Review of sliding mode based control techniques for control system applications

Gambhire, S. J.; Kishore, D. Ravi; Londhe, P. S.; Pawar, Sushant N.

doi:10.1007/s40435-020-00638-7

Cited by 139 publications

(57 citation statements)

References 161 publications

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“…The evolution of these control techniques leads to robust systems that are being explored in mechanical devices. These algorithms find application when there is the influence of parametric uncertainties due to modelling errors, non-linearity, and external disturbances [ 77 ], conditions that may occur in robotic exoskeletons for rehabilitation [ 50 , 78 ].…”

Section: Resultsmentioning

confidence: 99%

Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

Vélez-Guerrero

Callejas-Cuervo

Mazzoleni

2021

Sensors

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Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.

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Section: Resultsmentioning

confidence: 99%

Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

Vélez-Guerrero

Callejas-Cuervo

Mazzoleni

2021

Sensors

View full text Add to dashboard Cite

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“…As future work, the use of better control algorithms (such as those presented in [24][25][26]) is proposed to decrease the positioning error. The use of other throttling functions can be explored, aimed at avoiding current surges in the power converters but improving the speed response of the servo-driven joint.…”

Section: Discussionmentioning

confidence: 99%

“…In terms of electronic devices and strategies for controlling servo-driven systems, there are several remarkable approaches. The work developed in [24] is particularly significant since it reviews several advanced control strategies for servo devices, mainly using sliding methods. These advanced control methods enable better trajectory tracking as well as active disturbance rejection, which can improve actuator performance in applications that require higher precision in motion execution.…”

Section: Electronic Systems and Control Techniquesmentioning

confidence: 99%

Integration and Testing of a High-Torque Servo-Driven Joint and Its Electronic Controller with Application in a Prototype Upper Limb Exoskeleton

Vélez-Guerrero

Callejas-Cuervo

Mazzoleni

2021

Sensors

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Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented in various electronic devices to improve the performance and usability of these devices, which is desirable in any application. This paper proposes the integration and testing of a high-torque, servo-driven joint and its electronic controller, exposing its use in a robotic exoskeleton prototype as a case study. Following a brief background review, the development and implementation of the proposal are presented, allowing the control of the servo-driven joint in terms of torque, rotational velocity, and position through a straightforward, closed-loop control architecture. Additionally, the stability and performance of the servo-driven joint were assessed with and without load. In conclusion and based on the obtained results, the servo-driven joint and its control system demonstrate consistent performance under the proposed test protocol (max values: angular velocity 97 °/s, torque 33 Nm, positioning RMSE 1.46°), enabling this approach for use in various applications related to robotic exoskeletons, including human performance enhancement, rehabilitation, or support for daily living activities.

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“…The robotic manipulator is an electrically actuated Three Degrees of Freedom (3-DOF) arm-like serial manipulator comprising several segments which may be sliding or jointed. They are used in industrial applications with articulated geometric types because articulated robotic manipulators are most commonly used in factories worldwide (Gambhire et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Modeling and control of a 3-DOF articulated robotic manipulator using self-tuning fuzzy sliding mode controller

2021

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Robotic manipulators are highly coupled multi-input multi-output (MIMO) nonlinear systems with uncertainties and highly time-varying dynamic capabilities. These characteristics make the trajectory control of a robotic manipulator very challenging. This paper presents the modeling and trajectory tracking control of a 3-DOF robotic manipulator using self-tuning fuzzy sliding mode controller (ST-FSMC). The stability of the system was investigated using the Lyapunov direct method. The controller was implemented using MATLAB/Simulink and its performance was evaluated. The simulation results show that the proposed controller removed chattering phenomena from the control effort and reduced the tracking error (average steady-state error) to 0.0036 rad. However, in the case of the conventional controllers, the average steady-state error increased to 0.0413 rad, 0.0044 rad, and 0.0053 rad for the Proportional-integral-derivative (PID) controller, Sliding mode controller (SMC), and Fuzzy sliding mode controller (FSMC), respectively. The conventional controllers (PID, SMC, and FSMC) were designed for the Aderajew Ashagrie

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Review of sliding mode based control techniques for control system applications

Cited by 139 publications

References 161 publications

Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

Integration and Testing of a High-Torque Servo-Driven Joint and Its Electronic Controller with Application in a Prototype Upper Limb Exoskeleton

Modeling and control of a 3-DOF articulated robotic manipulator using self-tuning fuzzy sliding mode controller

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