An adaptive, robust control of DC motor using fuzzy-PID controller

The control of DC motor system is difficult and mathematically tedious due to their high non linearity property.To overcome this difficulty, a new approach has been required.This paper presented a systematic procedure to develop PI based speed controller for DC motor.The designing of speed controller through state estimation approaches.The optimal parameter of PI controller is finding out by using PSO algorithms.The performances and characteristics of DC motor are observed.The simulation results verify that steady state error is reduced, the rising time is improved and the disturbances affect is reduced hence the better performances of DC motor.

Sliding mode control with higher order strategy for buck converter in the presence of dynamic load

To precisely control the speed of BLDC motors at high speed and with very good performance, an accurate motor model is required. As a result, the controller design can play an important role in the effectiveness of the system. The classic controllers such as PID are widely used in the BLDC motor controllers, but they are not appropriate due to non-linear model of the BLDC motor. To enhance the performance and speed of response, many studies were taken to improve the adjusting methods of PID controller gains by using fuzzy logic. Use of fuzzy logic considering approximately interpretation of the observations and determination of the approximate commands, provides a good platform for designing intelligent robust controller. Nowadays type-2 fuzzy logic is used because of more ability to model and reduce uncertainty effects in rule-based fuzzy systems. In this paper, an interval type-2 fuzzy logic-based proportional-integral-derivative controller (IT2FLPIDC) is proposed for speed control of brushless DC (BLDC) motor. The proposed controller performance is compared with the conventional PID and type-1 fuzzy logic-based PID controllers, respectively in MATLAB/Simulink environment. Simulation results show the superior IT2FLPIDC performance than two other ones.

Abstract- This paper introduces a linear structure of wind turbine, operator and the pitch angle controller. Then, a new method of adaptive fuzzy on the variable speed wind turbines was provided and it was compared with PID and Fuzzy Logic Control ler and the simulation results were analyzed. So when the results of each simulation using PID and Fuzzy controllers and adaptive fuzzy PID controllers provided, the observed advantages and disadvantages of the rotor speed and wind turbine power can be introduced. It can be seen that in PID method the high overshoot is discussed as a disadvantage while it is overcome by using fuzzy controller and overshoot will decrease. The time of reaching to a sustained speed increases slightly and in adaptive fuzzy PID controller, the less overshoot has provided a good and effective performance for system response. The use of adaptive fuzzy PID controller causes the system does not have any steady-state error and at all moments of time, the response rate is better than PID and fuzzy controller. The importance of the amount of overshoot and rate fluctuations is that by reducing these parameters in addition to reducing the cost of preventive care, maintenance and depreciation, the fluctuations in electricity generated by induction generator also greatly reduced.

The Direct current motors are in different types and there are several methods for controlling of their speed. In this paper two ways for speed controlling suggested. First a fuzzy logic speed controller for DC motor is designed and it’s parameter calculated by Particle Sward Optimization (PSO). The speed controller designed according to fuzzy rules, then for having better performance, the controller optimized with PSO. Secondly a PID controller that it’s parameter find by PSO, is used for speed controlling of a DC motor. At the end the performance of fuzzy logic controller compared with PID controller. The results show that fuzzy-PSO controller has better performance.

Adaptive control of DC motor using bacterial foraging algorithm

In present scenario, various industrial, agricultural, transport and domestic resources have validated the diverse application of electric drives. The efficiency of the industry is increased by selectively regulating the operation of electric drives. The dc motor plays a significant role in modern industrial drives due to its higher performance, reliability, adjustable speed control etc. The speed control of separately excited dc motor is carried out by varying the armature voltage for below rated speed. A speed control methodology by varying the armature voltage using a buck converter is presented in this paper. The controller used in this methodology is proportional-integral type. Using this controller, the fast correction is performed by the proportional term and the integral term makes the steady state zero in finite time frame. A MATLAB simulation is performed for automatic control of dc motor using PI controller and buck chopper in a close loop. In addition to this, an antiwind up system is incorporated in the simulation to enhance the rate of speed control in the model.

For many years, the programmable positioners have been widely applied in structures of modern electro-pneumatic final control elements. The positioner consists of an electro-pneumatic transducer, embedded controller, and measuring instrumentation. Electro-pneumatic transducers that are used in positioners are characterized by a relatively short mean time-to-failure. The practical and economical method of a reasonable prolongation of this time is proposed in this paper. It is principally based on assessment and minimizing the effort of the embedded controller. For this purpose, some measures were introduced: The control value variability, mean-time, and the cumulative controller’s effort. The diminishing of controller effort has significant practical repercussions because it reduces the intensity of mechanical wear of the final control element components. On the other hand, the reduction of the cumulative effort is important in the context of process economy due to limitation of the consumption of energy of compressed air supplying the final control element. Therefore, the minimization of control effort indicators has an impact on the increase of the functional safety and economics of the controlled process. The simulations were performed in the Matlab-Simulink environment with the use of the liquid level control system in which a phenomenological model of a final control element was deployed. As a result of the performed simulations, the recommendations regarding the selection of the structure of positioner controller were elaborated.

–This paper designs the high-efficiency and the low-cost drive system of the small-size electric vehicles (EVs). The power circuit for driving the dc motor is designed by considering both the cost and efficiency. In order to reduce the conduction loss of MOTFET and diode for controlling an armature voltage, some MOSFETs and diodes at the armature are in parallel connection. An operating sequence for both the field current and the armature voltage according to the accelerator pedal angle is suggested for changing smoothly the rotating direction of dc motor. Through the simulation studies, the performances of the proposed methods are verified. Keywords: Electric vehicle, conduction loss, buck converter, switching loss, DC motor 1. Introduction Recently, because environmental pollution and the energy crisis are rising globally, electric vehicles (EVs) are promising instead of traditional gasoline vehicles. As the EVs are driven by electricity stored in a battery, they still suffer from the main problem as short driving range due to the low energy content of the batteries. As how to use the battery’s energy efficiently is a hot issue for developing EVs, it is important to design the drive system of a traction motor with high efficiency. Selection of traction motors for propulsion system is very important step that requires special attention. In fact, the choice of electric-propulsion systems for EVs mostly depends on three factors: efficiency, cost, and reliability. In an industrial point of view, the major types of electric motors adapted or under serious consideration for EVs include the dc motor, an induction motor (IM), and brushless DC (BLDC) motor. The BLDC motor has been widely used in the EVs, because it provides high power density, and has higher efficiency than induction motor [1]-[3]. By the way, in order to drive the BLDC motor, the 3-phase PWM inverter and complex control system are required [4]. Recently, the price of PM has been dramatically raised. They cause the increase of the manufacturing cost of the EVs. The small-size EVs such as the golf car and scooters require the simple propulsion system in order to reduce the manufacturing cost. Although a brushed dc motor has some problems such as requirement of maintaining both the brush and commutation, it has some advantages like a simple drive system and high starting torque. Thus, the dc motor as the traction motor is more suitable at the low cost small-size EVs [5]. In this paper, the power circuit for driving the dc motors is designed by considering both the cost and efficiency. In order to reduce the conduction loss of MOTFET and diode for controlling an armature voltage, some MOSFETs and diodes at the armature are in parallel connection. An algorithm to change smoothly the rotating direction of the motor is suggested. In order to verify the performances of proposed methods, some simulation studies are carried out.

The main focus of this paper is to do stability analysis of a DC Motor (Field controlled and armature controlled). The stability analysis includes time domain analysis, frequency domain analysis and pole-zero domain analysis using state space averaging technique. The simulation and study is done using Matlab from its respective graphs obtained from above mentioned domains. Later the control of this motor is done using advanced controllers such as Fuzzy and Genetic algorithm optimization techniques.

This paper presents an improved emotional controller for brushless DC motor (BLDC) drive. The proposed controller is called brain emotional learning based intelligent controller (BELBIC). The utilization of the new controller is based on the emotion processing mechanism in brain. This intelligent control is inspired by the limbic system of mammalian brain, especially amygdala. The controller is successfully implemented in simulation using MATLAB software, brushless dc drive with trapezoidal back-emf. In this work, a novel and simple implementation of BLDC motor drive system is achieved by using the intelligent controller, which controls the motor speed accurately. This emotional intelligent controller has simple structure with high auto learning feature. Simulation results show that both accurate steady state and fast transient speed responses can be achieved in wide range of speed from 20 to 300 [rpm]. Moreover, for evaluate this emotional controller and hence to assess the effectiveness and control capability of the proposed BELBIC scheme, the performances of proposed control scheme are compared with a conventional PID controller for the BLDC drive control, in simulation different conditions. This is shown proper operating than the PID controller. And also shows excellent promise for industrial scale utilization.

High efficiency due to reduced losses, low maintenance and low rotor inertia of the brushless dc (BLDC) motor have increased the demand of BLDC motors in high power servo and robotic applications. Since fuzzy logic with human like but systematic property can convert the linguistic control rules based on expert knowledge into automatic control strategy, it can be well applied to control the systems with uncertain or unmodelled dynamics. In view of fuzzy logic merits, this paper proposes three types of fuzzy logic controllers for BLDC motor drive using advanced simulation model and presents a comparative study of performance specifications of classical PI and PID controllers and three fuzzy logic controllers. The three fuzzy logic controllers considered are PI-like fuzzy logic controller (PI-Like FLC), Hybrid fuzzy logic controller (HFLC) and integrated fuzzy logic controller (IFLC). The steady state and dynamic characteristics of speed and torque are effectively monitored and analyzed using the proposed model. The aim of fuzzy logic controllers is to obtain improved performance in terms of disturbance rejection or parameter variation than obtained using classical controllers. In the HFLC, the proportional term of the traditional PID controller is replaced with an incremental fuzzy logic controller. For the PI-Like FLC, the output of the controller is modified by a rule base with the error and change of error of the controlled variable as the inputs. The IFLC is constructed by using Fuzzy logic controller and PID controller. A performance comparison of classical and fuzzy logic controllers has been carried out by several simulations at different speeds and different load conditions.

This paper presents a study on the speed tracking control of DC Motor that is develop by using an Adaptive Proportional-Integral-Derivative (APID) control structure. APID controller is used due to the ability to solve the drawback of conventional PID controller. DC motor system and proposed controller was simulated using MATLAB-Simulink software. Several tests such as step function, sine wave function and saw tooth function were used to examine the performance of the proposed controller. Several speeds input was used to evaluate the performance of APID controller. The result show that the proposed control structure can achieve targeted speed control with a good response. The DC Motor test rig are used to investigate in real time experiment for the ability of the proposed controller structure by comparing simulation APID with experiment APID controller. The result show that the proposed control structure proves to be able to track the desire speed with acceptable error.

Two-way shear failure of slabs is a sudden one, which has catastrophic outcomes. Slabs with large spans may be subjected to in-plane tensile forces due to thermal or earthquake loading. There is a lack of agreement between various design codes regarding the significance of in-plane tensile forces on the two-way shear strength. Two-way shear failure of slabs is a sudden one, which has catastrophic outcomes. Slabs with large dimensions may be subjected to in-plane tensile forces due to restraint or earthquake loading. There is a lack of agreement between various design codes regarding the significance of in-plane tensile forces on the two-way shear strength. The purpose of this study is to explore, propose a simplified two-way shear strength model, which includes the effect of in-plane tensile forces on the strength. A review for the experimental investigations, existing models, design codes for two-way shear of slabs is presented, with emphasis on in-plane tensile forces. The loading method used in the current experimental testing is misleading, where the two-way shear and the in-plane forces are independent. A comparative study was conducted between the existing formula and design codes for this case. The comparison between different codes with the experimental results show that the new proposed Eurocode design code was found to be the most accurate one. However, it did not include the effect of the in-plane tensile forces in a physically sound manner. In addition, more full testing of concrete slabs under combined two-way shear and tensile forces are required to refine this existing two-way shear design code provisions or develop new formulas or mechanical models.

This paper was written to demonstrate importance of a fuzzy logic controller in act over conventional methods with the help of an experimental model. Also, an efficient simulation model for fuzzy logic controlled DC motor drives using Matlab/Simulink is presented. The design and real-time implementation on a microcontroller presented. The scope of this paper is to apply direct digital control technique in position control system. Two types of controller namely PID and fuzzy logic controller will be used to control the output response. The performance of the designed fuzzy and classic PID position controllers for DC motor is compared and investigated. Digital signal Microcontroller ATMega16 is also tested to control the position of DC motor. Finally, the result shows that the fuzzy logic approach has minimum overshoot, and minimum transient and steady state parameters, which shows the more effectiveness and efficiency of FLC than conventional PID model to control the position of the motor. Conventional controllers have poorer performances due to the non-linear features of DC motors like saturation and friction. DOI: http://dx.doi.org/10.11591/ij-ai.v1i1.409