Entire Control Research Articles

LiDAR-assisted closed-loop control of a wind farm

Abstract A common approach to perform wake steering control in wind farms, involves using pre-calibrated, low-fidelity wake models. Due to their low computation time, these models can be efficiently used to precalculate the yaw angles that maximize the total wind farm power across a wide range of wind conditions. This “open-loop” control strategy, however, is highly dependent on the accuracy of the model. Any errors in the model can lead to suboptimal power output. To overcome this issue, a “closed-loop” control method can be used, which leverages available measurements to adjust certain model parameters, ensuring a closer alignment with the actual operation of the wind farm. To implement this closed-loop approach, a new control-oriented wake model is presented, designed to be adapted in real time using measurements from the wind farm. These measurements are assumed to come from nacelle-mounted multi-range LiDAR sensors, which provide partial wind field data. The entire closed-loop control scheme is validated using the medium-fidelity dynamic simulator FAST.Farm. Several wind condition scenarios are tested, all showing a significant increase in the total power output of the wind farm.

ПОКРАЩЕННЯ ЯКОСТІ РЕГУЛЮВАННЯ АСИНХРОННОГО ЕЛЕКТРОПРИВОДА З КЕРУВАННЯМ ЗА РЕАКТИВНОЮ ПОТУЖНІСТЮ

In addition to the known properties of an asynchronous electric drive with reactive power control - ensuring high speed in the entire multipolar speed control range, including zero, independence of mechanical torque from changes in the parameters of the asynchronous motor - the peculiarity of its operation at frequencies close to zero with a loaded motor is considered and an adaptation is proposed to ensure compliance with the set and actual speeds when changing the parameters of the asynchronous motor. The supplier of the electric drive can be Zaporozhye Electrical Equipment Plant, LLC "Electronics, LTD" can participate in the coordination of technical conditions. References 6, Figures 5.

High-Precision Landing on a Moving Platform Based on Drone Vision Using YOLO Algorithm

High-precision landing is a key technical problem that Unmanned Aerial Vehicles (UAVs) will encounter in all application fields, especially for the landing of moving targets. This paper focuses on developing a landing system designed to achieve real-time precise navigation by integrating the Global Navigation Satellite System (GNSS) with the quadcopter’s vision data. To overcome the challenge of the flight altitude being too high to detect the landing target, this paper first detects large-volume targets, followed by the precise identification of smaller targets, achieving enhanced recognition accuracy and speed through an improved YOLOv8 OBB algorithm. To maintain the UAV’s safety and stability throughout the landing process, this paper applies a position control approach using a reference model-based sliding mode controller (RMSMC). The quadcopter’s position is then controlled by the RMSMC throughout the entire landing procedure. The reference value of each state is determined by the reference model, which improves the stability and safety of the entire position control system. During the final experiment, the results demonstrate that the enhanced YOLOv8 OBB identification model increases the mAP0.5:0.95 index for landing target point detection by 2.22 percentage points compared to the original YOLOv8 OBB model, running at 53 FPS on Nvidia AGX. Through multiple actual flights, the proposed landing system consistently achieves an average position error of just 0.07 m.

IMPLEMENTATION OF SECURE TRAFFIC LIGHT MANAGEMENT USING A NEUROMORPHIC COMPUTING BASE BASED ON FUZZY GRAPHS

The task of safe traffic light management is to normalize traffic. Secure management involves the implementation of the protection of information involved in the management process. The traffic light management process is a complex dynamic process. The control object is a set of traffic lights. The subject of management is a specific management system, which can be autonomous or part of a top-level management system. The implementation of a traffic light based on a neuromorphic computing base allows you to perform some of the control processes in automatic mode. As part of the control process, you have to deal with different types of data (sensor readings, control signals of different levels, etc.). Big data is processed throughout the entire control process, and one of the main tasks is to reduce the dimensionality of the information being processed. The successful solution of this problem directly depends on the model of organization of a set of traffic lights. The article discusses various traffic lights, each of which is equipped with an intelligent controller. The neuromorphic basis of the intelligent controller allows you to expand the capabilities of the computing base at a low level. Fuzzy graphs are used to represent a set of traffic lights and to connect the traffic lights to the control system. This model makes it possible to combine the information and control components of the process of interaction between the object and the subject of management into one whole. The advantages of this representation are the minimization of information necessary for the successful solution of the problem of safe management, and the expansion of the possibilities of the management process through the use of fuzzy information.

“We do not always enjoy surprises”: investigating artificial serendipity in an online marketplace context

PurposeThis study aims to gain a better understanding of artificial serendipity – pre-planned surprises intentionally crafted through deliberate designs – in online marketplaces. By exploring the key features of artificial serendipity, this study investigates whether serendipity can be intentionally designed, particularly with the use of artificial intelligence (AI). The findings from this research broaden the scope of serendipity studies, making them more relevant and applicable in the context of the AI era.Design/methodology/approachA narrative study was conducted, gathering insights from 32 Chinese online consumers through diaries and interviews. The data were analysed in close collaboration with participants, ensuring an authentic reflection of their perceptions regarding the features of artificial serendipity in online marketplaces.FindingsFindings reveal that artificial serendipity, particularly when designed by AI, is still regarded by online consumers as genuine serendipity. It provides a sense of real surprise and encourages deeper reflection on personal knowledge, affording the two central qualities of genuine serendipity: unexpectedness and valuableness. However, since artificial serendipity is pre-planned through intentional design, consumers cannot have entire control over it. Therefore, compared to natural serendipity – fortune surprises arising from accidental correspondence between individuals and contexts – artificial serendipity tends to be more surprising yet less valuable.Research limitations/implicationsFor research, it highlights the potential of intelligent technologies to facilitate genuine serendipity, updating our understanding of serendipity.Practical implicationsAlso, the study provides practical insights into designing serendipity, especially in online markets. These contributions enrich both the theoretical framework and practical strategies surrounding serendipity in the era of AI.Originality/valueThis study stands out as one of the few to provide a nuanced understanding of artificial serendipity, offering valuable insights for both research and practice. For research, it highlights the potential of intelligent technologies to facilitate genuine serendipity, updating our understanding of serendipity. Also, the study provides practical insights into designing serendipity, especially in online markets. These contributions enrich both the theoretical framework and practical strategies surrounding serendipity in the era of AI.

A Control Method for Thermal Structural Tests of Hypersonic Missile Aerodynamic Heating

This paper presents an intelligent proportional-derivative adaptive global nonsingular fast-terminal sliding-mode control (IPDAGNFTSMC) for tracking temperature trajectories of a hypersonic missile in thermal structural tests. Firstly, the numerical analyses on a hypersonic missile’s aerodynamic heating are based on three different external flow fields via the finite element calculation, which provides the data basis for the thermal structural test of hypersonic vehicles; secondly, due to temperature trajectory differences of a hypersonic missile and the thermal inertia and nonlinear characteristics of quartz lamps in thermal structural test, IPDAGNFTSMC is proposed, consisting of three components: (i) the mathematical model of the thermal structural test is established and further replaced via an intelligent proportional-derivative with a nonlinear extended state observer (NESO) for online unknown disturbances observation; (ii) compared with the traditional sliding-mode control method, the AGNFTSMC method eliminates the reaching phase and the initial control state is trapped on the sliding-mode surface. Therefore, it can alleviate chattering phenomenon, accelerate the convergence rate of the sliding mode, and ensure that there is no singular problem in the entire control process; (iii) the adaptive law is designed to effectively solve problems of convergence stagnation and chattering phenomenon. The Lyapunov stability theory is used to prove the stability of the proposed IPDAGNFTSMC-NESO. Finally, the advantages of the designed control method are verified by experimental simulation and comparison.

Robust adaptive fuzzy type-2 fast terminal sliding mode control of robot manipulators in attendance of actuator faults and payload variation

Introduction. This study presents a robust control method for the path following problem of the PUMA560 robot. The technique is based on the Adaptive Fuzzy Type-2 Fast Terminal Sliding Mode Control (AFT2FTSMC) algorithm and is designed to handle actuator faults, uncertainties (such as payload change), and external disturbances. The aim of this study is to utilize the Fast Terminal Sliding Mode Control (FTSMC) approach in order to ensure effective compensation for faults and uncertainties, minimize tracking error, reduce the occurrence of chattering phenomena, and achieve rapid transient response. A novel adaptive fault tolerant Sliding Mode Control (SMC) approach is developed to address the challenges provided by uncertainties and actuator defects in real robotics tasks. Originality. The present work combined the AFT2FTSMC algorithm in order to give robust controllers for trajectory tracking of manipulator’s robot in presence parameters uncertainties, external disturbance, and faults. We use an adaptive fuzzy logic system to estimate the robot’s time-varying, nonlinear, and unfamiliar dynamics. A strong adaptive term is created to counteract actuator defects and approximation errors while also guaranteeing the convergence and stability of the entire robot control system. Novelty. The implemented controller effectively mitigates the chattering problem while maintaining the tracking precision and robustness of the system. The stability analysis has been conducted using the Lyapunov approach. Results. Numerical simulation and capability comparison with other control strategies show the effectiveness of the developed control algorithm. References 53, table 1, figures 8.

Practical Fixed-Time Robust Containment Control of Multi-ASVs with Collision Avoidance

A practical fixed-time robust containment control method for multiple autonomous surface vehicles (multi-ASVs) is proposed in this study. This method addresses the containment control problem of multi-ASVs, considering both collision risks and external disturbances. This control scheme improves the cooperative performance of the formation and guarantees safe collision avoidance behavior. First, to enable the online estimation of unknown time-varying disturbances from the external environment, a fixed-time disturbance observer (FNDO) is designed based on fixed-time control theory. Second, the distributed kinematic controller is modified to include the partial derivatives of the artificial potential energy function (APEF), thereby preventing collisions among multi-ASVs. Third, by applying fixed-time theory, graph theory, and fixed-time dynamic surface control techniques, a practical fixed-time robust containment controller for multi-ASVs is proposed. Additionally, the entire closed-loop control system is guaranteed to be practical and fixed-time stable through stability analysis. Finally, the proposed control strategy has been validated by simulation results.

Speed harmonization with enhanced precision

Speed harmonization using connected and automated vehicles (CAVs) is one of the most effective strategies for preventing capacity drops. However, existing methods often face challenges in managing heavy traffic and ensuring highly responsive demand control in various situations. This research introduces an enhanced speed harmonization controller that partitions the control zone and employs a cooperative strategy across these partitions. This design optimizes the performance of the control zone and provides three key benefits: (i) improved handling of heavier traffic, (ii) more responsive flow regulation, (iii) producing steadier flow. To evaluate the controller, a microscopic simulation evaluation was conducted. Sensitivity analysis was performed for CAVs’ penetration rate (PR), demand level (v/c ratio). Results show that: compared to state-of-the-art method, the capability for handling flow is improved about 35%. The response efficiency is generally improved by 12–20%. The control smoothness is ensured during entire control process, speed fluctuation is within 0.025 m / s 2 . The capability for handling flow and response efficiency are enhanced with the increase of demand and PR. The control smoothness during entire control process is still ensured no matter how the demand and PR change.

Data Fusion Approaches for Authenticating and Evaluating Quality of Food and Beverages

The increasing interest of customers in the safety, authenticity and quality of food products has led to greater attention being paid to the nondestructive methods used to check them. In recent years, fast and reliable sensing and spectroscopic, together with multivariate and multipath chemometrics, have improved the entire control process by reducing analysis time and providing more informative results. As more and better data become available, combining the outputs of different instrumental methods has emerged as a way to increase the reliability of nondestructive food classification or prediction compared to using a single analytical method. While promising results have been obtained in the authentication and quality assessment of food and beverages, the integration of data from multiple techniques poses a significant challenge for chemometrics. This paper provides a general overview of data integration techniques that have been used in the field of food and beverage authentication and quality assessment.

Evaluation of urine protein to creatinine ratio in sighthound breeds.

The breed can influence the results of haematological and biochemical blood tests, with sighthounds traditionally mentioned. It may also affect certain urinary parameters. This study aimed to compare urinary protein and creatinine concentrations and their ratio (UPC, urine protein to creatinine ratio) between sighthounds and non-sighthounds and to evaluate these parameters in various sighthound breeds. Urine samples from clinically healthy dogs were collected via normal voiding, representing both sighthound and non-sighthound breeds. The protein and creatinine concentrations in the urine samples were determined, and their ratio was subsequently calculated. A total of 191 urine samples from sighthounds and 90 urine samples from non-sighthound breeds used as a control group were evaluated in the study. In sighthounds, significantly lower urinary protein concentration (248.8 mg/l and 299.8 mg/l, respectively; P = 0.045) and significantly higher urinary creatinine concentration (23.0 mmol/l and 17.5 mmol/l, respectively; P = 0.000) and lower UPC values (0.13 and 0.18, respectively; P = 0.000) were observed in comparison to the entire control group. The UPC values were found to be significantly lower in Greyhounds and Spanish Greyhounds compared with non-sighthounds. Although statistically significant changes were identified, they are unlikely to be of great clinical importance.

Variable-structure trajectory correction control of small-caliber ammunition based on cascade fuzzy active disturbance rejection

In this study, a low-cost two-dimensional (2D) trajectory correction mechanism is proposed to address the large trajectory deviation of small-caliber extended-range ammunitions. By controlling the projectile’s roll, a single-channel 2D trajectory correction function can be realized. Moreover, based on the ideal trajectory, a five-degree-of-freedom approximate rigid-body trajectory equation is proposed. A high-order system is transformed into two low-order cascading subsystems using fuzzy control and the self-disturbance rejection control theory, which reduces the parameter tuning complexity. The entire control process is divided into three stages which realizes the second-order variable structure control of non-affine nonlinear subsystems. A low-altitude atmospheric disturbance model is established, and as an example, numerical calculations are performed on the control process and projectile impact point dispersion of a 35 mm small-caliber rocket. The results verify the performance of the proposed trajectory correction under atmospheric disturbances. This study provides a control approach for coupled underactuated nonlinear systems and provides guidance for the design of a low-cost 2D trajectory correction controller for small-caliber ammunitions.

Shaking Table Test Studies on Adaptive-Passive Variable Frequency Gas-Spring DVA for Structural Seismic Response Mitigation

The control performance of a passive dynamic vibration absorber (DVA) is known to be sensitive to its frequency deviation. This study upgrades the conventional device and proposes an adaptive-passive variable frequency gas-spring DVA (APVF-GSDVA) for controlling the structural seismic response, while an adaptive control algorithm is developed that requires only a single input signal. The DVA’s vibration frequency is precisely modulated by adjusting the gas pressure in the gas-spring, aligning it with the inherent frequency of the multi-degree-of-freedom (MDOF) structure. The working principle and control algorithm of the APVF system is introduced and derived in detail, the corresponding gas-spring DVA and implementation are designed, and the configuration of the entire control system is realized. An adaptive variable frequency test scheme is designed and the frequency retuning function of the prototype APVF-GSDVA device installed on an MDOF structure is experimentally validated. The seismic response control effectiveness of the retuned DVA is demonstrated by comparing the detuned DVA, highlighting the necessity of implementing adaptive frequency adjustment of the gas-spring DVA. Experimental findings demonstrate that APVF-GSDVA accurately identifies the inherent frequency of the MDOF structure in ambient excitation, it then adjusts the pressure of the gas-spring according to the frequency-pressure relationship, optimally retuning the DVA. A retuned GSDVA can effectively suppress the structural seismic responses, compared to a detuned DVA, its control effectiveness on peak and RMS responses can be improved by a maximum of nearly 13.5% and 53.3% at a frequency deviation of 10%. Furthermore, results from two “detuning-retuning” test paths with distinct seismic excitations indicate that the retuned DVA exhibits superior control effectiveness, underscoring the significance of the adaptive frequency adjustment function in passive DVAs.

Protection Against Coronary Atherosclerosis in High Cardiovascular Risk Sickle Cell Disease Patients: A Beneficial Role of Intravascular Hemolysis?

Protection Against Coronary Atherosclerosis in High Cardiovascular Risk Sickle Cell Disease Patients: A Beneficial Role of Intravascular Hemolysis?

Priority-based QoS Extensions and IAM Improvements

The command and control system operates in a harsh and dynamic environment with limited resources and have a very high risk of failure or malfunction. In the case of military information systems, including the command and control system, the efficiency and effectiveness of system resource management are very important and required. Therefore, the application of a QoS-like approach is necessary to improve the operational effectiveness of all command and control system resources. However, supporting QoS at the entire command and control system level incurs additional costs and burdens for implementation and operation. This paper describes the necessity and possibility of collaboration with QoS and IAM (identity and access management) among the collaboration between core functions within the command and control system. This paper proposes an extended QoS approach to improve the operational effectiveness of the entire command and control system resources. As a result of this research, expanded concepts, structures, standards, and methods of collaboration between QoS and IAM are developed and presented, and their feasibility is demonstrated through prototype development and experiments.

Prescribed Fixed-Time Control for Constrained Uncertain Nonlinear Cyber-Physical Systems Against Deception Attacks.

In this note, a novel prescribed fixed-time adaptive tracking control scheme is developed to cope with the fixed-time tracking control issue for a category of constrained MIMO nonlinear cyber-physical systems (CPSs) with exogenous perturbations, which suffer from deception attacks started in controller-actuator (C-A) channel. Distinguished from the conservative dynamic surface control (DSC) schemes with a linear filter, a novel nonlinear filter is designed in our strategy, which can tackle the intrinsic issue of explosion of computational complexity and promote the system performance. Besides, a new barrier Lyapunov function (BLF) is designed to ulteriorly enhance the tracking performance on the basis of the prescribed performance function (PPF) approach. Prominently, the proposed control strategy could accommodate the exogenous interferences and deception attacks simultaneously. Furthermore, we have substantiated that the developed approach can not only make certain that all the tracking errors of the resulting closed-loop system, including output tracking errors and virtual tracking errors, enter a prespecified small region near equilibrium point with fixed-time convergence rate, but also guarantee them obey the corresponding constraints throughout the entire control operation, where the regulation time and the tracking accuracy level keep prior known and could be prespecified arbitrarily. Finally, the validity and effectiveness of the proposed control scheme are illustrated through a representative application instance.

Valid RBFNN Adaptive Control for Nonlinear Systems With Unmatched Uncertainties.

In this article, an adaptive tracking controller based on radial basis function neural networks (RBFNNs) is proposed for nonlinear plants with unmatched uncertainties and smooth reference signals. The concept of valid RBFNN adaptive control is introduced where all closed-loop arguments of the involved RBFNNs should always remain inside their corresponding compact sets. Considering the local approximation capacity of RBFNNs, validity requirements are necessary for ensuring reliable closed-loop approximation accuracy and stability. To obtain valid RBFNN adaptive controllers, a novel iterative design method is proposed and embedded into the traditional backstepping approach. In the initial iteration, an ideal RBFNN and its online estimated version are introduced in each step where the initial compact set guarantees the validity requirement for only a finite time interval. Then, by carefully investigating the dependence among different signals and introducing some auxiliary variables, the compact sets are redesigned for prolonging the time interval satisfying validity requirements to infinity as the iteration goes on. Consequently, a closed-loop system model can be formulated during the entire control process, which underlies a rigorous proof on closed-loop stability and some guidelines on practical implementation. Meanwhile, rigorous analysis from validity requirements reveals, for the first time, a new feature of RBFNN adaptive controllers in the presence of unmatched uncertainties: excessively large scales of RBFNNs in intermediate steps may impair the closed-loop performance. Finally, simulation results are provided to illustrate the efficiency and feasibility of the obtained results.

Relay Switching–Based Event‐Triggered Finite‐Time Tracking Control for Nonholonomic Systems: Theory and Experiment

ABSTRACTThis paper investigates the event‐triggered finite‐time trajectory tracking controller based on a type of chained‐form nonholonomic systems under unknown disturbances by utilizing relay switching technology. A key design idea is that the entire control design is grouped into two separated control stages to produce different finite‐time tracking controllers with correspondingly event‐triggered control rules. By using some nonlinear design methods, a relay switching–based event‐triggered finite‐time tracking control method is adopted to assure that the resulting closed‐loop tracking error system converges to an arbitrarily small neighborhood around zero within a finite time. All closed‐loop error system states keep bounded throughout the entire process. Simulation and experiment results demonstrate the rationality of the designed tracking control strategy.

Design and Signal-Decoding Test Verification of Dual-Channel Round Inductosyn Decoding Circuit

During the in-orbit operation of spacecraft, permanent magnet synchronous motors are commonly used as power sources in the drive mechanisms of solar panel arrays and the high-precision servo control systems based on satellites. Apart from the performance of the motors themselves and the software control algorithms, the accuracy of the entire control system is also influenced by angle sensors used to detect the rotor position of the motors. As a high-precision angular measuring instrument, the inductosyn possesses excellent environmental adaptability and long service life. Effectively utilizing the inductosyn can greatly enhance the performance of servo control systems. To address the complexity of the decoding process for dual-channel round inductosyn-to-digital converters, this paper proposes a design of the decoding circuit for dual-channel round inductosyn based on the parallel-synchronization decoding method of two AD2S1210 Resolver-to-Digital Converter (RDC) decoding chips. The decoding circuit amplifies the excitation signal outputted by the AD2S1210 for driving the round inductosyn, and processes the sine and cosine induction signals outputted by the round inductosyn through filtering, amplification, and other methods; by using analog circuitry, the output signals of the dual-channel round inductosyn are processed to meet the input requirements of the AD2S1210. Finally, through both the Multisim (circuit simulation software Version 14.1) simulation and physical experiments, it was verified that the decoding circuit designed in this paper could process the input/output signals of the dual-channel round inductosyn and AD2S1210, and successfully decoded the analog induction signal of the round inductosyn. This greatly simplifies the signal decoding process for the dual-channel round inductosyn.

Trajectory tracking control of underactuated unmanned underwater vehicle without speeds measurement

When unmanned underwater vehicles (UUVs) navigate on the surface, the UUVs’ speed cannot be accurately measured due to the humid environment. This can lead to a decrease in trajectory tracking control accuracy, and in severe cases, it may lead to controller failure. To solve this problem, a novelty speed observer based on real-time position state is proposed, and the UUV trajectory tracking controller is designed based on this observer. First, a speed observer with position status based on the UUV surface navigation kinematics model is proposed. Considering the impact of environmental disturbances, a disturbance observer is designed to observe surge, sway, and yaw torque disturbances. Next, a virtual control law is designed based on speed observations and reference trajectories to solve control laws. Considering the saturation input problem of the UUV driver, a command filter is introduced to constrain the amplitude and speed of the virtual control law. Then, a trajectory tracking sliding mode controller is designed using the virtual control law and the output of the command filter. Meanwhile, the disturbance of surge torque and heading torque is compensated with the observed value of the disturbance observer. The stability of the entire closed-loop control system is analyzed using Lyapunov’s stability theory. Finally, a series of numerical simulations are added to illustrate the method’s effectiveness.