Motion Control System Research Articles

Trajectory Tracking Control of Transformer Inspection Robot Using Distributed Model Predictive Control.

To overcome the difficulty in tracking the trajectory of an inspection robot inside a transformer, this paper proposes a distributed model predictive control method. First, the kinematics and dynamics models of a robot in transformer oil are established based on the Lagrange equation. Then, by using the nonlinear model predictive control method and following the distributed control theory, the motion of a robot in transformer oil is decoupled into five independent subsystems. Based on this, a distributed model predictive control (DMPC) method is then developed. Finally, the simulation results indicate that a robot motion control system based on DMPC achieves high tracking accuracy and robustness with reduced computing complexity, and it provides an effective solution for the motion control of robots in narrow environments.

Formation of an approach to modeling orbital operations assembly of a reconfigurable spacecraft on geostationary orbit

The aim of the study is to form an approach to modeling the operations of the orbital assembly of a reconfigurable spacecraft (RS) in geostationary orbit. Reconfigurable spacecraft are a set of modular spacecraft (MS), where, in a particular case, one MS can be assigned the functions of the service systems module (MSS), and the second - the functions of the payload module (MPN). To ensure the assembly of the RC, or the replacement of some MC, for example, in case of its failure with a new one, it is necessary to provide a solution to the problem of bringing the MS with the RS. The article analyzes and studies the operation of the motion control system of the MS during the convergence of the MS with the RS. A list of necessary mathematical models for performing operations in solving the problem of convergence of the MS with the RS is formed, and a block diagram of the interaction of mathematical models is presented. The paper presents a brief description of the mathematical apparatus that allows modeling the operations of convergence of the MS with the RS. This mathematical apparatus includes: a model of the orbital motion of the MS and the RS, models of the angular motion of the MS and the RS, sensitive elements and executive bodies. In this paper, the mathematical modeling of the MS with the RS convergence operations is considered as the subject of research. The object of the study is the motion control system of the MS, which ensures the implementation of the approach of the RS in geostationary orbit.

Risk Assessment in the Design of Railroad Control Command and Signaling Devices Using Fuzzy Sets

Risk assessment in the design of control command and signaling devices (CCS) is one of the elements required by law. These analyses should be carried out at many stages of investment with the participation of various teams. This article presents a risk analysis method based on fuzzy sets, which can support and increase the safety of investment processes involving the railroad traffic control industry. The article analyzes hazards identified in CCS design. These risks were identified using a survey method based on a set of questions prepared by the authors and by conducting interviews among experts from design offices. As part of the survey, responses were obtained from 28 respondents who are specialists in the railway traffic control industry. Workshop meetings were held in six different design offices and at manufacturing plants of motion control systems. The identified risks were analyzed using the FMEA (failure mode and effect analysis) method and the fuzzy set method, as well as various methods of fuzzification and defuzzification. The results of all of the methods were compared with each other. The best solution from the analyzed ones was proposed.

Multimodal Global Trajectory Planner for Autonomous Underwater Vehicles

The underwater environment introduces many limitations that must be faced when designing an autonomous underwater vehicle (AUV). One of the most important issues is developing an effective vehicle movement control and mission planning system. This article presents a global trajectory planning system based on a multimodal approach. The trajectory of the vehicle’s movement has been divided into segments between introduced waypoints and calculated in parallel by advanced path planning methods: modified A* method, artificial potential field (APF), genetic algorithm (GA), particle swarm optimisation (PSO), and rapidly-exploring random tree (RRT). The shortest paths in each planned segment are selected and combined to give the resulting trajectory. A comparison of the results obtained by the proposed approach with the path calculated by each method individually confirms the increase in the system’s effectiveness by ensuring a shorter trajectory and improving the system’s reliability. Expressing the final trajectory in the form of geographical coordinates with a specific arrival time allows the implementation of calculation results in mission planning for autonomous underwater vehicles used commercially and in the military, as well as for autonomous surface vehicles (ASVs) equipped with trajectory tracking control systems.

A framework to develop and test a model-free motion control system for a forestry crane

This article has the objective of presenting our method to develop and test a motion control system for a heavy-duty hydraulically actuated manipulator, which is part of a newly developed prototype featuring a fully-autonomous unmanned forestry machine. This control algorithm is based on functional analysis and differential algebra, under the concepts of a new type of approach known as model-free intelligent PID control (iPID). As it can be unsafe to test this form of control directly on real hardware, our main contribution is to introduce a framework for developing and testing control software. This framework incorporates a desktop-size mockup crane equipped with comparable hardware as the real one, which we design and manufactured using 3D-printing. This downscaled mechatronic system allows to safely test the implementation of control software in real-time hardware directly on our desks, prior to the actual testing on the real machine. The results demonstrate that this development framework is useful to safely test control software for heavy-duty systems, and it helped us present the first experiments with the world’s first unmanned forestry machine capable of performing fully autonomous forestry tasks.

Research on Multi‐Algorithm Switching Hybrid Control of Permanent Magnet Synchronous Motor for Electric Special Vehicles

AbstractIn order to improve the smoothness of the electric special vehicle (ESV) under each operational condition, a multi‐algorithm switching hybrid control (MASHC) algorithm is proposed for the permanent magnet synchronous motor (PMSM) of ESV. For a steady–state operation state, the transfer function structure of the motor control system is optimized, avoiding its output variables from varying with the integral and differential changes of the input quantity to enhance the stability and response speed of the control system. For transient operation states, it is considered to avoid the torque ripple that can be generated due to the increased computational effort of introducing an intelligent algorithm. The fuzzy proportional (FP) control algorithm that can replicate the transient performance of the fuzzy control algorithm is designed to improve the control accuracy of the control system. In addition, a switching function is designed to blend the two algorithms to improve the overall vehicle operation performance. To verify the effectiveness of the control algorithm, a simulation model and an experimental platform are developed. Both simulation and experimental results show that the proposed control algorithm has the advantages of no overshoot and oscillation in output, which can improve the smoothness of the ESV drive system. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

A Review of EMI Research of High Power Density Motor Drive Systems for Electric Actuator

With the global attention given to energy issues, the electrification of aviation and the development of more electric aircraft (MEA) have become important trends in the modern aviation industry. The electric actuator plays multiple roles in aircraft such as flight control, making it a crucial technology for MEA. Given the limited space available inside an aircraft, the power density of electric actuators has become a critical design factor. However, the pursuit of high power density results in the need for larger rated power and higher switching frequency, which can lead to severe electromagnetic interference (EMI) issues. This, in turn, poses significant challenges to the overall reliability of the electric actuator. This paper provides a comprehensive review of EMI in high power density motor drive systems for electric actuator systems. Firstly, the state of the art of electric actuator systems are surveyed, pointing out the contradictory relationship between high power density and EMI. Subsequently, various EMI modeling approaches of motor control systems are reviewed. Additionally, the main EMI suppression methods are summarized. Active EMI mitigation methods are emphasized in this paper due to their advantages of higher power density compared with passive EMI filters. Finally, the paper concludes by summarizing the EMI research in motor drive systems and offering the prospects of electric actuators.

Development of a DC Motor Speed Control System Based on PID

In the field of motion control systems, motor speed control plays a pivotal role. Various control algorithms and methods have been developed for this purpose, and one of the earliest strategies to emerge was analog control. Over time, it has evolved into a typical control structure with convenient parameter tuning capable of meeting general control requirements. This design is based on digital control algorithms, with the ST89C52 microcontroller as the control core. It generates pulse-width modulation (PWM) pulses controlled by a digital algorithm to regulate the speed of direct circuit (DC) motors. Additionally, it utilizes a photoelectric sensor to convert motor speed into pulse frequency, which is fed back to the microcontroller, thereby achieving closed-loop speed control and eliminating static speed errors.

Research on the Current Control Strategy of a Brushless DC Motor Utilizing Infinite Mixed Sensitivity Norm

During the brushless DC (BLDC) motor working process, the system encounters inevitable uncertainties. These ambiguities stem from potential fluctuations, random occurrences, measurement inaccuracies, varying operational conditions, environmental shifts such as temperature alterations, among other factors. Uncertainties, an inherent aspect of any real control system, can be broadly classified into two categories: sensor signal uncertainties and discrepancies between the mathematical and actual models due to parameter perturbations. To mitigate the impact of sensor noise and parameter perturbations on the BLDC motor, a robust control strategy utilizing infinite norm mixed sensitivity based on PI control strategy (PI-H∞-MIX) is proposed in this paper. Firstly, the closed-loop control structure and transfer function model of the BLDC motor control system current loop are analyzed based on the current loop circuit topology, and then, the model parameters perturbation is analyzed, and the multiplicative uncertainty bound is given. In addition, the appropriate weighting function is selected to ensure the robustness of the system. In this case, the controller design problem is transformed into the H∞ standard control problem, and then, the system augmentation matrix is established, and the controller is solved by Matlab/Simulink. Finally, the performances of the traditional PI control strategy and the PI-H∞-MIX are compared and analyzed. The results show that (1) the proposed PI-H∞-MIX strategy can improve the control system robustness under the parameter perturbation condition effectively, and (2) the proposed PI-H∞-MIX strategy can suppress the noise signal of the sensor.

Feasibility Investigation on Sinusoidal-Reluctance Rotor Contour in Variable Reluctance Resolver

Variable reluctance (VR) resolvers are universally employed as the absolute position sensor in motor control systems. In this paper, a 4-pole 16-tooth VR resolver is proposed with the novel sinusoidal-reluctance rotor contour, and its operation feasibility is evaluated via the analytical investigation and finite element (FE) analysis. Considering the slot and air-gap flux leakage, the original third-order harmonic from the sinusoidal-reluctance rotor contour can be compensated to suppress the total harmonic distortion (THD) in the envelope. And the magnitude of the compensation third-order harmonic can be regulated by adjusting the tooth width. Under 4 mm tooth width, the THD of the cosine envelope with the proposed rotor contour can be limited to only 0.54%, and the angle error can also be restricted to only 0.012 degree (0.72 arc min).

On Some Properties of Sets of Bounded Controllability for Stationary Linear Discrete Systems with Total Control Constraints

We consider the problem of constructing reachable sets, i.e., sets of terminal states into which a system can be transferred from the origin in a fixed time, and 0-controllability sets, i.e., sets of initial states, from which a system can be transferred to the origin in a fixed time, for stationary linear discrete systems with a total control constraint. The representation of reachable and 0-controllable sets as linear transformations of superellipsoidal sets of finite and infinite dimensions is proved. A constructive method for describing the desired sets based on the apparatus of supporting half-planes is proposed, including for the limit sets of reachability and controllability. In the case of Euclidean spaces, the description is obtained explicitly. Examples are given. For a three-dimensional satellite motion control system in a near-circular orbit, reachability sets are modeled.

A Low Common-Mode SVPWM for Two-Level Three-Phase Voltage Source Inverters

In order to reduce the common-mode voltage (CMV) generated by the use of space vector pulse width modulation (SVPWM) in two-level three-phase voltage source inverters, a low common-mode SVPWM method is proposed. In this method, the voltage plane is divided into 12 sectors, and on each sector, two non-zero vectors of the same class and one single zero vector are adopted for synthesis. The action time of the zero vector is placed at both ends of each switching cycle, the currents are sampled at the beginning of each switching cycle, and the action time and sequence of vectors on each sector is provided. Simulation and experimental results show that, in the vector control system of a permanent magnet synchronous motor fed by the inverter, compared with the conventional SVPWM, the proposed method reduces the CMV peak-to-valley value by 33.333%, the CMV jump frequency by three times, and the performance of the line voltage and line current. The electromagnetic torque and rotor speed remain good, which has good application value in high-performance drives.

Electric Arc Furnace Electrode Movement Control System Based on a Fuzzy Arc Length Identifier

From the point of view of the synthesis of control influences, arc steelmaking furnaces are complex nonlinear objects with strongly expressed mutual influences. It has been demonstrated that at a given supply voltage, the distribution of the current values of the phase currents in the quasi-steady-state mode makes it possible to estimate the situation in the arc space of an arc steelmaking furnace and identify the value of arc lengths. This dependence is preserved in transient modes. In order to identify arc lengths from the phase currents, it is proposed to use an approach based on the theory of fuzzy sets. The construction of the fuzzy arc length identifier rule base was carried out in two stages: the first stage used data from quasi-steady-state modes and the Wang–Mendel algorithm; the second stage involved adding a new rule to the database if the activity level of the formed rules was lower than the established level α for the data obtained in the dynamic mode. Further optimization of the parameters of the fuzzy identifier for operation in dynamic modes was carried out using the “back-propagation” algorithm. Based on the identified values of arc lengths, a control system for the movement of electrodes in an arc steelmaking furnace was synthesised. The proposed control system makes it possible to eliminate unproductive electrode movements due to changes in the situation in other phases of the arc steelmaking furnace and simplifies the application of modern methods of synthesising a control system for such complex objects. The results obtained in the mathematical model have confirmed the effectiveness of the proposed control system for the movement of electrodes in an arc steelmaking furnace.

A Novel Angle Segmentation Method for Magnetic Encoders Based on Filtering Window Adaptive Adjustment Using Improved Particle Swarm Optimization.

In this paper we outline newly-developed control algorithms, designed to achieve high-precision feedback for a motor control system using a magnetic encoder. The magnetic encoder, combing single-pole and multi-pole magnetic steels, was adopted to extend the resolution of the magnetic encoder. First, with a view to settling the issue of the jump points of the multi-pole angle value at the convergence of two adjacent magnetic poles, the angle segmentation method, which uses the window filter discrimination method, is employed to determine the actual angle value. The appropriate filter window width is selected via the improved particle swarm optimization (IPSO) algorithm, and an expanded resolution is achieved. Second, a compensation table is completed via a linear compensation algorithm based on virtual cutting to enhance the accuracy of the combined magnetic encoder. On this basis, a linear difference algorithm is used to achieve deviation correction of the angle. Finally, the jump points can be restrained effectively via the angle segmentation method. The resolution reaches 0.05°, and the accuracy is 0.045°.

Research on coupling control of multiple permanent magnet synchronous motors based on NAISMC and SMDO.

The synchronous control system of multi-permanent magnet motor has the characteristics of many parameter variables and mutual coupling. The use of sliding mode control to optimize the parameters in the multi-permanent magnet motor system not only ensures the stability of the system operation, but also improves the control accuracy of the system, which is of great importance in practical applications. Based on this background, the study combines the new adaptive integral sliding mode control (NAISMC) with the improved sliding-mode disturbance observer (SMDO) and uses it for the multi-permanent magnet synchronous motor (MPMSM). In NAISMC, the controller updates and adjusts the parameters of the controller using an adaptive algorithm according to the state of the system and the error signals, which further improves the stability and robustness of the system. SMDO utilizes the principle of the sliding-mode observer to estimate the disturbance of the system, and eliminates the effect of the disturbance on the system by introducing a compensation term. The sliding mode observer calculates the disturbance estimate by comparing the difference between the actual and the estimated outputs. The disturbance estimate is finally used to generate the corresponding compensation signal to eliminate or minimize the effect of the disturbance on the system. NAISMC is combined with SMDO and used in the deviation coupling control of MPMSM. The study established a simulation experiment environment in MATLAB, set the simulation time to 0.4s, and the rated speed of the motor to 1000r/min. The improved sliding mode control scheme is tested, and the results show that the motor output speed, tracking error and electromagnetic torque variation under the improved sliding mode control scheme are smaller than those under the traditional sliding mode control scheme. Under the same simulation conditions, the multi-motor speed synchronization error under the improved sliding mode control scheme is around 0r/min, and its error value is close to 0, so the control effect is higher. In conclusion, the optimization scheme proposed in this study can effectively improve the stability and control accuracy of the multi-motor system.

Algorithm for automatic optimizing cross-cut saw based on computer vision techniques

The optimization of timber classification by grades and defect detection plays an important role in the production of timbers. Traditionally, a timber is manually cut by a worker according to his experience. Defect detection and classification of a timber are with great subjectivity. Meanwhile, the action is not safe enough. In this case, an automatic optimizing cross-cut saw to finish these tasks of timber classification by grades and defect detection is built significantly. Related algorithms and detailed procedures for optimizing cross-cut saws are proposed in this paper. Additionally, a vision system is used to capture images of a timber. Captured images are analyzed and processed. First, defects in these images are detected. Then the serviceable part (defect-free) of a timber can be determined. Based on the pretrained network, the timber can be classified. As the homography matrix has been known, the physical position can be confirmed. In our proposed system, the cutting list is transmitted from the industrial control computer to a motion control system, then the timber can be cut according to the cutting list automatically. In this paper, related algorithms and detailed procedures are given. Moreover, a new optimizing cross-cut saw is built. Experiments show that the processing time for each image is about 0.026s and the minimum mean average precision is 94.15%. In this case, it can make the optimizing cross-cut saw efficient, labor-saving and safe. Furthermore, related algorithms are suitable to improve a traditional automatic optimizing cross-cut saw.

Penerapan Metode Fuzzy Logic-PID Sebagai Kontrol Gerak Robot Berkaki Enam (Hexapod)

Robotics technology is currently developing rapidly and has become one of the sophistications that are relied upon by every country, one of which is Indonesia. One of the activities for the development of robotics technology in Indonesia is the Indonesian Robot Contest (KRI). KRI was held as an event for students' creativity in designing robots. One of the divisions contested at KRI is the Indonesian Search and Rescue Robot Contest (KRSRI) division. In the KRSRI division, it is required to make a legged robot that can navigate the motion of walking in the competition area and pass obstacles on the track. Of course, a navigation motion control system is needed that can regulate the movement of the legged robot's steps properly, so that the robot can pass the path in the arena. In this study, the answer to this problem is the application of legged robot navigation motion control using the Fuzzy Logic-PID method. The Fuzzy Logic-PID method is a combination of two methods between the Fuzzy Logic Controller method and the Proportional Integral Derivative (PID) control method. The Fuzzy method’s role is to produce constant values ??P, I, and D based on the error value and the incoming error delta. Furthermore, the resulting constant value is used in the calculation of the PID control. From the experimental data, the Fuzzy method has been able to produce a PID constant value and the PID method can also be applied to regulate the robot's motion steps. The test results on trials using obstacles and without obstacles were successful, except for uphill obstacles with a success percentage of 60% successfully passing incline obstacles and 40% failing to pass uphill obstacles.

Methodology and Research of Intelligent New Energy Vehicle Motion Control System based on Fuzzy Adaptive

To resolve the difficult control issue of intelligent new energy automobile in the process of vehicle control, the study starts from the vehicle motion mode and splits the vehicle control into two parts, transverse control and longitudinal control. Among them, the longitudinal speed control is controlled by an improved adaptive PID model, while the lateral angle control is dominated by an indistinct adaptive PID model, afterwards longitudinal speed control is combined with the lateral angle control for joint control. Finally, the study uses the actual lane simulation to verify the three perspectives of transverse control, longitudinal control and joint control respectively. It shows that the longitudinal control and lateral control are well realized with the improved adaptive PID model control effect at 8km, 15km and 20km per hour. Meanwhile, maximum trajectory error of the combined direction and transverse dominate is always lower than 0.5m at vehicle speeds of 8km/h, 16km/h and 20km/h in the integrated road environment and the combined longitudinal speed and transverse angle control performance is good in the curves. This shows that the model designed by the research can realize adaptive real-time precision control.

In-Wheel Motor Control System for Four-Wheel Drive Electric Vehicle Based on CR-GWO-PID Control.

In order to improve the driving performance of four-wheel drive electric vehicles and realize precise control of their speed, a Chaotic Random Grey Wolf Optimization-based PID in-wheel motor control algorithm is proposed in this paper. Based on an analysis of the structural principles of electric vehicles, mathematical and simulation models for the whole vehicle are established. In order to improve the control performance of the hub motor, the traditional Grey Wolf Optimization algorithm is improved. In particular, an enhanced population initialization strategy integrating sine and cosine random distribution factors into a Kent chaotic map is proposed, the weight factor of the algorithm is improved using a sine-based non-linear decreasing strategy, and the population position is improved using the random proportional movement strategy. These strategies effectively enhance the global optimization ability, convergence speed, and optimization accuracy of the traditional Grey Wolf Optimization algorithm. On this basis, the CR-GWO-PID control algorithm is established. Then, the software and hardware of an in-wheel motor controller are designed and an in-wheel motor bench test system is built. The simulation and bench test results demonstrate the significantly improved response speed and control accuracy of the proposed in-wheel motor control system.

Emerging the real‐time performance for the single axis slave controller in the decentralised network

AbstractIn the era of the fourth industrial revolution, many certain technologies such as Internet of Things (IoT) or Internet of Service (IoS) have been implemented for the improvement of current system. However, most of them did not ensure the real‐time performance which is inevitable for modern motion systems. The implementation of Ethernet‐based protocol, rapid data exchange and synchronised transmission are proper for the novelties of slave controller. An integration of the decentralised network into the motion control system is introduced firstly. To demonstrate the conceptual design, some descriptions of motivations and related definitions are explained. Then, the structure of hardware components and internal connections are mentioned. Later, the software architecture including the data exchange and flowchart of motion program, is described in detail. To verify the feasibility and effectiveness of the proposed approach, some technical analysis of timing synchronisation and tracking deviation between our method and the others are carried out. In addition, several practical validations are conducted in the same conditions. The contributions of the authors are (i) to firstly present the concept of controller design using the real‐time technology, (ii) to illuminate both hardware design and software design of the proposed approach and (iii) to analyse the superior performance in delay time between our method and the others as well as validate the real‐world results to prove the effectiveness and feasibility. From the authors’ achievement, it is observed that these results can be broadly purposeful to the sustainable development of Industry 4.0.