Development of practical application for sensorless crane control system

This study proposes a high-performance sensorless interior permanent-magnet synchronous motor control system using a high-frequency injection technique. A new estimation method that uses both the high-frequency d-axis current and q-axis current to estimate the rotor position is investigated. By using the proposed method, the hypothesis-synchronisation signal used in the conventional high-frequency injection method can be eliminated. A 1.25 kHz, 15 V, sinusoidal waveform voltage is injected into the d-axis synchronous frame of the motor and then the high-frequency d-axis and q-axis currents can be measured to determine the rotor position of the motor. In addition, a new compensation method is developed to reduce the estimation position error because of the mutual inductance and saturation effect of the motor. By using this new method, the estimated rotor-position error is within ±2 electrical degrees. A digital signal processor, TMS-320-F2812, is used as the estimating and control centre. The experimental results show that the proposed method can be applied in both a sensorless speed control system and a sensorless position control system. The sensorless speed control system has fast response, good load disturbance response and good tracking response.

This paper develops the brushless dc (BLDC) motor sensorless control system for an drilling dig system in shale gas development. The sensorless techniques that are based on a hysteresis comparator and inductance method with a high starting torque are suggested. Combined with the application of drilling rig system, analyzed the performance requirements of brushless DC motors (BLDCM) in the fields of low speed, and discussed the control method of the dr sensorless BLDCM, developed an prototype of sensorless BLDCM control system based on dsPIC33FJ32MC204. Started the motor in closed-loop mode by using inductance method and BEMF zero crossing detecting method, the motor speed range was effectively expanded. The experimental results showed that this control system could meet the requirements of low speed drilling dig and had application value.

An error correcting technique of an estimated position angle and rotating speed for the sensorless controlled salient-pole brushless DC motor drives is proposed. An unsymmetrical construction based on the mechanical or magnetic tolerance on the brushless DC motor appears as a modeling error of the motor. This error causes an estimating error which changes periodically. It is difficult to correct the error with hardware like filters. Then, a neuro-like fuzzy technique can he applied to correct the error of the estimated position angle. The position angle is estimated by a new AC current injection method. The errors of the estimated values change periodically, and unexpected cyclic speed errors generate when the motor is controlled as a speed servo system. The fuzzy model which estimates these errors is learned with a back propagation method which uses the cyclic errors as a teacher signal. Then, the system corrects the estimated position angles with the estimated error. The experimental results of the estimated position angle or speed are shown in the paper. From these results, the proposed sensorless control system could estimate more accurate position angle than conventional systems could.

Left ventricular assist devices (LVADs) are mechanical pumps, which can be used to support heart failure (HF) patients as bridge to transplant and destination therapy. To automatically adjust the LVAD speed, a physiological control system needs to be designed to respond to variations of patient hemodynamics across a variety of clinical scenarios. These control systems require pressure feedback signals from the cardiovascular system. However, there are no suitable long-term implantable sensors available. In this study, a novel real-time deep convolutional neural network (CNN) for estimation of preload based on the LVAD flow was proposed. A new sensorless adaptive physiological control system for an LVAD pump was developed using the full dynamic form of model free adaptive control (FFDL-MFAC) and the proposed preload estimator to maintain the patient conditions in safe physiological ranges. The CNN model for preload estimation was trained and evaluated through 10-fold cross validation on 100 different patient conditions and the proposed sensorless control system was assessed on a new testing set of 30 different patient conditions across six different patient scenarios. The proposed preload estimator was extremely accurate with a correlation coefficient of 0.97, root mean squared error of 0.84 mmHg, reproducibility coefficient of 1.56 mmHg, coefficient of variation of 14.44%, and bias of 0.29 mmHg for the testing dataset. The results also indicate that the proposed sensorless physiological controller works similarly to the preload-based physiological control system for LVAD using measured preload to prevent ventricular suction and pulmonary congestion. This study shows that the LVADs can respond appropriately to changing patient states and physiological demands without the need for additional pressure or flow measurements.

This paper presents a simulation method of modularization design for brushless DC motors (BLDCM). Based on the mathematical model of BLDCM, some isolated functional blocks, including BLDCM body block, speed PI controller block, current hysteresis controller block, current reference block, inverter block and commutation logic block, have been modeled in Matlab/Simulink. By the organic combination of these blocks, the simulation model of control system for BLDCM has been established. Additionally, some simulation works such as current waveform, back EMF waveform, torque curve and rotor speed curve have been done in this study. The simulation results indicate that the established model based on the new method proposed in this study has a good response to the rotor speed and torque, and possesses quick simulation pace, which offers foundation for the design of actual motor control system.These instructions give you the basic guidelines for preparing papers for IEEE 2008 ICAL conference proceedings.

This article presents a Permanent Magnet Synchronous Motor (PMSM) sensorless control system using backstepping control. The Extended State Observer (ESO) is also used to perform the sensorless control, and to estimate the load torque which is considered an external disturbance of the control system. Starting from the classic Field Oriented Control (FOC) type PMSM control structure, the classic PI speed and current controllers i <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> , i <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</sub> are replaced by a backstepping control structure. The main blocks used for the implementation and numerical simulation in the Matlab/Simulink graphical programming environment are presented. The very good static and dynamic performance obtained through numerical simulations even at high speeds, step variations of the value of the load torque, uniformly distributed noise, and variations of the PSMS nominal parameters can be explained by the fact that the backstepping control is applied to the non-linear system of the PMSM and by the step-by-step method of achieving each iqref, ud and uq control by using a Lyapunov-type function. Future articles propose the approach of real-time implementation of the PMSM sensorless control by using the backstepping control.

The paper describes the voltage control technique of induction machines supplied by a current source inverter. The control system is based on proposed new multi‐scalar variables, which are named “r.” The control system contains the output filter capacitor's model. In the sensorless control system the Z type backstepping speed observer was applied. The mathematical dependences are confirmed by simulation and experimental research.

Brushless DC Motor is a kind of a new motor which commutation signals replaces traditional motor mechanical structure with electronic signals. Square wave brushless DC motor can be divided into sensor motor and sensorless motor. Position sensor will increase system cost, motor size and maintenance difficulty, which bring about limitation and limits to promote its application in all areas. This project designs sensorless BLDC Motor control system with the core of the stm32 micro-controller and uses Back-EMF zero-crossing detection method. In the system designing software control algorithm, drawing schematic diagram of hardware and making PCB board have been completed dependently. The experimental results show that the system can well realize the starting and running of sensorless BLDC Motor control system, and have a good measure of protection.

The trial stereovision is manufactured which is a non-contact sensor and tried to control the overhead crane by visual feedback. The stereovision has four degree of freedom for tracking and gazing with two cameras. The three-dimensional position of the crane load is provided with image data of two cameras, the focus distance, and four-vision drive angles and is used for crane control. The desired angles to control the stereovision is obtained using inverse kinematics that a point of intersection of two camera optical axes seems to always accord with the crane load center. On the other hand, in the overhead crane, positioning and vibration suppression of the crane load are controlled, using three-dimensional position of the crane load measured by the stereovision. The overhead crane load is transported by the simultaneous traveling, traversing and hoisting motions of the trolley and swings with the vibrating amplitude and its direction. Therefore the dynamic overhead crane model has five degree of freedom. Variable feedback digital gains of the trolley to control the crane load are pursued in consideration of the rope length change. Experimental results of the positioning and swing control of the crane load and tracking of the stereovision in case of the load transportation with up and down hoisting are reported, and the possibility of zoom lens activity is described. The experimental results of overhead crane control by visual feedback show that the control system was effective

This study is focused on very low speed performance comparison between two sensorless control systems based on the novel `active flux` concept, that is, the current/voltage vector control versus direct torque and flux control (DTFC) for interior permanent magnet synchronous motor (IPMSM) drives with space vector modulation (SVM), without signal injection. The active flux, defined as the flux that multiplies iq current in the dq -model torque expression of all ac machines, is easily obtained from the stator-flux vector and has the rotor position orientation. Therefore notable simplification in the rotor position and speed estimation is obtained. For IPMSM, a stator-flux observer is employed based on combined current and voltage models, with speed-dependent smooth transition between them using a PI compensator of flux error. Comparative experimental results using both sensorless control systems are presented to verify the principles and to demonstrate the effectiveness of the active flux observer at very low speeds from 20 to 2 rpm (1 0.1 Hz).

This article presents a sensorless control system based on back-EMF (back electromotive force)sliding mode observer for control of rigid coupling of PMSM multi-motors. The back-EMF $\mathrm{e}_{\alpha}$ and $\mathrm{e}_{\beta}$ are provided by a sliding mode observer in order to estimate the rotor speed and position. The main advantage of the sensorless control consists in eliminating the speed transducers thus contributing to the increased reliability of the entire system. The control structure presented is cascaded, following the FOC (Field Oriented Control)principles, where the inner current loop has the reference I d set to be equal to zero, and the Iq reference is set by the PI-type speed controller in the outer loop. Considering that the load torque distributed to the two motors can be balanced or unbalanced, the main task of the multi-motor PMSM sensorless control system is to maintain the same speed of the slave system and the master system and that both systems match the required speed profile. Real time implementation of the multi-motor PMSM sensorless control system is recommended by the good results obtained from numerical simulations.

This paper proposes a method for improving the performance of a position sensorless control system for a slotless surface permanent magnet synchronous motor (SPMSM) in a very low-speed region. In position sensorless control based on a motor model, accurate motor parameters are required because parameter errors would affect position estimation accuracy. Therefore, online parameter identification is used. The error between the reference voltage and the voltage applied to the motor is compensated to ensure accuracy and stability of the sensorless control system. In this study, two voltage error compensation methods are used: compensation method 1, which is the conventional method and compensation method 2, which is the proposed method. In the proposed method, online parameter identification and compensation method 2 are used. The proposed method is evaluated by experimental results.

In this paper, a novel sensorless control structure based on multi-scalar variables is proposed. The static feedback control law is obtained by using the multi-scalar variables transformation, where the multi-scalar variables approach allows a full linearization of the nonlinear system. The control system could be described as “optimized” because of the minimized number of controllers. Furthermore, control system is divided into two independent control systems which are synchronized by additional controllers. The first control system is responsible for the generation of the 1st fundamental harmonic, while the second control system is responsible for the generation of the 3rd harmonic. Both control systems are synchronized and ensure a trapezoidal shape of air gap induction waveform regardless of the machine operation point. In order to ensure a sensorless control system the rotor angular speed and the state variables are estimated by a speed observer. This speed observer is based on the backstepping approach. All analytical proposed assumptions are confirmed by simulations and experimental results.

Introduction . Ensuring the operational safety of cargo lifting cranes, especially at nuclear power facilities when transporting hazardous loads such as spent fuel assemblies, requires high precision in the calculation of loadbearing structures. Existing modeling approaches do not always consider the influence of the detailing of removable load-handling attachments (RLHAs) on the overall stress-strain state of the crane. The objective of this study is to assess the influence of the finite element model’s level of detail for a traverse type RLHA on a flexible suspension on the convergence and accuracy of the static calculation results for an overhead crane. Materials and Methods . The study was conducted using the case of transporting TUK-13 containers with an overhead crane equipped with a traverse on a flexible suspension. Three variants of the crane’s computational static model (CSM) were developed and analyzed, varying in the way the RLHA was modeled: 1) representation of the load from the RLHA and cargo as lumped masses (weight); 2) use of a detailed model of the RLHA with cargo, featuring rigid element joints; 3) application of a detailed model of the RLHA with cargo, taking into account hinged joints. For each of the three models, a static analysis was performed using three different methods: linear static analysis, static analysis considering the P-Δ effect, and static analysis paying attention to both the P-Δ effect and large displacements. Conclusions . The comparative analysis showed that accounting for flexible suspension elements and hinged joints in the RLHA design requires consideration of the P-Δ effect and large displacements to adequately describe the deformed state of the “crane-RLHA-cargo” system. Linear methods and simplified RLHA models can lead to significant inaccuracies. The choice of the detailing level of RLHA and the calculation method significantly affects the reliability of the obtained results. Research Scope and Future Use . The results are applicable to the static analysis of overhead cranes with flexible suspensions and complex RLHAs. Further research could be extended to dynamic operating modes and other types of RLHAs.Practical Significance. The obtained information is important for engineering practice in the design and verification of overhead cranes’ calculation, enabling the selection of a rational balance between the model’s level of detail and the computing method to ensure the required accuracy and safety. Originality and Value . The novelty of this work lies in the systematic comparison of the influence of both the RLHA model’s level of detail (from umped masses to a detailed model with hinged joints) and various static analysis methods on the results for a crane with a flexible suspension. The results will be useful for design engineers, stressstrain analysts, and safety specialists working with lifting equipment in critical industries.

Switched resistance motors, are becoming increasingly used in industrial and hybrid electric vehicle (HEV) applications. But improving SRM performance is still a crucial field for study, especially with regard to their inherent benefit of accurate rotor position estimate, which is closely related to operational effectiveness. Rotor position sensing has traditionally required the incorporation of specialized sensors, which has led to difficulties like increased costs, complicated alignment, limited size, and maintenance requirements. In order to overcome these constraints, this work promotes the creation of sensorless motor control schemes that make use of cutting edge Artificial intelligence methods such as fuzzy logic and Adaptive Neuro-Fuzzy Inference System (ANFIS).To provide robust control, the suggested sensorless control systems make use of inputs such bus voltage, rotor speeds, torque instructions, and SRM parameters. The effectiveness of these methods is thoroughly assessed by painstaking simulation experiments, confirming their capacity to attain accurate control and high-performance operation. To further illuminate the benefits of sensorless control implementations, this research also does a comparison analysis between the two suggested soft computing approaches and their sensor-based equivalents. In the end, this research advances the field of SRM technology, opening the door to more dependable, economical, and efficient motor control systems in a variety of industrial and automotive applications.