Automatic Control Research Articles

ASCD: Automatic sensing and control device for crop irrigation scheduling

Traditional agricultural irrigation systems suffer from wasting a lot of water allocated for irrigation through evaporation and drainage. To address water waste and increase crop productivity, irrigation scheduling is used, as irrigation scheduling depends on four elements: soil moisture, soil characteristics, weather conditions, and plant type. This paper proposes a new design for monitoring agricultural conditions and controlling the amount of soil moisture by determining the required irrigation water ratios and the ideal time period for irrigating crops. An intelligent control and monitoring algorithm was created using experimental data for a wide range of plants (for soil moisture from 21 to 80 kPa), where plants were classified into three groups according to their common irrigation starting point. Based on the proposed plant classification, three models were provided, where irrigation ratios as the required parameter, soil moisture, plant type, and time interval as input parameters. This algorithm was used to program a custom-made automatic sensor and control device (ASCD). The ASCD is equipped with two input ports to communicate with two types of soil moisture sensors (a resistive sensor and a capacitive sensor) and with three output ports to drive three types of electronic irrigation valves. The ASCD can read from one sensor and drive one electronic valve at a time, the choice of which is made by the farmer. ASCD based the new algorithm showed high accuracy compared to a number of experimental results. The average absolute relative deviation (AAPD) of the new models and experimental data is 5.46 %. The application of the new algorithm shows a reduction in the amount of water used for crop irrigation during the day versus irrigation at night. On the other hand, ASCD has proven its success in sensing and controlling, and it works automatically and independently.

Improvement of the control system with the drive of high voltage arc furnaces

The article presents a method for improving the control system of electric motors driving the electrodes of high-voltage arc furnaces. The developed method today in the field of metallurgy is of great importance in solving problems such as at the first stage of melting and casting metal in arc steelmaking furnaces, when the electrodes are initially lowered into the working bath, the connection point breaks as a result of contact with a metal plate, the incompatibility of the formation of an electric arc on the electrodes, holding the electrodes at a certain distance from the metal charge. Also, automatic control of the speed of movement of the electrodes, i.e. (the time of formation of an electric arc in the electrodes, which reduces the speed of its movement, the time of lifting the electrodes, lowering, increasing the speed of movement), is relevant for solving problems such as welding electrodes into a metal shackle. The main purpose of introducing this method into practice is to reduce electricity consumption and ensure reliable operation of high-voltage electric arc furnaces by reducing the melting time of metal.

Performance study of a heat pump fresh air unit based on desiccant coated heat exchangers under different operation strategies

Fresh air system is getting more and more important nowadays. The heat pump fresh air system based on the desiccant coated heat exchanger (DCHE) that can handle the latent and sensible load of fresh air efficiently has a large energy saving potential. To improve the performance of the heat pump fresh air system based on DCHE, in this paper, a control system based on PLC is established and the operation strategies of the system are investigated. An operation strategy including automatic control of the opening of the electronic expansion valve based on the suction superheat of the compressor, control of the switchover period based on the relative humidity of supply air, and control of compressor frequency based on evaporation and condensation temperature is established. By using the optimal operation strategies, the dehumidification rate and COP of the system can reach 4.42 kg/h and 6.2 in summer, compared with the unoptimized strategy it increased 8% and 25%, respectively. The two performance indices can reach to 3.04 kg/h and 6.98, with an increase of 89% and 78%.

Self-paced heart rate control during treadmill exercise for persons with gait impairment: a case study

Introduction:A self-paced (SP) heart rate (HR) control system proposed in a previous study was found to be feasible for healthy participants. The aims of this work were to investigate whether the SP HR control system is feasible to achieve accurate HR control in a participant with gait impairments, and to assess its interaction with an existing motor-driven body weight support (BWS) system.Methods:One participant with cerebral palsy was recruited in this case study. Three preliminary tests were completed to determine the appropriate mean value and amplitude of the target heart rate curve, and to identify a customised heart rate response model. Two series of formal self-paced heart rate control tests were then conducted to investigate the influence of different heart rate compensators and the presence of the BWS system.Results:The customised heart rate controller achieved improved accuracy in heart rate control and reduced oscillation in the treadmill target speed: the root-mean-square heart rate tracking error (RMSE) was 2.38 beats per minute (bpm) vs. 3.91 bpm (customised controller vs. nominal controller), and the average power of changes in the treadmill target speed was 0.4 × 10−4 m2/s2 vs. 8.4 × 10−4 m2/s2. The BWS system resulted in improved HR tracking accuracy: RMSE on heart rate tracking was 3.02 bpm vs. 3.50 bpm (with BWS vs. without BWS). The BWS system had no influence on the automatic position control accuracy: RMSE on distance tracking was 0.0159 m vs. 0.0164 m.Conclusion:After customising the heart rate compensator, the self-paced heart rate control system is feasible to achieve accurate heart rate control in an individual with gait impairments, and it can correctly interact with the BWS system.

Method of reliability control of thermoelectric systems to ensure thermal regimes

The paper presents the results of research of controllability of the thermoelectric system for ensuring thermal modes of electronic equipment, including a regulator, a cooler, and a component of excess heat removal to the environment. It is shown that for the use of methods of optimization of automatic control systems it is necessary to study the transfer and dynamic characteristics of the object - thermoelectric cooling device with one input and one output. The mathematical model of the thermoelectric cooler of the system of providing thermal modes of a given design is presented, which takes into account the influence of the conditions of interaction of the heat sink with the medium on the main significant parameters, reliability indicators, dynamic and energy characteristics of the single stage cooler. The model is created for the operating range of cooling, level of thermal load, geometry of thermocouple branches, different temperature of the medium, for the characteristic thermal regime of maximum cooling capacity. The results of calculations of the main significant parameters, reliability indicators, dynamic and energy characteristics of the cooler for different medium temperature in the operating temperature range and variation of conditions of heat exchange of the heat sink with the medium are given. It is shown that as the intensity of heat exchange of the heat sink with the medium increases, the temperature difference between the heat sink and the medium decreases. This makes it possible to significantly reduce the relative failure rate, increase the probability of failure-free operation of the thermoelectric cooler and control the reliability indicators of the device of a given design during operation.

Machine vision-based online detection method for color characteristics of cobalt extraction solution

Cobalt, as a rare metal, plays an important role in strategic resources due to its physical, chemical, and mechanical properties in applications. In order to achieve automatic control of the cobalt extraction process, it is necessary to conduct online detection of the color characteristics of the cobalt extraction solution. Unfortunately, due to the lack of online automatic detection methods for the color of cobalt extraction solution, the automatic control of the extraction process has not yet been achieved. Currently, the color of cobalt extraction solution needs to be observed and judged by operators based on experience. This will result in significant detection errors and time lag. To change this situation, an online detection method for color features of cobalt extraction solution based on machine vision is proposed in this article. Firstly, we establish a real-time image acquisition environment for detecting object colors, and then use the Gaussian filters and K-means algorithm to denoise and segment the image. In order to correct color distortion in images caused by ambient light, we measure the color feature values of a set of standard color cards using the machine vision system and a standard spectrophotometer. Based on this test data, we establish chromaticity correction models for the extraction solution using back propagation (BP) network and radial basis function (RBF) network, respectively. The models can correct the color characteristic values of the extraction solution, overcome environmental interference, and thus obtain more accurate color characteristic values of the extraction solution. The established model can be used for online automatic color detection of cobalt extraction solution. The modeling results indicate that in the established color measurement environment, the RBF network model outperforms the BP network model in color feature detection accuracy.

Improved Immune Moth-Flame Optimization Based on Gene Correction for Automatic Reverse Parking.

During the process of reverse parking, it is difficult to achieve the ideal reference trajectory while avoiding collision. In this study, with the aim of establishing reference trajectory optimization for automatic reverse parking that smooths and shortens the trajectory length and ensures the berthing inclination angle is small enough, an improved immune moth-flame optimization method based on gene correction is proposed. Specifically, based on the standard automatic parking plane system, a reasonable high-quality reference trajectory optimization model for automatic parking is constructed by combining the cubic spline-fitting method and a boundary-crossing solution based on gene correction integrated into moth-flame optimization. To enhance the model's global optimization performance, nonlinear decline strategies, including crossover and variation probability and weight coefficient, and a high-quality solution-set maintenance mechanism based on fusion distance are also designed. Taking garage No.160 of the Dalian Shell Museum located in Dalian, Xinghai Square, as the experimental site, experiments on automatic parking reference trajectory optimization and tracking control were carried out. The results show that the proposed optimization algorithm provides higher accuracy for reference trajectory optimization and can achieve better tracking control of the reference trajectory.

Совершенствование структуры системы управления электроприводом переменного тока с асинхронными тяговыми электродвигателями на основе микропроцессорных вычислительных устройств

Objective: consideration of the issue of improving the structure of the automatic control system for an AC traction electric drive with asynchronous electric motors. Abandonment of the physical wheelset speed sensor. An overview of the performance of microprocessor computing devices at the beginning of their appearance in the USSR. An overview of the performance parameters of foreign and domestic microprocessor computing devices both abroad and in Russia. Comparison of the performance of computing devices at the time of their appearance and at the present moment. Methods: collecting information on possible options for improving the structure of the automatic control system for an AC traction electric drive. Collecting information about domestic microprocessor computing devices used at the beginning of their appearance. Collection of information on domestic and foreign microprocessor computing devices used today. Comparison of performance parameters of domestic microprocessor computing devices used at the beginning of their appearance with devices used today. Results: the possibility of analyzing the implementation of a microprocessor control system by a traction electric drive with asynchronous electric motors without using a physical speed sensor using a state observer based on an adaptive Luenberger filter is indicated. Practical importance: it consists in obtaining economic benefits from the elimination of the physical speed sensor of the wheelset as a result of the elimination of production and maintenance costs.

Calibration of visual measurement system for excavator manipulator pose

The automatic control of excavator operation trajectories is a pivotal technology for autonomous excavators, with the essential prerequisite being the real-time measurement of manipulator poses. Given the complexity of the operating environment, traditional sensor-based measurement methods face limitations, whereas visual measurement emerges as a promising technique. Accurately measuring excavator manipulator poses involves a crucial aspect: mapping the relationship between image information and poses. First, to address the significant errors in pose prediction encountered with machine learning techniques like artificial neural networks, this work introduces a mathematical model for mapping this relationship, referred to as the pose mapping mathematical model, which includes calibrating model parameters. Second, to address the sensitivity of initial values in the calibration process, we propose a residual-guided initialization algorithm. This algorithm aims to ensure that initial values closely approximate the ground truth values, thus preventing matrix singularity at the source and avoiding parameter estimation divergence. Third, to tackle challenges such as unstable lighting conditions and discrepancies between the dataset and the mathematical model, we introduce the random sample consensus-driven Levenberg–Marquardt parameter optimization algorithm to enhance parameter estimation accuracy. Experiments with static and dynamic online measurement demonstrate that our method reduces pose measurement errors compared to existing methods. This research lays a solid foundation for developing visual measurement techniques for excavators and automated manipulator control based on visual measurements, also serving as a valuable reference for research on mechanical arms.

Recent Research on Magnetic Machinery

Background: As a clean energy source, magnetic energy is a significant power source of mechanical equipment, which affects the direction of control mode and mechanical structure of mechanical equipment. Magnetic machinery is widely used in industrial power systems and automatic control systems as the power source of mechanical equipment transmission parts or actuators. Magnetic machinery is essential to make mechanical equipment easy to control, energy saving and environmental protection, simple structure, and so on. In order to innovate the control mode of mechanical equipment and optimize the types of traditional mechanical systems, magnetic machinery developed magnetic coupling, magnetic gear, magnetic spring, and other magnetic machinery. The characteristics of magnetic machines with different functions are analyzed based on the types of magnetic machines. Therefore, this aspect's development and application are getting more attention in recent years. To innovate the control mode of mechanical equipment and optimize the types of traditional mechanical structures, magnetic types of machinery, such as magnetic coupling, magnetic gear, and magnetic spring, are making continuous progress. New magnetic machines are also being developed. This paper summarizes the typical patents on three kinds of magnetic machinery: magnetic coupling, magnetic gear and magnetic spring. In addition, the advantages of existing magnetic machinery are summarized, the current situation of magnetic machinery is analyzed, and the development of magnetic machinery is summarized. Through the analysis of enormous patents of magnetic coupling, magnetic gear, and magnetic spring, it is concluded that although there are many kinds of magnetic machinery, there are no systematic and mature design theories and methods. The development trend of magnetic machinery is also discussed. The research on magnetic machinery helps innovate mechanical equipment's control mode and optimize the types of traditional mechanical structures. As a result, more patents will be invented in the future.

Adaptive cruise control design for collision risk avoidance

With advanced technologies such as perception and automatic control, automated vehicles (AVs) are gradually replacing human-driven vehicles (HDVs). They will become a significant component of transportation systems. As the crucial longitudinal control model for AVs, the existing adaptive cruise control (ACC) model faces challenges such as poor linear stability and compromised safety. To solve the problem, this paper proposes an adaptive cruise control model to avoid collision risk. First, the delay-considerate collision risk control strategy (DCRCS) is developed to consider vehicles' perception and control delay. Then, a proposed adaptive cruise control (PACC) model is designed by incorporating DCRCS into the ACC model based on the control gain coefficient. Finally, the effectiveness of the PACC model is discussed and analyzed in terms of stability, safety, efficiency, energy consumption, and pollutant emissions through a combined approach of theoretical analysis and simulation experiments. The result shows that (1) compared to the classical ACC model, the PACC model demonstrates significant improvements in system stability, reduced safety risks, enhanced efficiency, and decreased energy consumption and pollutant emissions. These enhancements are observed when the control gain coefficient is set to a positive value. (2) The equilibrium speed minimally influences the effectiveness of the PACC model. Under varying speed conditions, the PACC model consistently maintains stable performance. (3) The effectiveness of the PACC model is closely related to the selection of the control gain coefficient. Considering the effects of the control gain coefficient on stability, safety, efficiency, energy consumption, and pollutant emissions of the PACC model, the optimal range for the control gain coefficient is in the range of [0.8, 1.0]. In summary, compared to the classical ACC model, the PACC model exhibits outstanding performance in various aspects. It provides theoretical support for the longitudinal control of AVs in the future.

Preface

The advent of the fourth information revolution has made the digital economy a major driver of energy transition and low-carbon development. The overall architecture of smart energy is based on intelligence as the core, and based on infrastructure platforms such as intelligent cloud and IoT, as well as AI middle platform, Data middle office ether, etc. And with the help of cloud computing, artificial intelligence, big data, blockchain, digital twins and other technologies, smart energy can promote the intelligent transformation of energy enterprises ultimately.Against such background, the 2023 2nd International Conference on Smart Energy and Electrical Engineering (SEEE 2023) was held via hybrid form during December 22nd to 24th, 2023 in Malaysia. It was attended by about 50 researchers, scientists, engineers, and students working in the fields of smart energy and electrical engineering.The aims of SEEE 2023 are:To create an academic forum for sharing, communication and research at the international level, so that participants can be informed of the latest research directions, contents and results of smart energy and electrical engineering.To provide approaches to the main problems facing smart energy and electrical engineering, creating spaces that encourage discussion and joint development of research, technology development, and innovation.The excellent papers selected form the submissions were approved for presentation at the Conference and publication in this Conference Proceedings. Among the submissions are some submitted from abroad, but are unfortunately not accepted after rigorous review processes.There was an enabling environment for discussion and exchange of ideas, during which topics such as Core Technology of Intelligent Energy Equipment, Smart Transmission and Distribution, Power Grid Dispatching and Automatic Control, Power Systems and Energy, Electrical Theory and New Technology, etc. were presented. Some of the important issues were the sharing and discussion of Wireless Power Transfer and its Application on Electric Vehicle Wireless Charging by Prof. Yiming Zhang (Fuzhou University, China), Corona Loss Characteristics of EHV/UHV AC Transmission Lines by A. Prof. Shilong Huang (North China Electric Power University, China), Integrated Renewable Energy System based on Hydrogen by Prof. Mohan Lal Kolhe (University of Agder, Norway), etc.As in the last meeting, SEEE 2023 was again a space for the integration of undisputed knowledge and sharing of peer experiences within the specific areas of smart energy and electrical engineering. Both conference and presentation sessions were attended by many conference attendees, allowing closer relationships, both academic, as well as scientific and personal. The cordiality and good treatment of the attendees promoted a climate of friendship, which we could enjoy during all the development of the conference agenda.We would like to extend an enthusiastic round of thanks to all our conference authors and speakers for their excellent contributions. We are indebted to the Technical Program Committee for their efforts in making and pushing the conference program. Thanks also to the members of Journal of Physics: Conference Series for making the publication of SEEE 2023’s Proceedings possible.List of Committee Member is available in this pdf.

Leveraging Deep Learning to Increase the Success Rate of DoS Attacks in PMU-Based Automatic Generation Control Systems

Leveraging Deep Learning to Increase the Success Rate of DoS Attacks in PMU-Based Automatic Generation Control Systems

Hybrid System PSO-ANFIS for Optimization of The Water Level in The Tank

The speed and pressure of the water flow are determined by the height and volume of the water. The speed of the water flow in the actuator is determined by the use of this flow sensor system. A good tank-based water flow control model should be developed. At a certain point, the actuator stabilizes the rate of water production per minute. Therefore, it is necessary to develop an automatic and precise control technique. Many Artificial Intelligence (AI) methods are used in system optimization. Among them are Particle Swarm Optimization (PSO), Neural Network (NN), Fuzzy Inference System (FIS), and ANFIS. Adaptive Neuro Fuzzy Inference System (ANFIS) is a combination of NN and FIS. In this study, the PSO method was combined with ANFIS. This hybrid method produces better optimization compared to the previous method. The best water level control simulation results are PSO-ANFIS with an overshot of 0.572 pu, undershot of 0.563 pu, and flow output overshot of 0.008 pu, undershot of 0.009 pu.

Full-scale linear sensing of mode-localized sensors enabled by optimized readout circuit

This paper proposes a novel single-port readout circuit to realize the full-scale linear sensing of mode-localized sensors. In our proposal, in addition to the conventional frequency closed-loop control, the amplitude closed-loop based on automatic gain control (AGC) is adopted to stabilize the amplitude product of resonant units at a normalized value so that the difference of squared amplitudes can be regarded as the sensor readout to characterize the variations of external input signals. A micro-electro-mechanical system (MEMS) mode-localized accelerometer prototype is tested based on our proposed readout circuit. The experiment results demonstrate that the tested accelerometer prototype realizes the linear sensing in the full measurement range and shows a mechanical sensitivity of 0.1182 /g with a maximum non-linearity of -6.54 %, which are basically consistent with the output metric based on the subtraction of reciprocal amplitude ratios (SRAR).

A 56‐GBaud lumped linear push–pull driver for Mach–Zehnder modulator in 130‐nm SiGe technology

AbstractA fully differential lumped linear driver for Mach–Zehnder modulator has been presented and assessed in 130‐nm SiGe BiCMOS technology. Multitopology peaking techniques, especially T‐coil peaking method, have been employed to flatten the frequency response and increase the bandwidth. Degeneration resistors have been used to enhance circuit linearity. Simultaneously, improvements have been made to the output stage of the conventional single emitter follower push–pull) circuit to enhance the output eye diagram quality at higher transmission rates. The fabricated driver achieved a differential gain of 16.2 dB with a bandwidth of over 50 GHz, corresponding to a fixed output swing of over 3.2 Vppd within the automatic gain control loop. Time domain measurements, limited in speed by the measurement setup, reported a data rate up to 56 Gb/s none return to zero and 40‐GBaud 4‐levels pulse amplitude modulation with a bit error rate less than 10−12.

Control of Carbon Dioxide Bivalent Heat Pump on Heating of Buildings

The scheme of a bivalent heat pump (BHP) is considered, using both the heat of the water from the return network and the heat of the outside air as low-potential heat sources (LPH). The aim of the work is to create a BHP circuit that provides functioning at the variable heat load temperature. The goal was achieved by solving the following problems: analysis of methods of synthesis of BHP circuits, analysis of circuit operation under random disturbances and development of the automatic control systems for BHP. The most significant result of the work is: a heat pump circuit that can operate at variable pressures of the evaporator and the gas cooler. The next significant result is, for bivalent heat pumps intended for operation in heat supply systems with qualitative and qualitative-quantitative laws of thermal control, the introduction into the heat pump circuit of a heat exchanger installed in the return water circuit of the secondary building and cooled by outside air, as well as two control valves installed in series between the gas cooler and the evaporator, the first valve installed along the refrigerant flow being controlled by a signal based on the pressure difference between the outlet of the gas cooler and the separation vessel between the evaporator and the gas cooler, and the second by pressure in front of the evaporator. The significance of the obtained results lies in the increase of the COP of the heat pump, due to the increase of heat transfer in the gas cooler circuit. The HHP circuit differs from the known ones in that it uses two control valves and the heat exchanger for additional cooling of the return water of the BHP heated building.

Revisiting the Young’s model for ferrofluid droplets: Magnetowetting or magneto-dewetting?

Magnetic field-mediated wetting of ferrofluid droplets has emerged to be of fundamental importance because of its plethora of applications ranging from chemical and biomolecular analysis to soft robotics and medical imaging. However, while extensive studies continue to be reported on the underlying experimental facets, a fundamental theoretical depiction of the observed contact angle variation with the applied magnetic field remains grossly elusive, as attributable to a complex dependence of the induced magnetization on the droplet’s intrinsic magnetic properties. Circumventing these constraints, here we put forward a first-principle analytical model that delineates the variation in the contact angle as a function of an applied magnetic field on a sessile ferrofluid droplet, by appealing to energy minimization principles. One key feature of our analysis is the consideration of the local magnetization as a function of the magnetic field itself, resulting in a new contribution to the interfacial energy by virtue of normal traction at the droplet's contact with its non-magnetic surroundings. This theory is supported by experiments identified in prior research to elucidate the fundamental physics of relevance. Our results highlight the substantial influence of the saturation magnetization and the initial susceptibility of the ferrofluid on the resulting contact angle alterations, as well as possible non-trivial routes of highly selective and precise enhancement or attenuation in the extent of wetting. These findings are likely to be of fundamental importance towards establishing the design foundations of portable magnetic resonance imaging devices, micromixers, and microreactors, magnetically-manipulated automatic control of soft fluidic matters, among others.

Research on Path Tracking of Unmanned Spray Based on Dual Control Strategy

The high clearance spray is a type of large and efficient agricultural machinery used for plant protection, and path tracking control is the key to ensure the efficient and safe operation of spray. Sliding mode control and other methods are commonly used abroad to track vehicles, while fuzzy control, neural networks and other methods are commonly used at home. However, domestic and foreign research on autonomous agricultural machinery is mainly focused on tractors and other machinery, while research on self-propelled spray in high clearance is less abundant. This paper takes the path tracking algorithm in the integrated navigation system of spray as the main research goal, studies the path tracking control algorithm for straight lines and turning curves that can realize the automatic driving of spray by establishing the path tracking algorithm for unmanned spray based on dual control strategies, designs the path tracking controller, including the preview model theoretical path tracking controller and variable domain fuzzy controller, and determines the preview model through the design of the preview model theoretical path tracking controller. The lateral and longitudinal errors of the model algorithm are analyzed, and the driving characteristics under the complex spray road surface are analyzed. The design of the variable domain fuzzy predictor theory path tracking controller is proposed, and the design of the road model selection controller is calculated and analyzed in detail, including the determination of the road roughness coefficient and the selection of the range of the difference between the average value of the excitation before and after sampling, which improves the performance of the spray path tracking algorithm. The experiment shows that the proposed path tracking control algorithm can meet the path tracking requirements of unmanned spray in the current road environment, and provide a reliable solution for the automatic control of high clearance spray.

Model Predictive Control of Magnetic Helical Swimmers in Two-Dimensional Plane

Magnetic micro/mini-swimmers have a great potential application in biomedical research and have gained broad attention. Recent research studies focus on the automatic control methods of magnetic micro/mini-swimmers, such as artificial intelligence methods. However, their autonomous manipulation remains a challenge since they are subject to various disturbances from the external environment and model uncertainties. The current methods employ a status observer to estimate these disturbances and uncertainties. In this paper, we apply a data-driven technique that utilizes the nonlinear approximation ability of neural networks (NNs). To be specific, a flexible structure of NNs, Broad Learning System (BLS), is employed to model the input-output mapping relationship between the direction of the rotating magnetic field and the swimming direction of the helical miniature swimmer. Then, according to the dual-variable decoupling control, a levitation controller is formulated and a path following controller is proposed based on a planar three-degree-of-freedom model of magnetic helical swimmers, which is inspired by the model of wheeled mobile robots. Simulations and experiments are conducted to quantitatively validate the proposed control method using different planar paths. The experiment results show that the mean absolute error of the path following control is about 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula> of the body length which is less than 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$mm$</tex-math> </inline-formula> . Our proposed control method provides a preliminary study to alleviate the impact of disturbances and uncertainties on the control performance of magnetic micro/mini-swimmers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is mainly motivated by the potential application of artificial intelligence methods in magnetic micro/mini-robot community, especially for the applications that reject disturbances and uncertainties. In practice, a path planner is employed to compute a pre-defined reference path that connects the start and the targeted locations. Then our control method is applied to the magnetic helical swimmer and it is guided to follow the reference path. Tackling external disturbances and model uncertainties is still challenging during the control progress. Neural network-based technique is an intuitive approach since their nonlinear modeling ability and generalization are suitable for estimating these disturbances and uncertainties. As for training the neural-network model, the training data about the angle parameters should be recorded by manual control of the helical swimmer. These angle parameters define the rotating axis of the uniform rotating magnetic field and the self-rotating axis of the magnetic helical swimmer. According to the planar motion model, the optimal controller is formulated using the feedback distance error and angle error, and the sum of the control signal and the prediction of the compensating model is used as the final control input. Our electromagnetic coil system features easy operation and configuration of cameras or other sensors. Simulations and experiments validate the performance of the neural network-based compensating method and the proposed optimal control method using magnetic micro/mini-swimmers.