Linguistic Fuzzy Logic Control of a Double Inverted Pendulum With Destabilizing Fractional Dampers

2016 ◽  
Author(s):  
Arman Dabiri ◽  
Morad Nazari ◽  
Eric A. Butcher
Keyword(s):  
Human Brain ◽  
Inverted Pendulum ◽  
Fuzzy Controller ◽  
Equations Of Motion ◽  
A Priori ◽  
Fuzzy Rules ◽  
Brain Functions ◽  
Logic Control ◽  
Linguistic Rules ◽  
Two Degree Of Freedom

In this paper, a fuzzy controller is designed for a mechanical system with fractional damping without a priori knowledge of the system dynamics. Because of the constitutive equation of the damping, equations of motion of the system consist of fractional order terms. In the process of developing the fuzzy controller, the fuzzy rules are selected based on the human brain functions. The controller is first implemented for the case of a single inverted pendulum with destabilizing fractional dampings mounted on a cart, i.e. a two degree of freedom (DOF) system, where the functions of human brain in balancing a stick on a fingertip are used to train the fuzzy rules. Then, by extending the linguistic rules, the controller is applied to a double inverted pendulum with destabilizing fractional dampings mounted on a cart, i.e. a three DOF system. Since the linguistic rules are based on qualitative motion of the pendulums, the controller is capable bringing the system to rest at the unstable equilibrium point despite the fractional destabilizing damping in the system. Finally, the numerical results of the both examples are discussed.

Optimal Design for Fuzzy Controller by Ant Colony Algorithm

2010 ◽  
Vol 439-440 ◽  
pp. 1190-1196 ◽  
Author(s):  
Bao Jiang Zhao
Keyword(s):  
Ant Colony Algorithm ◽  
Inverted Pendulum ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Ant Colony ◽  
Fuzzy Rules ◽  
Real Time Control ◽  
Time Control ◽  
Information Updating ◽  
Fuzzy Logical

Fuzzy logical controller is one of the most important applications of fuzzy-rule-based system that models the human decision processing with a collection of fuzzy rules. In this paper, an adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of selection of the paths and the strategy of the trail information updating. The algorithm is used to design a fuzzy logical controller automatically for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due to multivariable inputs, state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. Experimental results show that the designed controller can control actual inverted pendulum successfully.

scholarly journals Flutter Suppression of an Airfoil Using Neuro-Fuzzy Control

2021 ◽  
Author(s):  
Chun Meng
Keyword(s):  
Fuzzy Controller ◽  
Equations Of Motion ◽  
Fuzzy Rules ◽  
Matlab Simulation ◽  
Modeling And Analysis ◽  
Flutter Suppression ◽  
Flutter Speed ◽  
Neuro Fuzzy ◽  
Excited Vibration ◽  
And Control

Flutter, a self-excited vibration of wings and control surfaces, can lead to catastrophic failure of aircraft structures. Classical methods have been applied successfully for flutter suppression and for increasing the flutter critical speed. With the demand of higher speed and more flexible aircraft, more advanced active flutter control techniques are required. In this study, a neuro-fuzzy methodology for flutter suppression of a two dimensional airfoil is explored. A MATLAB simulation environment is used for the modeling and analysis. The airfoil model is simulated according to a set of aeroelastic equations of motion. A neuro-fuzzy controller, called NEFCON, is then embedded in the airfoil model for increasing the flutter speed. NEFCON learns from the motion of the airfoil and automatically produces fuzzy rules. The simulation results show that these fuzzy rules can successfully increase the critical flutter speed. The performance of the fuzzy rules is tested with differential airfoil parameters.

scholarly journals Flutter Suppression of an Airfoil Using Neuro-Fuzzy Control

2021 ◽  
Author(s):  
Chun Meng
Keyword(s):  
Fuzzy Controller ◽  
Equations Of Motion ◽  
Fuzzy Rules ◽  
Matlab Simulation ◽  
Modeling And Analysis ◽  
Flutter Suppression ◽  
Flutter Speed ◽  
Neuro Fuzzy ◽  
Excited Vibration ◽  
And Control

Flutter, a self-excited vibration of wings and control surfaces, can lead to catastrophic failure of aircraft structures. Classical methods have been applied successfully for flutter suppression and for increasing the flutter critical speed. With the demand of higher speed and more flexible aircraft, more advanced active flutter control techniques are required. In this study, a neuro-fuzzy methodology for flutter suppression of a two dimensional airfoil is explored. A MATLAB simulation environment is used for the modeling and analysis. The airfoil model is simulated according to a set of aeroelastic equations of motion. A neuro-fuzzy controller, called NEFCON, is then embedded in the airfoil model for increasing the flutter speed. NEFCON learns from the motion of the airfoil and automatically produces fuzzy rules. The simulation results show that these fuzzy rules can successfully increase the critical flutter speed. The performance of the fuzzy rules is tested with differential airfoil parameters.

Identification of Fuzzy Rule on Manual Control of an Unstable System

1995 ◽  
Vol 7 (2) ◽  
pp. 100-107
Author(s):  
Shigehiro Masui ◽  
◽  
Toshiro Terano ◽  
Yoshimasa Sugaya ◽  
◽  
...  
Keyword(s):  
Inverted Pendulum ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Human Operator ◽  
State Variables ◽  
Initial Deviation ◽  
Control Rules ◽  
Linguistic Rules ◽  
Skilled Operator ◽  
Human Operators

After some training, human operators can manually control very unstable objects when some proper information is given. But they can hardly explain how they do it, because they operate them intuitively and not logically. In this paper, we study the human behavior during the control of a double inverted pendulum and identify its control rules experimentally. The motion of a double inverted pendulum is simulated by a micro-computer and some of the state variables are indicated on a CRT, observed by a subject, and controlled on a keyboard. In order to find which information is used by a subject, his visual points are examined by an eye-camera. As a result, we see that there are three phases of operation, that is, the decrease of initial deviation, the prevention of over-shoot, and the keeping of stability. Next, the motion of a pendulum is analyzed qualitatively in each phase so as to identify the control rules of a human operator. By this analysis, we see that the intuitive manipulator of the human operator is quite reasonable from the physical viewpoint, and we represent it by some linguistic rules. From these results, we suggest a hierarchical structure of fuzzy rules as a model of a human operator which is verified through experiments on fuzzy control. It is concluded that this fuzzy controller acts as a skilled operator, but its performance is far superior to humans.

Fuzzy Logic Control of Rotational Inverted Pendulum

2011 ◽  
Vol 177 ◽  
pp. 84-92 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Inverted Pendulum ◽  
Equations Of Motion ◽  
Dynamic Equations ◽  
Control Algorithms ◽  
Logic Control ◽  
Single Input ◽  
Balancing Control ◽  
Ladder Logic

The rotational inverted pendulum is a structure that was primarily developed by Katsuhisa Furuta. It is widely used thorough the control laboratories to demonstrate the effectiveness of nonlinear control algorithms. The rotational inverted pendulum is a nonlinear system of fourth order with a single input variable. In this article the full dynamic equations of motion of the rotational inverted pendulum are derived using Lagrangian formulation. Consequently, a comparison of obtained mathematical model with other models described and available in literature is conducted by means of computer simulations. Eventually, a complete energy build-up swing-up algorithm and fuzzy stabilization algorithm for the system are developed. The control algorithm is then implemented on a PLC device in order to control the existing laboratory stand available at the Department of Process Control [1]. The algorithm is implemented with the use of ladder logic and structured text programming language. The robustness of elaborated balancing control is verified by subsequent real-time tests conducted on the laboratory stand.

The Influence of Loading Position in A Priori High Stress Detection using Mode Superposition

2020 ◽  
Vol 1 (1) ◽  
pp. 93-102
Author(s):  
Carsten Strzalka ◽  
◽  
Manfred Zehn ◽  
Keyword(s):  
Finite Element ◽  
Degrees Of Freedom ◽  
Equations Of Motion ◽  
A Priori ◽  
High Stress ◽  
Von Mises Stress ◽  
Detailed Knowledge ◽  
Variable Loading ◽  
Numerical Effort ◽  
Von Mises

For the analysis of structural components, the finite element method (FEM) has become the most widely applied tool for numerical stress- and subsequent durability analyses. In industrial application advanced FE-models result in high numbers of degrees of freedom, making dynamic analyses time-consuming and expensive. As detailed finite element models are necessary for accurate stress results, the resulting data and connected numerical effort from dynamic stress analysis can be high. For the reduction of that effort, sophisticated methods have been developed to limit numerical calculations and processing of data to only small fractions of the global model. Therefore, detailed knowledge of the position of a component’s highly stressed areas is of great advantage for any present or subsequent analysis steps. In this paper an efficient method for the a priori detection of highly stressed areas of force-excited components is presented, based on modal stress superposition. As the component’s dynamic response and corresponding stress is always a function of its excitation, special attention is paid to the influence of the loading position. Based on the frequency domain solution of the modally decoupled equations of motion, a coefficient for a priori weighted superposition of modal von Mises stress fields is developed and validated on a simply supported cantilever beam structure with variable loading positions. The proposed approach is then applied to a simplified industrial model of a twist beam rear axle.

scholarly journals Real-Time Swing-up Control of Non-Linear Inverted Pendulum using Lyapunov based Optimized Fuzzy Logic Control

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Arpit Jain ◽  
Abhinav Sharma ◽  
Vibhu Jately ◽  
Brian Azzopardi ◽  
Sushabhan Choudhury
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Control ◽  
Inverted Pendulum ◽  
Logic Control ◽  
Non Linear

The effects of nonlinear energy sink and piezoelectric energy harvester on aeroelastic instability of an airfoil

2021 ◽  
pp. 107754632199358
Author(s):  
Ali Fasihi ◽  
Majid Shahgholi ◽  
Saeed Ghahremani
Keyword(s):  
Energy Harvester ◽  
Equations Of Motion ◽  
Continuation Method ◽  
Dynamical Behavior ◽  
Harmonic Balance Method ◽  
Nonlinear Energy Sink ◽  
Piezoelectric Energy ◽  
Energy Sink ◽  
Two Degree Of Freedom ◽  
Nonlinear Energy

The potential of absorbing and harvesting energy from a two-degree-of-freedom airfoil using an attachment of a nonlinear energy sink and a piezoelectric energy harvester is investigated. The equations of motion of the airfoil coupled with the attachment are solved using the harmonic balance method. Solutions obtained by this method are compared to the numerical ones of the pseudo-arclength continuation method. The effects of parameters of the integrated nonlinear energy sink-piezoelectric attachment, namely, the attachment location, nonlinear energy sink mass, nonlinear energy sink damping, and nonlinear energy sink stiffness on the dynamical behavior of the airfoil system are studied for both subcritical and supercritical Hopf bifurcation cases. Analyses demonstrate that absorbing vibration and harvesting energy are profoundly affected by the nonlinear energy sink parameters and the location of the attachment.

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