Multi-input Multi-output Fuzzy Logic Controller for Complex System: Application on Two-links Manipulator

Baghli, Fatima Zahra; Bakkali, Larbi El; Lakhal, Yassine

doi:10.1016/j.protcy.2015.02.086

Cited by 10 publications

(6 citation statements)

References 2 publications

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“…The study goes further to monitor the actual fuel flow, fuel level, consumption, and efficiency related to the work done by the specific machinery from a remote location. The Fuel Level Sensor (FLS) (1) is the energy supplied from a battery (12-24 V) and placed in the fuel tank (2). It is supported by a volumetric method of determining the fuel level.…”

Section: Methodsmentioning

confidence: 99%

“…Applied measurement and instrumentations for optimizing scanning devices [1] and digital controllers for highly complex systems (with fuzzy controllers) [2] are based on electronic equipment and use software programs [3]. The development of software automated systems for fuel level control supports the investigation of fuel economy and emissions [4] and the design for supply-to-engine [5].…”

Section: Introductionmentioning

confidence: 99%

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Development of an Automated System for Fuel Tank Level Checking and Machinery Location Management to Optimize Remote Accessibility and Mobile Tracking

Popescu¹,

Borzan

Baldean

2020

The 14th International Conference on Interdisciplinarity in Engineering—INTER-Eng 2020

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The present article shows the most significant steps to be taken in the process of the development of an automated system for fuel tank level monitoring and machinery location checking to optimize accessibility and mobile tracking. Fuel or energy consumption is converted with money spending and machinery in operation during different tasks. The maintenance and service costs add up to the final price of the product making it less attractive if the customer must pay more for each acquired unit of produce. Thus, optimization is required in the production system to lower the costs of energy and operation of working machinery. The main objective of the present paper is the research, development, and testing the process of an automated system designed with the purpose of controlling fuel tank level and machinery location management to improve accessibility and to optimize mobile tracking. The secondary objective consists of the installation of a volumetric sensor in the fuel tank.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of an Automated System for Fuel Tank Level Checking and Machinery Location Management to Optimize Remote Accessibility and Mobile Tracking

Popescu¹,

Borzan

Baldean

2020

The 14th International Conference on Interdisciplinarity in Engineering—INTER-Eng 2020

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“…It is relatively stable and resistant to noise and imprecision present in the data input. The principles include the arbitrary order and membership function number or form can be changed to control the programming of Fuzzy controller logic [15].…”

Section: Literature Surveymentioning

confidence: 99%

Actuator Fluid Control Using Fuzzy Feedback for Soft Robotics Activities

Karnavel¹,

Shanmugasundaram²,

Salunkhe³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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Soft robotics is a new field that uses actuators that are non-standard and compatible materials. Industrial robotics is high-throughput manufacturing devices that are quick and accurate. They are built on rigid-body mechanisms. The advancement of robotic production now depends on the inclusion of staff in manufacturing processes, allowing for the completion of activities that need cognitive abilities that are now beyond the scope of artificial networks. Hydrostatic pressure is used to achieve high deflections of structures that are based on the elastomeric in Fluid Actuators (FAs). Soft actuators based on the fluid are a popular choice safe for humans and lightweight robots. However, owing to a deficiency of durable, accurate, and affordable sensors that can be combined with actuator systems that are highly deformable and that use low-cost materials and production, closed-loop management of such actuators remains difficult. Such actuators, in combination with hydrodynamic force feedback, form a series-elastic actuation (SEA), which eliminates virtually friction from all driving-point. Fuzzy control is a smart computing analysis technique that enables complex systems to be controlled independently of a mathematical model. Fuzzy logic is used to optimize the parameters of a Fuzzy Logic Controller (FLC's) function to find the best rational controller for an automated robot. Because discontinuous endpoint friction is undetectable to the pressure of the fluid internally, feedback from traditional external force using force/tactile sensing is preferred. As a result, a fuzzy-based control using linear feedback was developed and used to test the integrated system's response dynamically and location accuracy.

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“…Fuzzy logic lends itself well to controlling intricate processes that prove troublesome to model analytically. The challenges may stem from lacking comprehensive knowledge regarding the system's mechanisms or stem from difficulties obtaining an accurate experimental identification [10]. Regardless of the root cause, fuzzy approaches can circumvent the need for precise models for processes that are too complex, nonlinear, or vague to characterize via conventional means.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Tracking and Disturbance Rejection Performance Analysis of Classical and Advanced Controllers for a SCORBOT Robot

Kern,

Urrea,

Verdejo

et al. 2024

Robotics

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This work presents the design and assessment of four control schemes for the monitoring and regulation of joint trajectories applied in the dynamic model of a SCORBOT-ER V plus robot, which includes the dynamics of the actuators, and the estimation of the friction forces present within the joints. The two classical control strategies calculated torque and PID, and the two advanced control strategies, fuzzy and predictive, are considered. In the latter case, a gravitational compensation stage is incorporated, as well as the inverse models of the motors and the transmissions of belt movement for each joint. Computational tests are performed by applying an external step-type disturbance to the third joint of the robot. Finally, an evaluation of the results obtained is presented through trajectory curves, joint errors, and the three performance indexes residual mean square, residual standard deviation, and index of agreement.

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Multi-input Multi-output Fuzzy Logic Controller for Complex System: Application on Two-links Manipulator

Cited by 10 publications

References 2 publications

Development of an Automated System for Fuel Tank Level Checking and Machinery Location Management to Optimize Remote Accessibility and Mobile Tracking

Development of an Automated System for Fuel Tank Level Checking and Machinery Location Management to Optimize Remote Accessibility and Mobile Tracking

Actuator Fluid Control Using Fuzzy Feedback for Soft Robotics Activities

Trajectory Tracking and Disturbance Rejection Performance Analysis of Classical and Advanced Controllers for a SCORBOT Robot

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