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Automated vehicles have drawn great attention in research and industry, due to their potential benefits in driving without passengers. Using computer simulation in motion and speed control of the vehicles can reduce errors and costs. Fuzzy logic provides a different way for issues that need to be controlled. This method is concentrated on what the system should do, not on how the works are done. Using...
In this paper, we propose an algorithm based on fuzzy control to ensure the stability of the quadrotor. After giving the nonlinear model of the robot, its representation by a Takagi-Sugeno (T-S) fuzzy model is first discussed. Next, a fuzzy controller are synthesized which guarantee desired control performances. The given controller is designed using numerical tools (Linear Matrix Inequalities-LMI)...
Recently, great interest has been the reluctance to move to DC motors and its applications in industry Such as robotics, textiles, and household electric vehicle or application or Aviation domains. The first control techniques used classic controllers have been difficult and complicated because of their requirements for a position sensor of the rotor. The position sensor rotor is an important contribution...
In this study, interval type2 fuzzy logic (IT2FL) and PID controller is designed for swing-up position control of double inverted pendulum (DIP) system. The double inverted pendulum system consists of two rigid bars connected by a revolute joint. Mass of the revolute joint is included in the dynamic model.Rigid bars in the system are assumed to experience planar motion. The pendulum system is connected...
In odder to improve positioning precision and decrease the exceed initial value of solar cell transfer robot, we design a kind of PID controller with fuzzy self-adjusting function based on fuzzy control technique, solve the problem that the PID-controller can not adjust parameters itself on line. The result of simulation in fuzzy logic toolbox of Matlab proves that the controller possess both the...
This paper deals with multi-objective behavior coordination and sensory networks based on fuzzy control for multiple mobile robots. In multi-objective behavior coordination, weights are assigned to basic behaviors and updated gradually according to the time series of sensory inputs. A robot with our behavior coordination can take a smooth action. The sensory network is the self-update mechanism of...
Human motion simulation is an ill-posed problem. In order to predict unique lifting motion trajectories, a motion simulation model based on fuzzy-logic control is presented. The human body was represented by a 2-D five-segment model, and the neural controller was specified by fuzzy logic. Fuzzy rules were defined with their antecedent part describing the fuzzy variables of scaled positional error...
A novel control strategy based on passivity theory was proposed with special attention to trajectory tracking and robust control of rigid robot. In this paper, robot model was divided into nominal model and uncertainty part. Based on the backstepping approach, feedback passivity was used to design controller for the nominal model. A variable structure concentrated compensation controller was adopted...
The purpose of this paper is to propose adaptive fuzzy sliding mode control (SMC) based on radial basis function neural network (RBFNN) for trajectory tracking problem of three link robot manipulator. A RBFNN is used to compute the equivalent control of sliding mode control. A Lyapunov function is selected for the design of the SMC and an adaptive algorithm is used for weight adaptation of the RBFNN...
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