Design of a Speed Sensorless Control System on a DC Motor using a PID Controller

This paper presents a novel design using fuzzy logic control and phase-locked loops to obtain a DC motor speed control system with excellent regulation and high robustness. The fuzzy logic controller is incorporated in order to achieve quick control of motor speed smoothly. The fuzzy logic controller enhances the robustness of the motor control system, which can handle abrupt load variation and exhibits good disturbance behavior. The PLL becomes effective at steady-state conditions when the speed error is small. A control scheme using fuzzy control of DC motor speed with extremely accuracy provided by PLL is implemented. Simulation demonstrates the effectiveness of the proposed scheme. Test results show that a system which consists of both fuzzy control and PLL can yield a high performance DC motor speed control system.

Surface mobility control is a fundamental challenge in robotics, and its applications range from autonomous vehicles to industrial automation. The main aim of the paper is to analyze the PID controller parameters for the speed control of a surface mobility platform mobile robot. MATLAB simulation toolbox and mathematical model of the DC motor are used to find the optimal PID controller parameters to complete the DC motor speed control system. For the SMP motion control system, the mobile robot kinematic model is supported as a differential drive system. In this paper, the PID controller parameters for the DC motor control system are analyzed with simulation results using various KP, KI, KD gains. The experimental results of the SMP mobile robot with optimal PID controller parameters are analyzed by driving on the rough, slope and even terrains. According to simulation results and experimental tests, the proposed system effectively controls the speed of the SMP mobile robot, demonstrating satisfactory performance in settling time, rise time, and system overshoot. Among PI and PID controllers, the designed PID controller can quickly control to reach the desired DC motor speed. Using the optimal PID coefficient parameters, all motors reached their desired speed in 0.12 seconds during simulations. In the experimental tests on various terrain (even, slope and rough), all motors achieved their desired speed simultaneously within 25 seconds.Keywords: Differential drive, PID controller, motion trajectory, real-time speed control. skid steering, SMP mobile robot, surface mobility control

The traditional DC double-loop speed control can not effectively overcome non-linear factors; it can not meet the needs of high-precision, high-performance requirements. This paper shows that the Fuzzy Self-Tuning PID Control strategy has been used in DC motor speed control systems to achieve real-time tuning PID parameters and introduces the entire design process of the controller. When referencing an actual motor parameter model a simulation model established by Matlab / Simulink, simulation results show that the Fuzzy Self-Tuning PID Controller is superior to the traditional PID control with its accuracy and robustness, thus enhancing its motor dynamics and static performance. From this it is seen that simulation results are concurrent with theoretical research, by verifying the reasonableness of program design, while it achieves an optimum control of control objectives.

PID controller is widely used in industry field, but when the industry presence exists noise interference, it is difficult for the conventional PID controller to achieve the expected control effect, in view of this situation, the method of combinating Kalman filter with the PID control is studied in this paper, the DC motor speed control system is simulated, the results shows that the PID controller based on Kalman filter is better to inhibit the effect of white noise, and it has a good dynamic response characteristics.

Experience Mapping based Prediction Controller (EMPC) is a recently proposed controller for DC motor based position control, whose design is inspired from human motor control. As it is developed for a Type-1 system, the algorithms developed there, cannot be directly used for Type-0 systems. This paper presents the modified EMPC for Type-0 systems and the principle is applied to a DC motor speed control system. EMPC uses past experience for generating the control action in each scenario and it works in quasi-open-loop unlike conventional control systems which work in tight close loop. The paper presents the details of development of EMPC algorithm and simulations to show its performance on a DC motor based speed controller. The performance of EMPC is compared with that of a conventional PID controller for different scenarios. The speed control of DC motor using EMPC is practically implemented and the experimental results are presented.

DC motors are the most widely used electrical motors since their ease of use. Controlling a DC motor can be done by adjusting amount of voltage and current supplied to the motor. In this design the controlling is done using proportional integral derivative (PID) control, applied for movement in XY plane. Ziegler-Nichols method is used to determine PID constants. A Raspberry Pi is used to receive and process input from the user through a graphical user interface (GUI). The data input consists of two values, i.e. position and velocity. The GUI also shows the actual coordinate position on the screen. Two motors are controlled simultaneously by the Raspberry Pi through serial peripheral interface (SPI) with one microcontroller for each motor axis. The program contains a PID control algorithm to stabilize the motor speed. The coordination of the two stabilized motor speed is used to draw a sloping line. Sloping lines are drawn in order to determine the performance of the PID controller.

The stability of the system is the main objective for Control System Design criteria. PID control with closed loop system is the one of control which can improve the stability of the system from disturbance effect. In this study, DC Motor Speed Control is designed with PID LabVIEW 2010 Software and Proximity Sensor as a closed loop feedback. The system allows the operator to control speed of DC Motor from LabVIEW front panel which automatically stabilized when load ?which usually slow down the speed of DC Motor, applied. PID LabVIEW 2010 generates voltage output 0-5Vdc and drives DC Motor through analog output channel from NIDAQ 600, which received by Non-Inverting Amplifier and amplified to 0-12Vdc output. PID Control with Closed Loop system may dampen the speed response second order of DC Motor to have value of overshoot number ? 0 with steady state error of ?2%. The system feedback can stabilize this condition from outside interference. The result of this speed control system has success criteria of overshoot (Mp) = 0 and Error Steady State (Ess) = 0.82%.

This study presents the design and development of a tire tread with a brushless DC (BLDC) motor speed control and monitoring system for an unmanned ground vehicle (UGV) in mining applications. By providing precise speed control and real-time monitoring of the motor's operating parameters, the proposed system seeks to enhance the performance of UGVs used in mining operations. A BLDC motor, a motor controller, and a monitoring system that captures data on the motor's speed, temperature, and voltage are incorporated into the tire tread design. The data is wirelessly transmitted to a central control system, enabling operators to monitor the UGV's performance and make informed maintenance and operation decisions. Experiment results demonstrate the efficacy of the proposed system in enhancing the performance and safety of UGVs on mining sites, highlighting the system's potential for utilization in other industries.

This study presents the application of the aquila optimizer (AO) algorithm to determine the parameters of the proportional integral derivative (PID) controller to control the speed of a dc motor. The AO method is inspired by the most popular bird of prey in the northern hemisphere named Aquila. Initially, the proposed AO algorithm is applied to unimodal and multimodal benchmark optimization problems. To get the performance of the AO method, the controller is compared with other methods, namely Seagull optimization algorithm (SOA), marine predators algorithm, giza pyramids construction (GPC), and chimp optimization algorithm (ChOA). The results represent that the AO is promising and shows the effectiveness. Determination of PID parameters using the AO method for dc motor speed control system shows superior performance.

The Loss-Free resistor (LFR) is applied to DC motor speed control system. A compensation Control algorithm based on LFR is proposed. The LFR is realized by means of switching network whose characteristics are nonlinear, thus, a neural network was designed and used. The switching on-off time can be instantaneously calculated by using the Neural-network-based algorithm proposed. The varies of the motor speed is realized by controlling the output of the LFR, the energy loss in the system is reduced compared with using a conventional power amplifier, and the dynamic characteristics of the system are also improved. The validation of the simulation results is proposed as well.

The brushless DC motor (BLDCM) speed control system has various kinds of uncertainties, such as reference speed mutation, noise and parameters change, etc. However, proportional integral (PI) control method used widely cannot handle the uncertainties in the control system well. A novel discrete adaptive control with Multiple-Step-Guess (MSG) estimation for BLDCM speed control system is proposed in this contribution. MSG estimation is firstly developed and applied in BLDCM speed control system, which estimate the BLDCM model parameters online with only five steps history information sampled from the input signal and output signal. The tracking adaptive control law is designed to ensure the speed can track reference speed rapidly and accurately. Compared with PI control and recursive least square adaptive control (RLSAC), extensive simulations verify that the BLDCM speed response under MSG adaptive control (MSGAC) has better dynamic and steady state performance in the case of reference speed mutation and BLDCM parameters change. Simulation results illustrate that the novel proposed method is effective and robust for uncertainties of BLDCM speed control system.

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.

The main objective of this paper is to control the speed of separately excited DC Motor using a Sliding mode controller based on VSS approach. This controller is based on variable structure systems which aim at reducing the peak overshoot, steady state error and settling time of a DC Motor. In the first stage, PI controller is used to control the speed of DC Motor. A model is developed and simulated using MATLAB/SIMULINK. Later on the same is done with sliding mode controller. The speed control of DC Motor using both PI and Sliding mode controllers is studied and the results are compared. The simulation results show that Sliding mode controller is superior than PI for speed control of DC motor. Since the SMC is robust in presence of disturbances, the desired speed is perfectly tracked.

PurposeThe principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.Design/methodology/approachIn order to regulate the current and speed of the motor, the Multi-resolution PID (MRPID) controller is proposed. The altered Landsman converter is utilized in this proposed suppression circuit, and the obligation cycle is acclimated to acquire the ideal DC-bus voltage dependent on the speed of the BLDC motor. The adaptive neuro-fuzzy inference system-elephant herding optimization (ANFIS-EHO) calculation mirrors the conduct of the procreant framework in families.FindingsBrushless DC motor's dynamic properties are created, noticed and examined by MATLAB/Simulink model. The performance will be compared with existing genetic algorithms.Originality/valueThe presented approach and performance will be compared with existing genetic algorithms and optimization of different structure of BLDC motor.

Pulse width modulation (PWM) is used to generate pulses with variable duty cycle rate. The rapid rising and falling edges of PWM signal minimises the switching transition time and the associated switching losses. This paper presents a DC motor speed controller system using PWM technique. The PWM duty cycle is used to vary the speed of the motor by controlling the motor terminal voltage.The motor voltage and revolutions per minutes (RPM) obtained at different duty cycle rates. As the duty cycle increases, more voltage is applied to the motor. This contributes to the stronger magnetic flux inside the armature windings and the increasethe RPM. The characteristics and performance of the DC motor speed control system was investigated. In this paper, a PIC microcontroller and a DC-DC buck converter are employed in the DC motor speed controller system circuit. The microcontroller provides flexibility to the circuit by incorporating two push button switches in order to increase and to decrease the duty cycle rate. The characteristics and performance of the motor speed controller system using microcontroller was examined at different duty cycle rate ranging from 19% to 99%.