Robust Hybrid Fractional Order Proportional Derivative Sliding Mode Controller for Robot Manipulator Based on Extended Grey Wolf Optimizer

Robotica ◽  
2019 ◽  
Vol 38 (4) ◽  
pp. 605-616 ◽  
Author(s):  
Hossein Komijani ◽  
Mojtaba Masoumnezhad ◽  
Morteza Mohammadi Zanjireh ◽  
Mahdi Mir
Keyword(s):  
Fractional Order ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Lyapunov Theory ◽  
Grey Wolf Optimizer ◽  
Sliding Mode Controller ◽  
Grey Wolf ◽  
Robust Controller ◽  
The Stability ◽  
Proportional Derivative Controller

SUMMARYThis paper presents a novel robust hybrid fractional order proportional derivative sliding mode controller (HFOPDSMC) for 2-degree of freedom (2-DOF) robot manipulator based on extended grey wolf optimizer (EGWO). Sliding mode controller (SMC) is remarkably robust against the uncertainties and external disturbances and shows the valuable properties of accuracy. In this paper, a new fractional order sliding surface (FOSS) is defined. Integrating the fractional order proportional derivative controller (FOPDC) and a new sliding mode controller (FOSMC), a novel robust controller based on HFOPDSMC is proposed. The bounded model uncertainties are considered in the dynamics of the robot, and then the robustness of the controller is verified. The Lyapunov theory is utilized in order to show the stability of the proposed controller. In this paper, the EGWO is developed by adding the emphasis coefficients to the typical grey wolf optimizer (GWO). The GWO and EGWO, then, are applied to optimize the proposed control parameters which result in the optimized GWO-HFOPDSMC and EGWO-HFOPDSMC, respectively. The effectivenesses of the optimized controllers (GWO-HFOPDSMC and EGWO-HFOPDSMC) are completely verified by comparing the simulation results of the optimized controllers with the typical FOSMC and HFOPDSMC.

scholarly journals Designing a Robust Controller Using SMC and Fuzzy Artificial Organic Networks for Brushed DC Motors

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3091 ◽  
Author(s):  
Pedro Ponce ◽  
J. Antonio Rosales ◽  
Arturo Molina ◽  
Hiram Ponce ◽  
Brian MacCleery
Keyword(s):  
Engineering Students ◽  
Sliding Mode ◽  
Dc Motor ◽  
Sliding Mode Controller ◽  
Robust Controller ◽  
Load Torque ◽  
Dc Drive ◽  
The Stability ◽  
Command Signal ◽  
Organic Networks

Electric direct-current (DC) drives based on DC motor are extremely important in the manufacturing process, so it must be crucial to increase their performance when they are working on load disturbances or the DC motor’s parameters change. Usually, several load torque suddenly appears when electric drives are operating in a speed closed-loop, so robust controllers are required to keep the speed high-performance. One of the most well-known robust strategies is the sliding mode controller (SMC), which works under discontinue operation. This controller can handle disturbances and variations in the plant’s parameters, so the controller has robust performance. Nevertheless, it has some disadvantages (chattering). Therefore, this paper proposed a fuzzy logic controller (FLC) that includes an artificial organic network for adjusting the command signal of the SMC. The proposed controller gives a smooth signal that decrements the chattering in the SMC. The stability condition that is based on Lyapunov of the DC motor is driven is evaluated; besides, the stability margins are calculated. The proposed controller is designed using co-simulation and a real testbed since co-simulation is an extremely useful tool in academia and industry allows to move from co-simulation to real implementation in short period of time. Moreover, there are several universities and industries that adopt co-simulation as the main step to design prototypes. Thus, engineering students and designers are able to achieve excellent results when they design rapid and functional prototypes. For instance, co-simulation based on Multisim leads to design directly printed circuit boards so engineering students or designers could swiftly get an experimental DC drive. The experimental results using this platform show excellent DC-drive performance when the load torque disturbances are suddenly applied to the system. As a result, the proposed controller based on fuzzy artificial organic and SMC allows for adjusting the command signal that improves the dynamic response in DC drives. The experimental response using the sliding-mode controller with fuzzy artificial organic networks is compared against an auto-tuning, Proportional-Integral-Derivative (PID), which is a conventional controller. The PID controller is the most implemented controller in several industries, so this proposal can contribute to improving manufacturing applications, such as micro-computer numerical control (CNC) machines. Moreover, the proposed robust controller achieves a superior-speed response under the whole tested scenarios. Finally, the presented design methodology based on co-simulation could be used by universities and industry for validating and implementing advanced control systems in DC drives.

scholarly journals Optimal New Sliding Mode Controller Combined with Modified Supertwisting Algorithm for a Perturbed Quadrotor UAV

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yassine El Houm ◽  
Ahmed Abbou ◽  
Moussa Labbadi ◽  
Mohamed Cherkaoui
Keyword(s):  
Sliding Mode ◽  
External Disturbance ◽  
Lyapunov Theory ◽  
Sliding Mode Controller ◽  
Time Varying ◽  
Sliding Surface ◽  
State Variables ◽  
Quadrotor Uav ◽  
The Stability ◽  
Quadrotor System

This paper deals with the design of a novel modified supertwisting fast nonlinear sliding mode controller (MSTFNSMC) to stabilize a quadrotor system under time-varying disturbances. The suggested control strategy is based on a modified supertwisting controller with a fast nonlinear sliding surface to improve the tracking performance. The paper suggests a simple optimization tool built-in MATLAB/Simulink to tune the proposed controller parameters. Fast convergence of state variables is established by using a nonlinear sliding surface for rotational and translational subsystems. The modified supertwisting controller is developed to suppress the effect of chattering, reject disturbances, and ensure robustness against external disturbance effect. The stability of the proposed controller (MSTFNSMC) is proved using the Lyapunov theory. The performance of the proposed MSTFNSMC approach is compared with the supertwisting sliding mode controller (STSMC) by numerical simulations to verify its effectiveness.

scholarly journals A neural network combined with sliding mode controller for the two-wheel self-balancing robot

2021 ◽  
Vol 10 (3) ◽  
pp. 592
Author(s):  
Duc-Minh Nguyen ◽  
Van-Tiem Nguyen ◽  
Trong-Thang Nguyen
Keyword(s):  
Neural Network ◽  
Control Method ◽  
Sliding Mode ◽  
Lyapunov Theory ◽  
Sliding Mode Controller ◽  
Control Laws ◽  
Noise Compensation ◽  
Simulation Results ◽  
Balancing Robot ◽  
The Stability

This article presents the sliding control method combined with the selfadjusting neural network to compensate for noise to improve the control system's quality for the two-wheel self-balancing robot. Firstly, the dynamic equations of the two-wheel self-balancing robot built by Euler–Lagrange is the basis for offering control laws with a neural network of noise compensation. After disturbance-compensating, the sliding mode controller is applied to control quickly the two-wheel self-balancing robot reached the desired position. The stability of the proposed system is proved based on the Lyapunov theory. Finally, the simulation results will confirm the effectiveness and correctness of the control method suggested by the authors.

scholarly journals CentrifugationSynchronization Control of Fractional Order Chaotic Systems Based on Memristor and Its Hardware Implementation

2021 ◽  
pp. 289-297
Author(s):  
Zhaohan zhang, Huiling Jin
Keyword(s):  
Fractional Order ◽  
Hardware Implementation ◽  
Chaotic Systems ◽  
Control Method ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Controlled System ◽  
Integer Order ◽  
The Stability ◽  
Dynamic Phenomena

This paper studies the synchronization control of fractional order chaotic systems based on memristor and its hardware implementation. This paper takes the complex dynamic phenomena of memristor turbidity system as the research background. Starting with the integer order memristor system, the fractional order form is derived based on the integer order turbid system, and its dynamics is deeply studied. At the same time, the turbidity phenomenon is applied to the watermark encryption algorithm, which effectively improves the confidentiality of the algorithm. Finally, in order to suppress the occurrence of turbidity, a fractional order sliding mode controller is proposed. In this paper, the sliding mode controller under the function switching control method is established, and the conditions for the parameters of the sliding mode controller are derived. Finally, the experimental results analyze the stability of the controlled system under different parameters, and give the corresponding time-domain waveform to verify the correctness of the theoretical analysis.

Chaos Synchronization of Optical Systems via a Fractional-Order Sliding Mode Controller

2018 ◽  
pp. 218-260 ◽  
Author(s):  
Abdesselem Boulkroune ◽  
Amina Boubellouta
Keyword(s):  
Fractional Order ◽  
Chaos Synchronization ◽  
Sliding Mode ◽  
Optical Systems ◽  
Sliding Mode Controller ◽  
Asymptotically Stable ◽  
Robust Controller ◽  
External Disturbances ◽  
Chattering Effect ◽  
Synchronization Scheme

In this chapter, one investigates the chaos synchronization of a class of uncertain optical chaotic systems. More precisely, one also presents a systematic approach for designing a fractional-order (FO) sliding mode controller to achieve a rapid, robust, and perfect chaos synchronization. By this robust controller, it is rigorously proven that the associated synchronization error is Mittag-Leffler (or asymptotically) stable. In a numerical simulation framework, this synchronization scheme is tested on many chaotic optical systems taken from the open literature. The obtained results clearly show that the proposed chaos synchronization controller is not only strongly robust with respect to the unavoidable system's uncertainties (as unmodeled dynamics, and parameters' variation and uncertainty) and eventual dynamical external disturbances, but also can significantly reduce the chattering effect.

Sliding mode based fractional-order iterative learning control for a nonlinear robot manipulator with bounded disturbance

2016 ◽  
Vol 40 (1) ◽  
pp. 49-60 ◽  
Author(s):  
Iman Ghasemi ◽  
Abolfazl Ranjbar Noei ◽  
Jalil Sadati
Keyword(s):  
Fractional Order ◽  
Iterative Learning Control ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Learning Control ◽  
Iterative Learning ◽  
Control Law ◽  
Sliding Mode Controller ◽  
Text Type ◽  
Single Link

In this paper a new type of sliding mode based fractional-order iterative learning control (ILC) is proposed for nonlinear systems in the presence of uncertainties. For the first time, a sliding mode controller is combined with fractional-order ILC. This sliding mode based [Formula: see text] and [Formula: see text]-type ILC is applied on a nonlinear robot manipulator. Convergence of the proposed method is investigated when the stability is also proved. In this method, the control signal at any iteration is generated in two parts. The first section comes from the sliding mode controller while the second part is output of the fractional-order ILC. The latter signal is assessed using its previous amount and the sliding mode error signal. The achieved control law is capable of controlling nonlinear iterative processes, perturbed by bounded disturbances with high accuracy. The same frequent disturbance is eliminated by the iterative learning part, while the effect of nonrepetitive uncertainty is improved by the sliding mode part. The sliding mode based [Formula: see text]-type ILC (as an adaptive control law) is proposed to control a single-link arm robot. The controller is then improved to sliding mode based [Formula: see text]-type ILC. The effectiveness of the proposed method is again investigated on a single-link robot manipulator through a simulation approach. It is shown that the controller for [Formula: see text] provides performance by means of faster response together with more accuracy with respect to a conventional ILC.

Trajectory-Tracking-Based Adaptive Neural Network Sliding Mode Controller for Robot Manipulators

2020 ◽  
Vol 20 (3) ◽  
Author(s):  
Bin Ren ◽  
Yao Wang ◽  
Jiayu Chen
Keyword(s):  
Neural Network ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Lyapunov Theory ◽  
Robot Dynamics ◽  
Sliding Mode Controller ◽  
Adaptive Neural Network ◽  
Proposed Model ◽  
The Impact

Abstract Unpredictable disturbances and chattering are the major challenges of the robot manipulator control. In recent years, trajectory-tracking-based controllers have been recognized by many researchers as the most promising method to understand robot dynamics with uncertainties and improve robot control. However, reliable trajectory-tracking-based controllers require high model precision and complexity. To develop an agile and straightforward method to mitigate the impact caused by uncertain disturbance and chattering, this study proposed an adaptive neural network sliding mode controller based on the super-twisting algorithm. The proposed model not only can minimize the tracking error but also improve the system robustness with a simpler structure. Moreover, the proposed controller has the following two distinctive features: (1) the weights of the radial basis function (RBF network) are designed to be adjusted in real-time and (2) the prior knowledge of the actual robot system is not required. The analytical model of the proposed controller was proved to be stable and ensured by the Lyapunov theory. To validate the proposed model, this study also conducted a comparative simulation on a two-link robot manipulator system with the conventional sliding mode controller and the model-based controller. The results suggest the proposed model improved the control accuracy and had fewer chattering.

Tracking Control of Robot Manipulator Using Sliding Mode Controller With Performance Robustness

1999 ◽  
Vol 121 (1) ◽  
pp. 64-70 ◽  
Author(s):  
Chieh-Li Chen ◽  
Rui-Lin Xu
Keyword(s):  
Tracking Control ◽  
Feedback Linearization ◽  
Controller Design ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Design Procedure ◽  
Sliding Mode Controller ◽  
Systematic Design ◽  
And Performance ◽  
The Stability

The tracking control problem of robot manipulator is considered in this paper. A sliding mode controller design with global invariance is proposed using the concept of extended system and feedback linearization. The sliding surface is assigned such that the sliding mode motion will occur while the proposed control law is applied. This results in a system with global invariance. The stability and performance of the resulting system can be guaranteed by the proposed systematic design procedure.

scholarly journals Adaptive High Order Sliding Mode Controller Design for Hypersonic Vehicle with Flexible Body Dynamics

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Bailing Tian ◽  
Wenru Fan ◽  
Qun Zong ◽  
Jie Wang ◽  
Fang Wang
Keyword(s):  
Controller Design ◽  
Sliding Mode ◽  
Adaptive Controller ◽  
Hypersonic Vehicle ◽  
High Order ◽  
Lyapunov Theory ◽  
Sliding Mode Controller ◽  
Flexible Body Dynamics ◽  
Robust Adaptive ◽  
The Stability

This paper describes the design of a nonlinear robust adaptive controller for a flexible hypersonic vehicle model which is nonlinear, multivariable, and unstable, and includes uncertain parameters. Firstly, a control-oriented model is derived for controller design. Then, the model analysis is conducted for this model via input-output (I/O) linearized technique. Secondly, the sliding mode manifold is designed based on the homogeneity theory. Then, the adaptive high order sliding mode controller is designed to achieve the tracking for hypersonic vehicle where the upper bounds of the uncertainties are not known in advance. Furthermore, the stability of the system is proved via the Lyapunov theory. Finally, the Monte-Carlo simulation results on the full-order nonlinear model with aerodynamic uncertainties are provided to demonstrate the effectiveness of the proposed control strategy.

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