Abstract

Abstract

This paper deals with mathematical modeling of Permanent magnet brushless DC (BLDC) motor in MATLAB-SIMULINK environment. Modeling of BLDC motor carried in transfer function, transfer equations and state space model to verify the performance as actuators. Mathematical switches to control electronic commutation of BLDC motor based on signals of Hall Effect position sensor using threephase inverter drive. Performance of the simplified mathematical inverter fed BLDC motor under steady state and dynamic conditions analyzed. Due to the switching losses during PWM generation generates low ripple content in torque of BLDC motor which described and eliminated through state space model. Comparison made of proposed modeling of BLDC motor with motor parameters like back-EMF, stator current and speed of BLDC motor, proposed work suggests the state space modeling holds a superior method for design of BLDC motor during high dynamic load performance and operating ranges

Abstract

This paper deals with mathematical modeling of Permanent magnet brushless DC (BLDC) motor in MATLAB-SIMULINK environment.

Modeling of BLDC motor carried in transfer function, transfer equations and state space model to verify the performance as actuators. Mathematical switches to control electronic commutation of BLDC motor based on signals of Hall Effect position sensor using three-phase inverter drive. Performance of the simplified mathematical inverter fed BLDC motor under steady state and dynamic conditions analyzed. Due to the switching losses during PWM generation generates low ripple content in torque of BLDC motor which described and eliminated through state space model. Comparison made of proposed modeling of BLDC motor with motor parameters like back-EMF, stator current and speed of BLDC motor, proposed work suggests the state space modeling holds a superior method for design of BLDC motor during high dynamic load performance and operating ranges.

Abstract

Abstract

Second order systems are those that respond to a second order differential equation. The study of a second order system is proposed, given by an RC electric circuit. The transfer equation was determined and the transient response was analyzed using the method of the Geometric Place of the Roots, likewise the coefficients of the PID controller were determined. From the response of the PID controller, a backpropagation neural network was created and trained to later replace the classic PID controller. In this work, the analysis of a PID controller case study is carried out where an artificial neural network has been implemented to evaluate its response. It is observed that the results are acceptable and with a good transient response.

Abstract

Abstract

In this paper we present the numerical solution, via the Finite Differences Method, of the fourth-order Partial Differential Equation that controls the deflection of bi-supported orthopropic thin plates when subjected to a uniformly distributed load. This method transforms the partial differential equation into a system of linear equations. To obtain the solution of this system, to facilitate the interpretation and reading of the results, a program compiled in language MatLab was developed, using the tool App Designer. The obtained results were compared with commercial software, using the Finite Element Method, where, through the percentage error, the equivalence was found in these results.

Abstract

Abstract