Proportional Integral Speed Controller Research Articles

Intelligent Control of an Experimental Small-Scale Wind Turbine

Nowadays, wind turbines are one of the most popular devices for producing clean and renewable electric energy. The rotor blades catch the wind’s kinetic energy to produce rotational energy from the turbine and electric energy from the generator. In small-scale wind turbines, there are several methods to operate the blades to obtain the desired speed of rotation and power outputs. These methods include passive stall, active stall, and pitch control. Pitch control sets the angular position of the blades to face the wind to achieve a predefined relationship between turbine speed or power and wind velocity. Typically, conventional Proportional Integral (PI) controllers are used to set the angular position of the rotor blades or pitch angle. Nevertheless, the quality of speed or power regulation may vary substantially. This study introduces a rotor speed controller for a pitch-controlled small-scale wind turbine prototype based on fuzzy logic concepts. The basics of fuzzy systems required to implement this kind of controller are presented in detail to counteract the lack of such material in the technical literature. The knowledge base of the fuzzy speed controller is composed of Takagi–Sugeno–Kang (TSK) fuzzy inference rules that implement a dedicated PI controller for any desired interval of wind velocities. Each wind velocity interval is defined with a fuzzy set. Simulation experiments show that the TSK fuzzy PI speed controller can outperform the conventional PI controller in the speed and accuracy of response, stability, and robustness over the whole range of operation of the wind turbine prototype.

Optimal proportional-integral speed control for closed-loop engine timing system

In internal combustion engines, adjusting the air-fuel ratio is essential to control the speed and minimize the burnt fuel. The throttle opening is the actuator to control the air-fuel. A better design for the used/conventional controller can give a better response without additional cost. In this work, the proposed controller gains of the proportional-integral (PI) controller are tuned to enhance the speed in constant and variable drive cycle modes. The tuning process is conducted based on two of the most efficient performance indices used in this field. The performance indices are integral absolute error (IAE) and integral time absolute error (ITAE). The optimization problem is solved using three reliable stochastic optimization algorithms to ensure mature convergence of the solutions, to avoid local optima solutions, and to ensure effective shrinking of the search space. The optimization algorithms are teaching-learning-based optimization (TLBO), particle swarm optimization (PSO), and genetic algorithm (GA). Different simulations are conducted to validate the results. The results are compared with conventional tuning methods regarding the system's time response.

Effective speed control of brushless DC motor using cascade 1PDf-PI controller tuned by snake optimizer

This paper introduces a cascade one proportional derivative incorporating filter (1PDf)-proportional integral (PI) controller abbreviated as c-1PDf-PI to deal effectively with the speed control issue of brushless DC (BLDC) motors. Two problems exist with implementing this controller such as iterated integral overflow and derivation-based chattering owing to the noise. The former is resolved by using an equivalent expression for the integral operation, while the latter is addressed by putting a first-order filter on the derivative term. To achieve the best performance from the controller, snake optimizer (SO) is fruitfully employed for optimizing the controller parameters without need for expert knowledge/interpretation. Here, a more reasonable cost function to assess the candidate solutions is also described. Simulations and laboratory experiments using DSP of TI TMS320F28335 are performed and the results are presented which show that the reference tracking performance, torque disturbance capability and robustness of the c-1PDf-PI controller have potential. These results are also contrasted by those offered by PI and 1PDf speed control schemes individually, affirming the superior performance of our proposal. As per the results, discussion and observation of this research, we stress that good performance and simplicity are salient advantages of the c-1PDf-PI controller, rendering it a good alternative over the complicated controller designs.

A Novel Control Method for Permanent Magnet Synchronous Linear Motor Based on Model Predictive Control and Extended State Observer

Permanent magnet synchronous linear motor (PMSLM) is widely used to meet the requirement of high dynamic accuracy positioning, such as in machine tools and devices of semiconductor manufacturing. A new 2-DOF control structure is proposed in this paper to improve the dynamic performance of the positioning servo system with PMSLM. Aiming at the position tracking performance, a control algorithm based on the model predictive control (MPC) is developed with position and speed as the feedback state variables. In addition, an extended state observer (ESO) is designed for the rejection of various disturbances, which are not involved in the control model and are regarded as the lumped disturbance to be estimated and compensated by the ESO. The experimental results show that, compared with the commonly used PPI controller (proportional position controller and proportional–integral speed controller), the proposed method enhances the position bandwidth and servo stiffness effectively.

Composite Sliding Mode Speed Control for Sinusoidal Doubly Salient Electromagnetic Machine Drives Using Fast Reaching Law and Disturbance Compensation

The proportional-integral speed controller is widely used in field-oriented control due to its simplicity in implementation; however, parameter variations and load disturbance easily lead to the deterioration of its dynamic performance. To address the above problem, a composite sliding mode speed control (CSMSC) is proposed in this article, which is composed of a sliding mode controller based on a new fast reaching law (FRL-SMC) and an extended state observer (ESO). The FRL-SMC can effectively solve the contradiction between response time and chattering amplitude, which is superior to the traditional SMC approaches; the lumped disturbance is estimated online by the ESO, and then the estimated value used as feedforward compensation is introduced into the FRL-SMC to enhance the disturbance reject ability. The sinusoidal doubly salient electromagnetic machine (SDSEM) speed regulation system applying the proposed CSMSC obtains a fast startup response and load step response, an excellent anti-disturbance performance, and a small <i>q</i>-axis current steady chattering. Finally, the effectiveness of the proposed method is verified by experimental results for a SDSEM test platform.

Wind Energy Conversion System Using Advanced Speed Control and Model-Based Loss Minimization

This paper presents a new optimization strategy for a stand-alone wind energy conversion system (WECS). The WECS is comprised of a variable-speed wind turbine (WT) with a vector-controlled self-excited induction generator (SEIG), a three-phase full-bridge converter, and a DC-bus containing the excitation capacitor, batteries, and a load. The control strategy incorporates an advanced model-based SEIG loss minimization and fuzzy-logic WT optimization. The latter utilizes a hedge-algebra speed controller to ensure fast response with practically no overshoot in the whole WT operating range, which cannot be achieved with the conventional proportional-integral (PI) controller. Consequently, the WT optimization time step is shortened and its convergence accelerated. The proposed SEIG loss minimization is based on the corresponding mathematical model that accounts for magnetic saturation and variable stray load and iron losses. Simultaneous optimization of the WT and SEIG is enabled, which results in greater total energy output compared to the successive WT-SEIG optimization. The proposed control strategy is run in real-time using the DS1103 board (dSpace) with a 1.5 kW SEIG driven by an emulated WT. It is experimentally evaluated over a wide WT operating range and compared with several competing strategies involving successive optimization, PI speed control and/or less elaborate SEIG models.

Designing practical fuzzy gain scheduling controllers for micromobility applications of permanent magnet synchronous machines

In micromobility applications, maintaining satisfactory motor drive performance in the full torque-speed envelope of an outer rotor non-salient permanent magnet synchronous machine is a challenge due to the drastic performance degradation with the increasing non-linearity above the nominal ratings of the motor. In this article, we tackle this challenge via fuzzy gain scheduling proportional–integral speed controllers that have been designed by taking into account practical considerations. On the basis of experimental voltage ripple analyses conducted on the speed control loop with different system characteristics, we develop a single-input fuzzy gain scheduling proportional–integral speed controller and a double-input fuzzy gain scheduling proportional–integral speed controller to reduce the voltage ripples while providing satisfactory dynamical performance. The proposed structures continuously adjust the characteristics of the speed control loop within a specified region to exhibit different dynamical system characteristics against varying conditions. It is verified by the experimental test results that the proposed structures successfully reduced the increasing voltage ripples as the disturbances increase while providing satisfactory dynamical performance. Finally, we provided a discussion on the trade-off between the proposed structures and suggested deploying single-input fuzzy gain scheduling proportional–integral controller for micromobility speed control applications as it is agnostic to noise to a certain degree hence offering better reliability.

Simulation model of proportional integral controller-PWM DC-DC power converter for DC motor using MATLAB

Smoothly speed range changing, easily speed controlling, and swiftly dynamic response for load torque changing are the main merits which are delivered by direct current (DC) motors. They are also distinguished by their versatility. All these characteristics make the DC motors suitable candidates for various applications. An accurate high-speed control with a good dynamic response, would be of demand for many applications of the DC motors. Controlling the speed of motors using conventional systems is one of the most important method that is adopted and it can be more efficient when used with electronic power devices to control the output voltage. Hence, this paper introduces an efficient proportional integral (PI) speed controller for DC motor fed by direct current-direct current (DC-DC) convertor, which is switched by pulse-width modulation technique. MATLAB/Simulink environment is used to build the whole system. Two operation scenarios have been conducted including constant load with variable speed and variable load with constant speed.

An optimal angle control strategy for switched reluctance motor drive in EV applications

In this study, a hybrid method of the Harris-Hawk optimisation method is used to simultaneously manage the speed of a switched reluctance motor and minimise the torque ripple. A proportional integral (PI) speed controller is used in the outer loop of the three-phase, six-phase switching reluctance motor, and a PI current controller is used in the inner loop. Turn-on and turn-off angles are also controlled. In order to decrease current parameter error measures, reduce torque ripples, and increase efficiency, the task of finding the turn-on and turn-off angles is treated as an optimisation problem. Using the suggested optimisation technique, a model with adjustable turn-on and turn-off angles under different load torques is produced. When contrasted to current optimisation methodologies, the suggested model is demonstrated to be efficient for torque ripple suppression and speed augmentation simultaneously.

Direct torque control based on second order sliding mode controller for three-level inverter-fed permanent magnet synchronous motor: comparative study

Introduction. The permanent magnet synchronous motor (PMSM) has occupied a large area in the industry because of various benefits such as its simple structure, reduced moment of inertia, and quick dynamic response. Several control techniques have been introduced for the control of the PMSM. The direct torque control strategy associated to three-level clamped neutral point inverter has been proven its effectiveness to solve problems of ripples in both electromagnetic torque and stator flux with regard to its significant advantages in terms of fast torque response. Purpose. The use of a proportional integral speed controller in the direct torque control model results in a loss of decoupling with regard to parameter fluctuations (such as a change in stator resistance value induced by an increase in motor temperature), which is a significant drawback for this method at high running speeds. Methods. That is way a second order sliding mode controller based on the super twisting algorithm (STA) was implemented instead of PI controller to achieve a decoupled control with higher performance and to insure stability while dealing with parameter changes and external disturbances. Results. The simulation results carried out using MATLAB/Simulink software show that the model of direct torque control based on a three-level inverter-fed permanent magnet synchronous motor drive has better performance with second order sliding mode speed controller than the proportional integral controller. Through the response characteristics we see greater performance in terms of response time and reference tracking without overshoots. Decoupling, stability, and convergence toward equilibrium are all guaranteed.

Hall sensor-based speed control of a 3-phase permanent-magnet synchronous motor using a field-oriented algorithm

To achieve optimum torque per amp, we retain the angle of the stator-current-vector with respect to the rotor-flux at 90 degrees, rather than controlling the amplitude of the stator-current-vector. Without or with the load torque, the proportional integral (PI) controller produced better results in the speed control loop. A controller is required to maintain a consistent speed and improve system performance as the load changes. This work develops an auto-tuning PI speed controller for 3-phase permanent-magn et synchronous motors using field oriented algorithm. The 3-phase voltage from the grid is converted to DC through a transformer and a grid-side rectifier. The DC voltage is converted back into AC through a machine-side inverter, which drives the motor with time-varying loud. The objective of field oriented control (FOC) in this work is to control the semiconductor switches in the machine-side power inverter to achieve the desired torque and flux. The stator-currents are measured and fed into the flux observer to obtain the direct-quadrature-zero (DQ-axis) current, the rotor magn etizing current, and the angle of the synchronously rotating reference frame. The results show that the motor's speed response has an earlier transient response and a less steady-state inaccuracy after tuning the controllers during acceleration and torque load adjustments.

Fuzzy logic direct torque control of induction motor for photovoltaic water pumping system

This study presents a fuzzy logic direct torque control for induction motor to be used in photovoltaic (PV) water pumping system. The system is intended to be less expensive and simple while maximizing PV array power utilization. For this purpose, a smart technology based on fuzzy logic controller (FLC) has been implemented to track the maximum power which has been successfully used in solar water pumping systems under different irradiance levels. Next, to alleviate the disadvantages of standard DTC, we chose fuzzy direct torque control (FDTC) for induction motors driving a centrifugal pump. Furthermore, this study includes the usage of IP with antiwindup and slide mode speed controller (SMC) instead of the traditional proportional-integral speed controller. Finally, the induction motor (IM) speed has been optimized with an optimum speed control in order to maximize the pump’s hydraulic parameters. The FDTC, with its SMC outperforms the photovoltaic pumping system (PVPS) in terms of dynamic performance and robustness. To develop a full simulation model of the proposed PVPS configuration under various climate conditions, MATLAB environment and associated Simulink are used.

Hybrid MPPT-based predictive speed control model for variable speed PMSG wind energy conversion systems

In this research, a predictive speed control (PSC) technique based on permanent magnet synchronous generators is proposed for variable-speed wind energy conversion systems (VS-WECS) (PMSG). The control approach that has been developed makes it possible to regulate mechanical and electrical variables concurrently within the context of a single cost function. The power converter will then use the optimum switching state that will result in the lowest possible cost function when it has been chosen. The maximum power point tracking (MPPT) algorithms used in the proposed control approach are combined in order to achieve optimum efficiency. As a direct result of this, the conventional cascade structure of proportional-integral (PI) controllers has been removed, which results in an improvement in the system's dynamic responsiveness. In addition, predictive current control, also known as PCC, is implemented on the grid-side converter, also known as the GSC, in order to accomplish decoupled grid current control. Using MATLAB/SIMULINK, we analyze the performance of the suggested control methods and compare it to the performance of a traditional PI speed controller. The findings demonstrated that the MPC controller is superior than the PI controller in terms of its ability to handle system dynamics.

Performance enhancement of direct torque control induction motor drive using space vector modulation strategy

Purpose. The main objective of this work is to demonstrate the advantages brought by the use of space vector modulation technique in the direct torque control of the induction motor. To achieve this purpose, two different direct torque control approaches (with space vector modulation) are proposed and studied from a comparative aspect with each other and with the conventional direct torque control. The novelty of this work consists in the employment of an Integral-Proportional (IP) speed controller in the two proposed direct torque control approaches and a more in-depth evaluation for their performance mainly the switching frequency of inverter semiconductor components and motor torque ripples. Methods. Two different direct torque control approaches that use the space vector modulation strategy and/or fuzzy-logic control, are described in detail and simulated with IP speed controller. The simulation experiments are carried out using Matlab/Simulink software and/or fuzzy-logic tools. Results. Practical value. Comparison results show that the two proposed direct torque control structures (with space vector modulation) exhibit a large reduction in torque ripples and can also avoid random variation problem of switching frequency (over a wide range of speed or torque control). On the other hand, the use of IP speed regulator ensured good dynamic performance for the drive system as well as considerably minimized peak overshoot in the speed response. Practically all of these benefits are achieved while retaining the simplicity and the best dynamic characteristics of the classical direct torque control, especially with the modified direct torque control approach in which the design or implementation requires minimal computational effort.

Sliding mode control with observer for permanent magnet synchronous machine drives

&lt;span lang="EN-US"&gt;This &lt;span&gt;paper aims to develop the sliding mode control (SMC) scheme in sensorless permanent magnet synchronous machine (PMSM) drives to replace conventional proportional integral (PI) speed control. The SMC is formulated based on the integral sliding surface of the speed error. And the error is corrected based on the concept of Lyapunov stability. The SMC is designed with the load torque observer so that the disturbance can be estimated as feedback to the controller. The vector control technique which is also known as field-oriented control (FOC) is also used to split the stator current into the magnetic field generating part which is the direct axis and the torque generating part which is the quadrature axis. This can be done by using Park and Clarke transformations. The performance of the proposed SMC is tested under changes in load-torque and without load for different speed commands. The results prove that the SMC produces robust performances under variations of speeds and load disturbances. The effectiveness of the proposed method is verified and simulated by using MATLAB/SIMULINK &lt;/span&gt;software.&lt;/span&gt;

Enhanced Intelligent Closed Loop Direct Torque and Flux Control of Induction Motor for Standalone Photovoltaic Water Pumping System

This paper aims to search for a high-performance low-cost standalone photovoltaic water pumping system (PVWPS) based on a three-phase induction motor (IM). In order to control the IM, a fuzzy direct torque control (FDTC) is proposed in this paper for overcoming the limitations of the conventional direct torque control (CDTC). In fact, the CDTC suffers from several problems such as torque ripples, current distortion, and switching frequency variations. These problems can be solved with the proposed FDTC. To ensure high performance of the PVWPS, the reference torque is generated using a fuzzy speed controller (FSC) instead of a conventional proportional integral speed controller. In order to extract the maximum amount of power, the proposed maximum power point tracking controller is based on variable step size perturb and observe to surmount the weakness of the conventional perturb and observe technique. The performance of the proposed FDTC based on the FSC under variable climatic conditions is demonstrated by digital simulation using Matlab/Simulink. The obtained results show the effectiveness of the suggested FDTC based on the FSC compared with the CDTC in terms of pumped water, reduction in flux and torque ripple, diminution of losses, and decrease in the stator current harmonic.

Nonlinear speed tracking control of PMSM servo system: A global robust output regulation approach

It is well known that load torque disturbance and parametric uncertainties commonly exist in permanent magnet synchronous motor (PMSM) and may reduce the tracking accuracy especially when the reference trajectory is time-varying. Thus it is challenging to achieve precise speed tracking control with both load torque disturbance and parametric uncertainties being taken into account. This task can be formulated as a global robust output regulation problem (GRORP) of multi-input, multi-output nonlinear system. In this paper, a systematic internal model control (IMC) method is proposed to solve the GRORP. By constructing a suitable internal model, we convert the GRORP into a global stabilization problem of an augmented system, and then design a stabilization controller to globally stabilize the augmented system. To validate the advantages of the proposed IMC method, comparative studies with conventional proportional–integral speed control method and linear active disturbance rejection control method are conducted via simulations and experiments. It is worthy of mentioning that our method can not only achieve high precision speed tracking performance under time-varying reference speed and/or load torque disturbance, but also allow all the motor parameters to be uncertain.

Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles.

Safe path planning for obstacle avoidance in autonomous vehicles has been developed. Based on the Rapidly Exploring Random Trees (RRT) algorithm, an improved algorithm integrating path pruning, smoothing, and optimization with geometric collision detection is shown to improve planning efficiency. Path pruning, a prerequisite to path smoothing, is performed to remove the redundant points generated by the random trees for a new path, without colliding with the obstacles. Path smoothing is performed to modify the path so that it becomes continuously differentiable with curvature implementable by the vehicle. Optimization is performed to select a “near”-optimal path of the shortest distance among the feasible paths for motion efficiency. In the experimental verification, both a pure pursuit steering controller and a proportional–integral speed controller are applied to keep an autonomous vehicle tracking the planned path predicted by the improved RRT algorithm. It is shown that the vehicle can successfully track the path efficiently and reach the destination safely, with an average tracking control deviation of 5.2% of the vehicle width. The path planning is also applied to lane changes, and the average deviation from the lane during and after lane changes remains within 8.3% of the vehicle width.

Controlling of Induction Motor Using Grey Wolf Optimization Algorithm

This paper introduces the improved Direct Torque Control (DTC) of the Induction Motor (IM) to enhance its performance. The DTC method is generally used to control electrical machinery. The traditional Proportional Integral (PI) speed controller parameters are manually adjusted to match the speed with the given reference. However, traditional PI has a drawback such that it does not fit all error limits. Thus, the intelligent DTC has been discussed with the proposed Grey Wolf (GWO). The grey wolf algorithm is used to adjust PI speed controller parameters as well the results are compared with those of genetic algorithm. Simulation results show that the GWO algorithm is exceptionally successful for improving induction motor with a fast-tracking response.

Speed Control of Permanent Magnet Synchronous Motor With Uncertain Parameters and Unknown Disturbance

Control of the speed as well as shaping the speed transient response of a surface-mounted permanent magnet synchronous motor (PMSM) is achieved using the method of feedback linearization and extended high-gain observer. To recover the performance of feedback linearization, an extended high-gain observer is utilized to estimate both the speed of the motor and the disturbance present in the system. The observer is designed based on a reduced model of the PMSM, which is realized through the application of singular perturbation theory. The motor parameters are assumed uncertain and we only assume knowledge of their nominal values. The external load torque is also assumed to be unknown and time-varying, but bounded. Stability analysis of the output feedback system is given. Experimental results confirm the performance and robustness of the proposed controller and compare it to the cascaded proportional integral (PI) speed controller.