scholarly journals Control de velocidad de un motor de reluctancia variable de 4 fases y 6 polos, utilizando técnicas de control clásico

2021 ◽  
Author(s):  
◽  
Jesús Daniel González San Román
Keyword(s):  
Control System ◽  
Linear Model ◽  
Linear Models ◽  
Controller Design ◽  
Dead Zone ◽  
Digital Simulation ◽  
Viscous Friction ◽  
Pi Controller ◽  
Analysis And Design ◽  
Non Linear

In this work, the analysis and design of a speed control system of a variable reluctance motor with six poles and four phases is presented. The nonlinear motor model includes the nonlinearity of the Coulomb friction plus the viscous friction. The structural analysis of the non-linear model is carried out, which is linearized at the operating point established at 2000rpm. Both the non-linear and linear models are compared both in their structure and in their responses through digital simulations, finding that under certain conditions both have similar behaviors. Subsequently, based on the linear model, a classic PI controller is designed and subjected to regulation, tracking and load torque variation tests. The controller design is carried out using the Bode shaping technique, guaranteeing adequate gain and phase margins with a higher bandwidth than the mechanical subsystem mode. The robustness is verified by means of the digital simulation of the control system using the non-linear model, which is also subjected to load variations, finding that the PI controller has excellent performance in both regulation and tracking. Finally, two additional controllers are proposed: the first is a PII controller, the objective of which is to reduce the effect of the non-linearity called dead zone present in the motor at start-up or at low speeds. The second is a PI controller that adds a new technique for reducing the ripple present in the speed and torque responses, characteristics of this type of motor.

scholarly journals Hard Dead Zone and Friction Modeling and Identification of a Permanent Magnet DC Motor Non-Linear Model

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Permanent Magnet ◽  
Linear Model ◽  
Motor Behavior ◽  
Dead Zone ◽  
Viscous Friction ◽  
Dc Motor ◽  
Time Data ◽  
Wide Range ◽  
Non Linear ◽  
Permanent Magnet Dc Motor

The identification of a permanent magnet DC motor model including non-linearities dead zone, Coulomb friction, and viscous friction, is presented. The dead zone considered here is the so call "hard" dead zone, whereas the friction force is modeled in two different ways: first, considering the value of viscous coefficient friction as a constant and second, approximating viscous coefficient by a polynomial depending on motors rotor velocity. The polynomial representation of the viscous friction value allows it to be adjusted automatically as a function of the speed of the system, as occurs in real systems. Therefore, a model capable of better representing the real motor behavior along a wide range of operation is obtained. The non-linear model is validated and compared using real-time data obtained from Quanser's direct current motor control trainer system, using the numerical tool Matlab®/Simulink™

scholarly journals Multiloop and Prediction Based Controller Design for Sugarcane Crushing Mill Process

2015 ◽  
Vol 4 (4) ◽  
pp. 135
Author(s):  
Sandeep Kumar Sunori ◽  
Pradeep Kumar Juneja ◽  
Anamika Bhatia Jain
Keyword(s):  
Control System ◽  
Linear Model ◽  
Predictive Control ◽  
Closed Loop ◽  
Controller Design ◽  
Mimo System ◽  
Pi Controller ◽  
Open Loop ◽  
Turbine Speed ◽  
Mill Process

In the present work a sugarcane crushing mill is presented as a MIMO system with high multivariable interaction.A linear model of the plant is taken with flap position and turbine speed as manipulated variables and mill torque and buffer chute height as controlled variables.The multiloop PI controller has been designed for this plant by first investigating the RGA and the value of Niederlinski index of this plant.The decoupling of this system is done and the respective open loop and closed loop step responses are observed and compared with those of the composite MIMO system. Also the performance of multiloop controller is compared with controller designed using model predictive control system strategy for this plant.

scholarly journals Experimental validation of wind energy estimation

2020 ◽  
Vol 24 (6 Part A) ◽  
pp. 3795-3806
Author(s):  
Predrag Zivkovic ◽  
Mladen Tomic ◽  
Vukman Bakic
Keyword(s):  
Wind Speed ◽  
Linear Model ◽  
Linear Models ◽  
Stokes Equations ◽  
Momentum Conservation ◽  
Electricity Production ◽  
Navier Stokes ◽  
Energy Estimation ◽  
Navier Stokes Equations ◽  
Non Linear

Wind power assessment in complex terrain is a very demanding task. Modeling wind conditions with standard linear models does not sufficiently reproduce wind conditions in complex terrains, especially on leeward sides of terrain slopes, primarily due to the vorticity. A more complex non-linear model, based on Reynolds averaged Navier-Stokes equations has been used. Turbulence was modeled by modified two-equations k-? model for neutral atmospheric boundary-layer conditions, written in general curvelinear non-orthogonal co-ordinate system. The full set of mass and momentum conservation equations as well as turbulence model equations are numerically solved, using the as CFD technique. A comparison of the application of linear model and non-linear model is presented. Considerable discrepancies of estimated wind speed have been obtained using linear and non-linear models. Statistics of annual electricity production vary up to 30% of the model site. Even anemometer measurements directly at a wind turbine?s site do not necessarily deliver the results needed for prediction calculations, as extrapolations of wind speed to hub height is tricky. The results of the simulation are compared by means of the turbine type, quality and quantity of the wind data and capacity factor. Finally, the comparison of the estimated results with the measured data at 10, 30, and 50 m is shown.

scholarly journals Hybrid MARMA-NARX model for flow forecasting based on the large-scale climate signals, sea-surface temperatures, and rainfall

2018 ◽  
Vol 49 (6) ◽  
pp. 1788-1803 ◽  
Author(s):  
Mohammad Ebrahim Banihabib ◽  
Arezoo Ahmadian ◽  
Mohammad Valipour
Keyword(s):  
Linear Model ◽  
Hybrid Model ◽  
Large Scale ◽  
Linear Models ◽  
Moving Average ◽  
Effective Parameters ◽  
Forecasting Accuracy ◽  
Local Factor ◽  
Non Linear ◽  
Climate Signals

Abstract In this study, to reflect the effect of large-scale climate signals on runoff, these indices are accompanied with rainfall (the most effective local factor in runoff) as the inputs of the hybrid model. Where one-year in advance forecasting of reservoir inflows can provide data to have an optimal reservoir operation, reports show we still need more accurate models which include all effective parameters to have more forecasting accuracy than traditional linear models (ARMA and ARIMA). Thus, hybridization of models was employed for improving the accuracy of flow forecasting. Moreover, various forecasters including large-scale climate signals were tested to promote forecasting. This paper focuses on testing MARMA-NARX hybrid model to enhance the accuracy of monthly inflow forecasts. Since the inflow in different periods of the year has in linear and non-linear trends, the hybrid model is proposed as a means of combining linear model, monthly autoregressive moving average (MARMA), and non-linear model, nonlinear autoregressive model with exogenous (NARX) inputs to upgrade the accuracy of flow forecasting. The results of the study showed enhanced forecasting accuracy through using the hybrid model.

A tube-based robust MPC for duty-cycled rotation needle steering systems with bounded disturbances

2021 ◽  
pp. 014233122110430
Author(s):  
Zhi Qi ◽  
Qianyue Luo ◽  
Hui Zhang
Keyword(s):  
Model Predictive Control ◽  
Linear Model ◽  
Predictive Control ◽  
Control Method ◽  
Controller Design ◽  
Control Approach ◽  
Bounded State ◽  
Non Linear ◽  
System States ◽  
Trajectory Tracking Controller

In this paper, we aim to design the trajectory tracking controller for variable curvature duty-cycled rotation flexible needles with a tube-based model predictive control approach. A non-linear model is adopted according to the kinematic characteristics of the flexible needle and a bicycle method. The modeling error is assumed to be an unknown but bounded disturbance. The non-linear model is transformed to a discrete time form for the benefit of predictive controller design. From the application perspective, the flexible needle system states and control inputs are bounded within a robust invariant set when subject to disturbance. Then, the tube-based model predictive control is designed for the system with bounded state vector and inputs. Finally, the simulation experiments are carried out with tube-based model predictive control and proportional integral derivative controller based on the particle swarm optimisation method. The simulation results show that the tube-based model predictive control method is more robust and it leads to much smaller tracking errors in different scenarios.

scholarly journals Comparison of Linear and Nonlinear Behavior of Track Elements in Contact-Impact Models

2018 ◽  
Author(s):  
Jabbar Ali Zakeri ◽  
Mosab Reza Tajalli
Keyword(s):  
Linear Model ◽  
3D Model ◽  
Linear Models ◽  
Wave Length ◽  
Short Wave ◽  
Contact Forces ◽  
Reliable Estimate ◽  
Impact Forces ◽  
Linear Behavior ◽  
Non Linear

Existence of short wave length irregularities and discontinuities in the rail, such as corrugation, isolated rail joints, crossings and rail breakage, result in impact forces and an increase in wheel-rail contact force. Extreme forces in such could result in non-linear behavior of ballast and pads, and as a result, employing common linear models mihgt over/under estimate contact forces. A 3D model of wheel and rail is developed in this paper, and by considering rail breakage, validity of linear models and considering non-linear behavior of materials are studied. Wheel-rail interactions are studied for two common pads with high stiffness (HDPE) and low stiffness (Studded) for speeds of 20 to 160 km/h. Three behavioral patterns are considered for the developed 3D model: linear pad and ballast (LP-LB), nonlinear pad and linear ballast (NLP, LB), and nonlinear pad and ballast (NLP, NLB), and results are compared. According to the results, for HDPE pads and impact forces of up to 30 tons, linear model for material could estimate acceptable results. Yet for studded pads, linear model estimates forces that are comparably less than those estimated by non-linear model. Moreover employing NLP-LB model overestimates pad and wheel-rail contact forces by a rather small margin, compared to those estimated by NLP-NLB model, and hence, could be a suitable replacement for it. It is also observed that in order to have a reliable estimate of ballast forces, using non-linear ballast models are mandatory, and neither LP-LB nor NLP-LB could be acceptable replacements.

State Feedback Linearization of a Non-linear Permanent Magnet Synchronous Motor Drive

2016 ◽  
Vol 1 (3) ◽  
pp. 534 ◽  
Author(s):  
Pilla Ramana ◽  
Karlapudy Alice Mary ◽  
Munagala Surya Kalavathi
Keyword(s):  
Control System ◽  
Feedback Linearization ◽  
State Feedback ◽  
Permanent Magnet Synchronous Motor ◽  
Pi Controller ◽  
State Feedback Control ◽  
Pole Placement ◽  
Motor Speed ◽  
Control Loops ◽  
Non Linear

Control system design for inverter fed drives previously used the classical transfer function approach for single-input singleoutput (SISO) systems. Proportional plus Integral (PI) controllers were designed for individual control loops.It is found that the transient response of a PI controller is slow and is improved by pole placement through state feedback. However, the effective gains of the PI controller are substantially decreased as a function of the increase of motor speed. A control system is generally characterized by the hierarchy of the control loops, where the outer loop controls the inner loops. The inner loops are designed to execute progressively faster. The speed controller (PI controller) processes the speed error and generates the reference torque. In the inner loop, firstly a non-linear controller is designed for the system by which the system nonlinearity is canceled using state or exact feedback linearization. In addition, a linear state feedback control law based on pole placement technique including the integral of output error (IOE) is used in order to achieve zero steady state error with respect to reference current specification, while at the same time improving the dynamic response.The proposed scheme has been validated through extensive simulation using MATLAB.

Machine Learning Techniques on Multidimensional Curve Fitting Data Based on R- Square and Chi-Square Methods

2016 ◽  
Vol 6 (3) ◽  
pp. 974 ◽  
Author(s):  
Vidyullatha P ◽  
D. Rajeswara Rao
Keyword(s):  
Machine Learning ◽  
Linear Model ◽  
Curve Fitting ◽  
Linear Models ◽  
Machine Learning Techniques ◽  
Chi Square ◽  
Curve Fit ◽  
Learning Techniques ◽  
Non Linear ◽  
Data Points

<p>Curve fitting is one of the procedures in data analysis and is helpful for prediction analysis showing graphically how the data points are related to one another whether it is in linear or non-linear model. Usually, the curve fit will find the concentrates along the curve or it will just use to smooth the data and upgrade the presence of the plot. Curve fitting checks the relationship between independent variables and dependent variables with the objective of characterizing a good fit model. Curve fitting finds mathematical equation that best fits given information. In this paper, 150 unorganized data points of environmental variables are used to develop Linear and non-linear data modelling which are evaluated by utilizing 3 dimensional ‘Sftool’ and ‘Labfit’ machine learning techniques. In Linear model, the best estimations of the coefficients are realized by the estimation of R- square turns in to one and in Non-Linear models with least Chi-square are the criteria. </p>

PI Controller Design for DFIG Wind Power Generation System RSC Based on PSO Algorithm

2014 ◽  
Vol 508 ◽  
pp. 196-199
Author(s):  
Yi Min Chu ◽  
Wu Wang
Keyword(s):  
Control System ◽  
Controller Design ◽  
Good Control ◽  
Pso Algorithm ◽  
Pi Controller ◽  
Current Loop ◽  
Control Effect ◽  
Loop Control ◽  
Stator Flux ◽  
Rotor Side Converter

PID controller has widely used in control system for its simple structure, good control effect and strong robustness, the PI control strategy was introduced into rotor side converter of DFIG control with the mathematical models and the structure of stator flux-oriented vector control. Particle swam optimization algorithm was a new random optimization technology which has the features of rapid calculation speed. The PI controller design for RSC current loop and speed loop control was analyzed, and the PSO algorithm was presented for PI controller design, the simulation experiments demonstrated that the algorithm was suitable for the RSC control system with PSO remarkable search capability.

scholarly journals Non-linear behaviour of charge-pump phase-locked loops

2010 ◽  
Vol 8 ◽  
pp. 161-166 ◽  
Author(s):  
C. Wiegand ◽  
C. Hedayat ◽  
U. Hilleringmann
Keyword(s):  
Linear Model ◽  
Dead Zone ◽  
Charge Pump ◽  
Phase Detector ◽  
Phase Locked Loops ◽  
Time Varying ◽  
Invariant Representation ◽  
Non Linear ◽  
Linear Behaviour ◽  
Time Invariant

Abstract. The analysis of the mixed analogue and digital structure of charge-pump phase-locked loops (CP-PLL) is a challenge in modelling and simulation. In most cases the system is designed and characterized using its continuous linear model or its discrete linear model neglecting its non-linear switching behaviour. I.e., the time-varying model is approximated by a time-invariant representation using its average dynamics. Depending on what kind of phase detector is used, the scopes of validity of these approximations are different. Here, a preeminent characterization and simulation technique based on the systems event-driven feature is presented, merging the logical and analogue inherent characteristics of the system. In particular, the high-grade non-linear locking process and the dead-zone are analyzed.

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