Model-Free Controller Designs for a Magnetic Micromanipulator

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Günyaz Ablay
Keyword(s):  
Current Approach ◽  
Nonlinear Controller ◽  
Optimal Model ◽  
Liquid Environment ◽  
Smooth Control ◽  
Magnetic Microparticles ◽  
Linear Controller ◽  
Model Free ◽  
Control Signals ◽  
Model Free Controller

Abstract An optimal model-free controller and a linear controller are designed and applied to a horizontal magnetic micromanipulator for controlling microparticles in a liquid environment. An input–output relation based model for the magnetic micromanipulator is obtained, verified, and used in the analysis of controllers. A model-free linear controller is designed using the offset current approach. An optimal nonlinear controller based on Karush–Kuhn–Tucker conditions is designed and then modified to produce smooth control signals. Experimental results are provided to show the efficiency and feasibility of the proposed controllers. The model-free controllers yield short settling time and zero steady-state error in the control of magnetic microparticles.

Optimal model-free fuzzy logic control for autonomous unmanned aerial vehicle

2021 ◽  
pp. 095441002110253
Author(s):  
Hossam E Glida ◽  
Latifa Abdou ◽  
Abdelghani Chelihi ◽  
Chouki Sentouh ◽  
Gabriele Perozzi
Keyword(s):  
Fuzzy Logic ◽  
Unmanned Aerial Vehicle ◽  
Fuzzy Logic Control ◽  
Estimation Error ◽  
Design Parameters ◽  
Multiple Model ◽  
Optimal Model ◽  
Model Free ◽  
Logic Control ◽  
Aerial Vehicle

This article deals with the issue of designing a flight tracking controller for an unmanned aerial vehicle type of quadrotor based on an optimal model-free fuzzy logic control approach. The main design objective is to perform an automatic flight trajectory tracking under multiple model uncertainties related to the knowledge of the nonlinear dynamics of the system. The optimal control is also addressed taking into consideration unknown external disturbances. To achieve this goal, we propose a new optimal model-free fuzzy logic–based decentralized control strategy where the influence of the interconnection term between the subsystems is minimized. A model-free controller is firstly designed to achieve the convergence of the tracking error. For this purpose, an adaptive estimator is proposed to ensure the approximation of the nonlinear dynamic functions of the quadrotor. The fuzzy logic compensator is then introduced to deal with the estimation error. Moreover, the optimization problem to select the optimal design parameters of the proposed controller is solved using the bat algorithm. Finally, a numerical validation based on the Parrot drone platform is conducted to demonstrate the effectiveness of the proposed control method with various flying scenarios.

A Distributed Model-Free Controller for Enhancing Power System Transient Frequency Stability

2019 ◽  
Vol 15 (3) ◽  
pp. 1361-1371 ◽  
Author(s):  
Yinliang Xu ◽  
Wei Zhang ◽  
Mo-Yuen Chow ◽  
Hongbin Sun ◽  
Hoay Beng Gooi ◽  
...  
Keyword(s):  
Power System ◽  
Frequency Stability ◽  
Distributed Model ◽  
Model Free ◽  
Model Free Controller

Event-triggered discrete extended state observer–based model-free controller for quadrotor position and attitude trajectory tracking

2021 ◽  
pp. 095965182110553
Author(s):  
Dingxin He ◽  
Haoping Wang ◽  
Yang Tian ◽  
Konstantin Zimenko
Keyword(s):  
Trajectory Tracking ◽  
Signal Transmission ◽  
State Observer ◽  
Extended State Observer ◽  
Extended State ◽  
Model Free ◽  
Model Free Controller ◽  
Quadrotor System ◽  
Static Threshold ◽  
Event Triggered

In this article, an event-triggered discrete extended state observer–based model-free controller is developed for the position and attitude trajectory tracking of a quadrotor with uncertainties and external disturbances. The referred event-triggered discrete extended state observer–based model-free controller is composed of two event-triggered mechanisms, ultra-local model-based discrete extended state observer and proportional-derivative sub-controller. To reduce system output signal transmission, the event-triggered mechanism of output signal which owns dynamic and static threshold is designed. Based on event-triggered output signals, the discrete extended state observer is constructed to obtain the estimations of state values which are utilized as controller’s variables and to compensate for the lumped disturbances. The proportional-derivative sub-controller is adopted to guarantee the convergence of trajectory tracking error. To decrease control input signal transmission, the event-triggered mechanism of input signal that processes static threshold is constructed. Moreover, the stability analysis of overall quadrotor system with the proposed control strategy is investigated using Lyapunov theorem and the Zeno behavior is avoided. Finally, corresponding control scheme for quadrotor system is structured and the numerical comparative simulation and co-simulation experiment are given to demonstrate the effectiveness and performance of the proposed approach.

Tracking control design for a multi-degree underactuated flexible-cable overhead crane system with large swing angle based on singular perturbation method and an energy-shaping technique

2019 ◽  
Vol 25 (11) ◽  
pp. 1752-1767 ◽  
Author(s):  
Mohammad H. Fatehi ◽  
Mohammad Eghtesad ◽  
Dan S. Necsulescu ◽  
Ali A. Fatehi
Keyword(s):  
Control System ◽  
Singular Perturbation ◽  
Underactuated System ◽  
Overhead Crane ◽  
Nonlinear Controller ◽  
Parameter Uncertainties ◽  
Energy Shaping ◽  
Flexible Cable ◽  
Shaping Technique ◽  
Linear Controller

A flexible-cable overhead crane system having large swing is studied as a multi-degree underactuated system. To resolve the system dynamics complexities, a second order singular perturbation (SP) formulation is developed to divide the crane dynamics into two one-degree underactuated fast and slow subsystems. Then, a control system is designed based on the two-time scale control (TTSC) method to: (a) transfer the payload to a desired location and decrease the payload swing, by a nonlinear controller for slow dynamics; and (b) suppress transverse vibrations of the cable, by a linear controller for fast dynamics. The nonlinear controller is designed based on an energy shaping technique according to the controlled Lagrangian method. To demonstrate the control system effectiveness, an example of the flexible cable crane systems with a lightweight payload is considered to perform simulations. In addition to the proposed control system, two other controllers; namely, a linear controller based on the linear–quadratic regulator method and a TTSC based on the approximate SP model and partial feedback linearization, are applied to the system for comparison. Also, by applying a disturbance force to the trolley and considering 10% uncertainty in crane parameters, the control performance against disturbances and parameter uncertainties is investigated.

scholarly journals Designing of Adaptive Model-Free Controller Based on Output Error and Feedback Linearization

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
S. Pezeshki ◽  
M. A. Badamchizadeh ◽  
S. Ghaemi ◽  
M. A. Poor
Keyword(s):  
Feedback Linearization ◽  
Adaptive Controller ◽  
Control Signal ◽  
Adaptive Model ◽  
New Approach ◽  
Output Error ◽  
Model Free ◽  
Signal Changes ◽  
Simulation Results ◽  
Model Free Controller

This paper introduces a new approach to design Model-Free Adaptive Controller (MFAC) using adaptive fuzzy procedure as a feedback linearization based on output error. The basic idea is to transfer the control signal to an appropriate surface and then, depending on the output error of system, the control signal changes around this surface. Some examples are provided as well to illustrate the efficiency of the proposed approach. The obtained simulation results have shown good performances of the proposed controller.

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