion inaccuracy.…”

Section: Introductionmentioning

confidence: 99%

Control of Flexible Manipulator Robots Based on Dynamic Confined Space of Velocities: Dynamic Programming Approach

Peña Fernández

2022

Journal of Robotics and Control

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Linear Parameter Varying models-based Model Predictive Control (LPV-MPC) has stood out in manipulator robots because it presents well-rejection to dynamic uncertainties in flexible joints. However, it has become too weak when the MPC's optimization problem does not include kinematic constraints-based conditions. This paper uses dynamic confined space of velocities (DCSV) to include these conditions as a recursive polytopic constraint, guaranteeing optimal dependency on a simplex scheduling parameter. To this end, the local frame's velocities and torque/force preload of joints (related to violation of kinematic constraints) are associated with different time scale dynamics such that DCSV correlates them as a polytope. So, a classical LPV-MPC will be updated using a dynamic programming approach according to the DCSV-based polytope. As a result, one lemma about DCSV-based recursive polytope and a five-step procedure for two decoupled close-loop schemes with different time scales compose the LPV-MPC proposed method. Numerical validation shows that even for relevant flexibility situations, trajectory tracking performance is improved by tuning finite horizons and optimization problem constraints regarding DCSV's behavior.

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“…Control of wheeled autonomous vehicles (WAV) has been a challenge in last years, mainly when the tracking trajectory is not suitable according to specifications of the workspace, taking into account that such specifications can be modeled by using the configuration space (due to different kinds of wheels and inherent contact constraints) or by considering nonlinear forces, either due to static friction nature on the wheels or by just torsional or flexible behavior on mechanical-coupling, all WAVs are always a new opportunity to research more alternatives to control them [1,2,3,4,5,6,7]. Usually, when WAVs do not satisfy kinematics constraints are treated as systems with a high nonholonomy degree, becoming more complex to synthesize any nonlinear control law that operates on the actuator's space and guarantees good convergence of the wheel speed as well as of the error for trajectory tracking.…”

Section: Introductionmentioning

confidence: 99%

Oriented manifold-based error tracking control for nonholonomic wheeled autonomous vehicles on Lie group for curvilinear approach

Fernández¹

2021

Lat. Americ. J. of Develop.

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This paper considers the trajectory tracking control of wheeled autonomous vehicles (WAV) with slipping in the wheels, i.e., when the kinematic constraints are not satisfied. Usually, the coordinates system used to represent all control problems suggest invariant subspaces mutually orthogonal, but this approach can not be enough to treat curvatures significative large at different navigation speed. In order to get a slight im- provement on this topic, there are previous works showing that the kinematic problem (commonly associated with an outer loop) can be resynthesized by using other invariant subspaces, i.e., another representation of the configuration space. For this reason, the proposal reported here uses an oriented-manifold parametrized by a coordinate system on a curve viewpoint of the trajectory to describe the kinematic problem, however, the dynamic control law remains faithful to the singular perturbation approach with invariant subspaces mutually orthogonal, thus, it is possible to include the flexibility through a small factor in the dynamic model (well-known as ε), responsible to avoid the good-performance of the kinematic constraints. Only a common curvature-transformation between orthogonal and curve coordinates will be used to couple both approaches. Finally, it will be observed that when the controller is applied to the control scheme the behavior of the tracking is meaningfully improved.

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

Cited by 4 publications

References 39 publications

Terminal and Backstepping Sliding Mode Control with Genetic Algorithms for Robot Manipulators

Terminal and Backstepping Sliding Mode Control with Genetic Algorithms for Robot Manipulators

Control of Flexible Manipulator Robots Based on Dynamic Confined Space of Velocities: Dynamic Programming Approach

Oriented manifold-based error tracking control for nonholonomic wheeled autonomous vehicles on Lie group for curvilinear approach

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