Optimal fuzzy control using hedge algebras of a damped elastic jointed inverted pendulum

In this paper, three controllers including OFCHA (optimal fuzzy control using hedge algebras-HAs), FCHA (fuzzy control using HAs) and CFC (conventional fuzzy control) are designed. Our attention is paid to the stability in the vertical position of a damped-elastic-jointed inverted pendulum subjected to a time-periodic follower force. Different values of the pendulum length are considered. Simulation results are exposed to illustrate the effect of OFCHA in comparison with FCHA and CFC

Bibliometric Mapping of the Computational Intelligence Field

In this paper, a bibliometric study of the computational intelligence field is presented. Bibliometric maps showing the associations between the main concepts in the field are provided for the periods 1996–2000 and 2001–2005. Both the current structure of the field and the evolution of the field over the last decade are analyzed. In addition, a number of emerging areas in the field are identified. It turns out that computational intelligence can best be seen as a field that is structured around four important types of problems, namely control problems, classification problems, regression problems, and optimization problems. Within the computational intelligence field, the neural networks and fuzzy systems subfields are fairly intertwined, whereas the evolutionary computation subfield has a relatively independent position.neural networks;bibliometric mapping;fuzzy systems;bibliometrics;computational intelligence;evolutionary computation

Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms

This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and increasing its flexibility. Designing a two-wheeled robot with five degrees of freedom creates a high challenge for the control, therefore the modelling and design of such robot should be precise with a uniform distribution of mass over the robot and the actuators. By employing the Lagrangian modelling approach, the TWRM′s mathematical model is derived and simulated in Matlab/Simulink®. For stabilizing the system′s highly nonlinear model, two control approaches were developed and implemented: proportional-integral-derivative (PID) and fuzzy logic control (FLC) strategies. Considering multiple scenarios with different initial conditions, the proposed control strategies′ performance has been assessed

CONTROL OF A PENDULUM USING HEDGE ALGEBRAS CONTAINING ACTUATOR SATURATION

In this study, the control problem of a pendulum using hedge-algebras-based fuzzy controller (HAC) containing actuator saturation is presented. In HAC, linguistic values of linguistic terms are obtained through semantically quantifying mappings (SQMs) based on several fuzzy parameters of each linguistic variable without using any fuzzy set and inherent order relationships between linguistic values are always ensured. Hence, the design of a HAC leads to determining parameters of SQMs. Numerical results of HAC are compared with those of an analogical conventional fuzzy controller (FC) in order to show advantages of the proposed method.In this study, the control problem of a pendulum using hedge-algebras-based fuzzy controller (HAC) containing actuator saturation is presented. In HAC, linguistic values of linguistic terms are obtained through semantically quantifying mappings (SQMs) based on several fuzzy parameters of each linguistic variable without using any fuzzy set and inherent order relationships between linguistic values are always ensured. Hence, the design of a HAC leads to determining parameters of SQMs. Numerical results of HAC are compared with those of an analogical conventional fuzzy controller (FC) in order to show advantages of the proposed method

Fabrication, Balancing and Analysis of Two Wheeled Robot

Two wheeled self balancing robot is based on the concept of inverted pendulum, which center of mass is above the pivot point. Generally the pendulum is an unstable system on its horizontal plane and must be balanced to remain upright. This can be achieved by applying require amount of torque to the pivot point. Similarly here in two wheeled balancing robot being unstable will deflect from its vertical position and try to fall down. The angle of tilt is calculated by IMU sensor and sends to the microcontroller, which further gives a command to the motor through the motor controller to move in the same direction where the robot has been tilted. When the motor will rotate, it will give an opposite torque to the robot through the pivot point which will counter the angle of deflection and the robot will be stable. This will happen for both the direction of the deflection and hence the robot will move forward and backward and finally it will be balanced. So it require both mechanical and electronics equipment for the robot to achieve the goal

CONTROL DE UN PÉNDULO DE FURUTA. UNA REVISIÓN DEL ESTADO DEL ARTE.

This work shows a state of art about the different modeling and control strategies for the inverted rotational Pendulum. A brief description of each of them from the creation of the Furuta Pendulum to the present day was made, we pay great interest of Friction phenomena in the control strategies, highlighting the whole world, include Colombia.Se realiza una descripcion de algunos trabajos reportados en la comunidad de control a nivel internacional y nacional sobre PENDULOS INVERTIDOS. Este trabajo abarca desde la creacion del pendulo de Furuta hasta la actualidad

Designing a hierarchical fuzzy logic controller using the differential evolution approach

In conventional fuzzy logic controllers, the computational complexity increases with the dimensions of the system variables; the number of rules increases exponentially as the number of system variables increases. Hierarchical fuzzy logic controllers ( HFLC) have been introduced to reduce the number of rules to a linear function of system variables. However, the use of hierarchical fuzzy logic controllers raises new issues in the automatic design of controllers, namely the coordination of outputs of sub- controllers at lower levels of the hierarchy. In this paper, a method is described for the automatic design of an HFLC using an evolutionary algorithm called differential evolution ( DE). The aim in this paper is to develop a sufficiently versatile method that can be applied to the design of any HFLC architecture. The feasibility of the method is demonstrated by developing a two- stage HFLC for controlling a cart - pole with four state variables. The merits of the method are automatic generation of the HFLC and simplicity as the number of parameters used for encoding the problem are greatly reduced as compared to conventional methods