Nonlinear Control of a Flexible Joint Robotic Manipulator with Experimental Validation

Alam, Waqar; Mehmood, Adeel; Ali, Khurram; Alharbi, Soltan Abed; Iqbal, Jamshed

doi:10.5545/sv-jme.2017.4786

Cited by 18 publications

(15 citation statements)

References 11 publications

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“…Integral sliding mode control ISMC's main concept is high-frequency switching gain, which aims to force the state to achieve the integral sliding surface. The states are then guided to the desired equilibrium point by the integral action in the sliding manifold [9]. It reduces chattering and improving the control system's robustness and accuracy while maintaining nominal control efficiency.…”

Section: Modelling For Two Rigid Link-flexible Joint Manipulatormentioning

confidence: 99%

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Optimal integral sliding mode controller controller design for 2-RLFJ manipulator based on hybrid optimization algorithm

Yahya

Abbas

2022

IJECE

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A newly hybrid nature-inspired algorithm called HSSGWOA is presented with the combination of the salp swarm algorithm (SSA) and grey wolf optimizer (GWO). The major idea is to combine the salp swarm algorithm's exploitation ability with the grey wolf optimizer's exploration ability to generate both variants' strength. The proposed algorithm uses to tune the parameters of the integral sliding mode controller (ISMC) that design to improve the dynamic performance of the two-link flexible joint manipulator. The efficiency and the capability of the proposed hybrid algorithm are evaluated based on the selected test functions. It is clear that when compared to other algorithms like SSA, GWO, differential evolution (DE), gravitational search algorithm (GSA), particles swarm optimization (PSO), and whale optimization algorithm (WOA). The ISMC parameters were tuned using the SSA, which was then compared to the HSSGWOA algorithm. The simulation results show the capabilities of the proposed algorithm, which gives an enhancement percentage of 57.46% compared to the standard algorithm for one of the links, and 55.86% for the other.

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Section: Modelling For Two Rigid Link-flexible Joint Manipulatormentioning

confidence: 99%

“…An integral sliding mode controller (ISMC) tracks a flexible joint manipulator driven by a direct current (DC) motor. It is an efficient control strategy for resolving many issues with the sliding mode control (SMC) approach, including the high-frequency chattering effect and insensitivity [9].…”

Section: Introductionmentioning

confidence: 99%

Optimal integral sliding mode controller controller design for 2-RLFJ manipulator based on hybrid optimization algorithm

Yahya

Abbas

2022

IJECE

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“…The linear control fails when there is a need to tackle complex system dynamics [8], nonlinearities and parameter changes in the control laws, which require robust or adaptive control laws to handle the trajectories [9]. Many nonlinear control strategies have been developed to deal with the nonlinearities present in the system, such as robust control [10], optimal control [11], adaptive control [12], nonlinear control [13,14], and intelligent control [15]. In [9], authors present a systematic review of control strategies for multi-Degree of Freedom (DoF) robotic manipulators, using one of the most commonly used modeling formulas, Euler Lagrange.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Tracking Control of Manipulator Arms with Fuzzy Neural Networks

Fouzia

Khenfer

Boukezzoula

2020

Eng. Technol. Appl. Sci. Res.

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The learning space for executing general motions of a flexible joint manipulator is quite large and the dynamics are, in general, nonlinear, time-varying, and complex. The objective of this paper is to design a nonlinear system based on the fuzzy neural network control using supervised training, into executing reference trajectories by a flexible joint manipulator. The structure identifications of controller networks are performed by using the Adaptive Neural Fuzzy Inference System (ANFIS), with new parameters and weight coefficients automatically adapted and adjusted, in order to decrease position tracking errors. In order to adapt and reduce the number of undefined parameters in the network, a new technique is used. Reported research works use the Euler method for the resolution of the arm's dynamic function, in this paper, a more exact method was used, represented by the Fourth-Order Runge-Kutta (RK4) method. A comparative study has been carried out between these two methods in order to prove the effectiveness of the later. Finally, in order to test the robustness of the proposed approach, it was also investigated considering parameter variations. The tracking speed of the model on the system control accuracy was also analyzed. The simulation results show that the proposed approach has a good tracking effect.

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“…In recent years, many scholars have applied advanced control methods, such as adaptive, robust, sliding mode, and intelligent controls [8], to the electro-hydraulic servo control system to improve the control performance of the system, and have achieved varied results [9]. However, the work environment of the electro-hydraulic servo system of a launch vehicle is complex, that is, the load characteristics have many new characteristics, and the stability of the rocket control system requires the launch vehicle to have good dynamic characteristics [10].…”

Section: Introductionmentioning

confidence: 99%

RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator

Shi

Zhao

et al. 2020

SV-JME

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Aiming at the interference problem and the difficulty of model parameter determination caused by the nonlinearity of the valve-controlled hydraulic cylinder position servo system, this study proposes a radial basis function (RBF) neural network sliding mode control strategy based on a backstepping strategy for the electro-hydraulic actuator. First, the non-linear system model of the third-order position electro-hydraulic control servo system is established on the basis of the principle analysis. Second, the model function RBF adaptive law and backstepping control law are designed according to Lyapunov’s stability theorem to solve the problem of external load disturbance and modelling uncertainty, combined with sliding mode control strategy and virtual control law. Finally, simulation and experiment on MATLAB Simulink and semi-physical experimental platform are accomplished to show the effectiveness of the proposed method. Moreover, results show that the designed controller has high tracking accuracy to the given signal.

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Nonlinear Control of a Flexible Joint Robotic Manipulator with Experimental Validation

Cited by 18 publications

References 11 publications

Optimal integral sliding mode controller controller design for 2-RLFJ manipulator based on hybrid optimization algorithm

Optimal integral sliding mode controller controller design for 2-RLFJ manipulator based on hybrid optimization algorithm

Robust Adaptive Tracking Control of Manipulator Arms with Fuzzy Neural Networks

RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator

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