scholarly journals Leader-Follower Multimotor Speed Coordination via Adaptive Fuzzy Multiagent Consensus Scheme

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Suhaib Masroor ◽  
Chen Peng ◽  
Eman H. Alkhammash
Keyword(s):  
Fuzzy Logic Controller ◽  
Cross Coupling ◽  
Adaptive Controller ◽  
Consensus Algorithm ◽  
Pole Placement ◽  
Hybrid Controller ◽  
Simulation Purpose ◽  
Pole Placement Controller ◽  
Model Reference Adaptive ◽  
Belt System

Coordinated speed of interconnected motors has vast application in the industry. Typically, the smooth operation of the system relies on the coordinated speed of the multiple motors such as the conveyer belt system. Thus, the problem to have coordinated speed in a network-connected motor is mostly dealt with wire-connected architectures such as cross coupling. The presented study suggests a unique design to deal with the said problem by proposing a network model consisting of a DC chopper drive, termed as an ith agent of a network, while a leader-follower multiagent consensus algorithm is used, in a supervisory role, to ensure coordinated speed. Moreover, a hybrid controller (Fuzzy MRAC-RST), composed of Fuzzy logic controller, pole placement controller (F-RST), along with model reference adaptive controller (MRAC), is used to control the ith agent. The proposed hybrid controller along with MAS consensus algorithm forms an adaptive tracking performance and ensure coordinated speed. The MATLAB platform is used for simulation purpose, and the obtained results validate the design concept.

Synthesis Design and Analysis of a Hybrid Controller for Robotic Arms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Adaptive Controller ◽  
Convergence Speed ◽  
Model Reference ◽  
Robotic Arms ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

In this paper, a hybrid controller for robotic arms is proposed and designed by combining a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the model reference adaptive controller and the PID+MRAC hybrid controller for 1-DOF and 2-DOF manipulators are compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+MRAC controllers are better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

scholarly journals Experimental simplified rule of self tuning fuzzy logic-model reference adaptive speed controller for induction motor drive

2020 ◽  
Vol 20 (3) ◽  
pp. 1653
Author(s):  
M.Z. Ismail ◽  
M.H.N. Talib ◽  
Z. Ibrahim ◽  
J. Mat Lazi ◽  
Z. Rasin
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Tuning Parameter ◽  
Model Reference ◽  
Wide Range ◽  
Speed Performance ◽  
Self Tuning ◽  
Model Reference Adaptive

<span>Fuzzy logic controller (FLC) has shown excellent performance in dealing with the non-linearity and complex dynamic model of the induction motor. However, a conventional constant parameter FLC (CPFL) will not be able to provide–good coverage performance for a wide speed range operation with a single tuning parameter. Therefore, this paper proposed a self tuning mechanism FLC approach by model reference adaptive controller (ST-MRAC) to continuously allow to adjust the parameters. Due to real time hardware application, the dominant rules selection method for simplified rules has been implemented as part of the reducing computational burden. Experiment results validate a good performance of the ST-MRAC compared to the CPFL for the   speed performance in terms of the wide range of operations and disturbance showed remarkable performance.</span>

scholarly journals Improved Transient Performance of a Fuzzy Modified Model Reference Adaptive Controller for an Interacting Coupled Tank System Using Real-Coded Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Asan Mohideen Khansadurai ◽  
Valarmathi Krishnasamy ◽  
Radhakrishnan Thota Karunakaran
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Transient Performance ◽  
Model Reference ◽  
Modified Model ◽  
Real Coded Genetic Algorithm ◽  
Tank System ◽  
Model Reference Adaptive ◽  
The Membership Function

The main objective of the paper is to design a model reference adaptive controller (MRAC) with improved transient performance. A modification to the standard direct MRAC called fuzzy modified MRAC (FMRAC) is used in the paper. The FMRAC uses a proportional control based Mamdani-type fuzzy logic controller (MFLC) to improve the transient performance of a direct MRAC. The paper proposes the application of real-coded genetic algorithm (RGA) to tune the membership function parameters of the proposed FMRAC offline so that the transient performance of the FMRAC is improved further. In this study, a GA based modified MRAC (GAMMRAC), an FMRAC, and a GA based FMRAC (GAFMRAC) are designed for a coupled tank setup in a hybrid tank process and their transient performances are compared. The results show that the proposed GAFMRAC gives a better transient performance than the GAMMRAC or the FMRAC. It is concluded that the proposed controller can be used to obtain very good transient performance for the control of nonlinear processes.

scholarly journals PASSIVITY BASED FRACTIONAL ORDER ADAPTIVE CONTROL OF DEPTH OF ANESTHESIA

2019 ◽  
Vol 49 (3) ◽  
pp. 155-161
Author(s):  
M. BOROOJERDI ALAVI ◽  
M. TABATABAEI
Keyword(s):  
Fractional Order ◽  
Adaptive Controller ◽  
Pole Placement ◽  
Model Parameters ◽  
Depth Of Anesthesia ◽  
Model Uncertainties ◽  
Adaptation Mechanism ◽  
Polynomial Coefficients ◽  
Simulation Results ◽  
Model Reference Adaptive

In this paper, a passivity based model reference adaptive controller with fractional-order adaptation mechanism is utilized for control of depth of anesthesia. The propofol infusion rate is adjusted to reach an appropriate Bispectral Index (BIS). The Pharmacokinetic-Pharmacodynamic (PK-PD) model is employed to model the distribution of propofol in patient body. Since, the PK-PD model parameters depend on physical specifications of patient, employing an adaptive controller to control this system is inevi-table. The utilized controller is a pole placement con-troller in which its polynomial coefficients are ad-justed according to a fractional-order adaptation mechanism. Simulation results on several patients demonstrate the efficiency of the proposed method in the presence of disturbance, noise, and model uncertainties.

Design of a Control System for Serial Mechanisms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Control System ◽  
Dynamic Equation ◽  
Degrees Of Freedom ◽  
Nonlinear Term ◽  
Hybrid Control ◽  
Adaptive Controller ◽  
Hybrid Controller ◽  
Speed Performance ◽  
Convergence Performance ◽  
Model Reference Adaptive

A hybrid control system for multi degrees of freedom robotic manipulator is designed by integrating a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. For the 1-DOF link, because the inertia matrices and nonlinear term of the dynamic equation are constant, we can directly combine the PID and MRAC controller to design the PID+MRAC controller. However, for the more than 1-DOF link case, it is no longer applicable because the inertia matrices and nonlinear term of the dynamic equation are not constant. By using an improved adaptive algorithm and structure, and by combining the PID and improved MRAC controllers, a controller is designed for the more than 1-DOF link case. The convergence performance of the PID controller, MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators are compared.

scholarly journals Attitude and Altitude Control of Trirotor UAV by Using Adaptive Hybrid Controller

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Zain Anwar Ali ◽  
Daobo Wang ◽  
Suhaib Masroor ◽  
M. Shafiq Loya
Keyword(s):  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Kinematic Model ◽  
Nonlinear Behavior ◽  
Pole Placement ◽  
Hybrid Scheme ◽  
Hybrid Controller ◽  
Aerial Vehicle ◽  
6 Degrees Of Freedom

The paper presents an adaptive hybrid scheme which is based on fuzzy regulation, pole-placement, and tracking (RST) control algorithm for controlling the attitude and altitude of trirotor UAV. The dynamic and kinematic model of Unmanned Aerial Vehicle (UAV) is unstable and nonlinear in nature with 6 degrees of freedom (DOF); that is why the stabilization of aerial vehicle is a difficult task. To stabilize the nonlinear behavior of our UAV, an adaptive hybrid controller algorithm is used, in which RST controller tuning is performed by adaptive gains of fuzzy logic controller. Simulated results show that fuzzy based RST controller gives better robustness as compared to the classical RST controller.

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