Robust Control System Research Articles

Adaptive terminal sliding mode control of hypersonic vehicles based on ESO

PurposeThis paper aims to solve the uncertainty problem of hypersonic vehicle tracking control; an adaptive terminal sliding mode control (TSMC) method based on extended state observer (ESO) is proposed. The combination of adaptive techniques, TSMC and ESO offers an effective approach for managing uncertain systems.Design/methodology/approachThe dynamic model of a hypersonic vehicle is transformed into two control-oriented subsystems. The control system design incorporates an adaptive technique, an ESO and a TSMC. The ESO estimates the primary uncertainties, while the adaptive technique determines the upper limit of secondary uncertainties. These estimates are used for the design of the TSMC law. In addition, the filter is used to generate the reference trajectory to improve the dynamic performance of the system. The stability of the closed-loop system is proved by the Lyapunov stability theory.FindingsA robust control system for hypersonic vehicles is developed with guaranteed stability and strong adaptability to various uncertainties such as parameter variations, external disturbances and actuator faults. Furthermore, the proposed system demonstrates enhanced dynamic performance compared to observer-based sliding mode control. Specifically, for the velocity and altitude tracking control, the settling time of the proposed sliding mode control is approximately 100 s and 70 s shorter than that of the observer-based sliding mode control, respectively.Originality/valueDifferent from the single equivalent treatment, various uncertainties here are classified and treated with different strategies, which improves the disturbance rejection ability of the control system. This ability is of great significance for enhancing the autonomy, adaptability and reliability of hypersonic vehicles in extreme environments.

Rotor Position Estimation Algorithm for Surface-Mounted Permanent Magnet Synchronous Motor Based on Improved Super-Twisting Sliding Mode Observer

In response to the chattering issue inherent in sliding mode observers during rotor position estimation and to enhance the stability and robustness of sensorless control systems for surface-mounted permanent magnet synchronous motors (SPMSM), this study proposes a rotor position estimation algorithm for SPMSM based on an improved super-twisting sliding mode observer (ISTSMO) and a second-order generalized integrator (SOGI) structure. Firstly, the super-twisting algorithm is introduced to design the observer, which effectively attenuates the sliding mode chattering by using continuous control signals. Secondly, SOGI is introduced in the filtering stage, which not only effectively addresses the time delay issues caused by traditional low-pass filters but also enables the observer to extract rotor position information by monitoring only the back electromotive force (back-EMF) signal of the α-phase, thereby simplifying the observer structure. Finally, the proposed scheme is experimentally compared with the traditional sliding mode observer on the YXMBD-TE1000 platform. The experimental results showed that during motor acceleration and deceleration tests, the average speed estimation error was reduced from 141 r/min to 40 r/min, and the maximum position estimation error was reduced from 0.74 rad to 0.29 rad. In load disturbance experiments, the speed variation decreased from 781 r/min to 451 r/min, and the steady-state speed fluctuation was significantly reduced. These results confirm that the proposed observer exhibits superior stability and robustness.

EMG Dataset for Gesture Recognition with Arm Translation

Myoelectric control has emerged as a promising approach for a wide range of applications, including controlling limb prosthetics, teleoperating robots and enabling immersive interactions in the Metaverse. However, the accuracy and robustness of myoelectric control systems are often affected by various factors, including muscle fatigue, perspiration, drifts in electrode positions and changes in arm position. The latter has received less attention despite its significant impact on signal quality and decoding accuracy. To address this gap, we present a novel dataset of surface electromyographic (EMG) signals captured from multiple arm positions. This dataset, comprising EMG and hand kinematics data from 8 participants performing 6 different hand gestures, provides a comprehensive resource for investigating position-invariant myoelectric control decoding algorithms. We envision this dataset to serve as a valuable resource for both training and benchmark arm position-invariant myoelectric control algorithms. Additionally, to expand the publicly available data capturing the variability of EMG signals across diverse arm positions, we propose a novel data acquisition protocol that can be utilized for future data collection.

An identification-based robust H∞ control of fouling in chemical reactor

In this article, a robust control algorithm is proposed for a nonlinear and time-varying continuous stirred tank reactor (CSTR) with sediment formation in the cooling jacket. The existing control schemes may fail, as deposition measurement or estimation is a challenge in such a process. As a main contribution, the deposition phenomenon is modeled here as the system uncertainty. Then, an identification-based robust integral controller is constructed for the underlying CSTR. Applying the loop-shaping procedure here is also a novelty to satisfy the performance objectives in the frequency domain. In a comprehensive scenario, which includes the set-point tracking in the presence of system uncertainties and external disturbance, the performance of the proposed robust control system is evaluated and discussed from a comparison viewpoint. The numerical study shows that fouling control and robust performance are ensured by the developed H∞-based technique.

Analysis and Synthesis of Disturbance Observer-Based Digital Robust Motion Control Systems in State Space

Analysis and Synthesis of Disturbance Observer-Based Digital Robust Motion Control Systems in State Space

Swarm-initialized adaptive controller with beetle antenna searching of wearable lower limb exoskeleton for sit-to-stand and walking motions.

In recent years, exoskeleton robots have attracted great interest from researchers in the area of robotics due to their ability to assist human functionality improvement. A wearable lower limb exoskeleton is aimed at supporting the limb functionality rehabilitation process and to assist physical therapists. Development of a stable and robust control system for multi-joint rehabilitation robots is a challenging task due to their non-linear dynamic systems. This paper presents the development of a Swarm-Initialized Adaptive (SIA) based controller, which is a combination of a swarm-based intelligence, named Swarm Beetle Antenna Searching (SBAS), and an adaptive Lyapunov-based controller. The SBAS initializes the parameters of SIA to efficiently improve the performance of the control system and then these controller parameters are updated by an adaptive controller. The control system is validated in a lower limb exoskeleton prototype with four degrees of freedom, using a healthy human subject for sit-to-stand and walking motions. The experimental results show the applicability of the proposed method and demonstrate that our approach obtained efficient control performance in terms of steady-state error and robustness and can be used for a lower limb exoskeleton to improve human mobility.

Improved Interconnected MRAS Parameter Identification for Speed Sensorless Control of Linear Induction Motor

After eliminating the speed sensor in the linear induction motor (LIM) high-performance closed-loop control system, the speed feedback information is missing in the speed closed loop. The accuracy of speed observation results is affected by changes in magnetizing inductance and primary resistance. This effect can cause significant oscillations in the results of the speed sensorless control system, preventing them from converging. An enhanced model reference adaptive system (MRAS) multi-parameter parallel identification methodology based on the interconnected second-order super-twisting algorithm (SOSTA) is proposed. To enhance the system’s dynamic performance, we designed an improvement to the MRAS observer based on the SOSTA, with a focus on the LIM state-space equation that considers dynamic edge-end effects. The impact of parameter alterations on the LIM system is examined. To improve speed observation accuracy and system stability, a two-parameter MRAS identification model was created. The Popov hyperstability principle was used to formulate control laws for these two parameters, ultimately enabling the identification of these two parameters. The identified values were fed back to the speed observation and control system, which reduces the coupling of these two parameters and speed. Simulation and hardware-in-the-loop experiments demonstrate that the observation system estimates speed accurately when these two parameters undergo abrupt changes within the rated speed range, enhancing the precision and robustness of the speed sensorless control system.

ANALYZING THE IMPACT OF THE ARMS TRADE TREATY ON HUMAN SECURITY: REGIONAL INSIGHTS

The Arms Trade Treaty (ATT), which was adopted by the General Assembly of the United Nations in 2013 and entered into force on December 24, 2014, is another important step forward for regulation of the trade in conventional arms and for mitigating some of the harmful effects of armed conflict on human security. This research article delves into the ATT’s implications for human security, emphasizing its role in preventing human rights abuses and promoting transparency and accountability in arms transfers. The ATT mandates comprehensive risk assessments by state parties before authorizing arms exports, ensuring that these transfers do not contribute to the human suffering or violate of international humanitarian law. By fostering international cooperation and robust national control systems, the treaty aims to curb the illicit arms trade, which exacerbates violence and hinders development, particularly in conflict-prone regions. The article highlights the ATT’s significance in integrating human security concepts into arms export controls, despite challenges in changing state behavior and the treaty’s limitations, such as the exclusion of non-state actors and emerging technologies. Through regional insights, the study examines the ATT’s impact on human security in Sub-Saharan Africa, the Middle East, Asia-Pacific and Europe. Identifying both successes and areas for improvement. This Article underscores the need for enhanced implementation strategies, political will, and international collaboration fully with the ATT is potential in safeguarding human security and promoting sustainable development in a world fraught with violence and instability.

Smart village: Evaluating the role of Siskeudes management in enhancing village fund accountability

Smart villages are basically about how rural communities make the best use of ICT and social innovation to create accountability. Rural communities worldwide are looking for solutions to improve suboptimal community services. Information and communication technology applications allow rural communities to improve their quality of life and provide excellent service. Smart villages are basically about how rural communities make the best use of ICT and social innovation to create accountability. The objective of this study is to investigate the impact of Siskeudes operator’s competence, training quality, and internal control on the accountability of village fund management mediated by Siskeudes usage. The study employed a questionnaire survey with village officials in Ketanggungan Sub-district, Brebes Regency, with a sample size of 105 people, decided employing the purposive technique. Descriptive analysis was used to clarify the general perceptions of the survey respondents and path analysis to explore the direct and indirect effect. The results point out a direct effect of Siskeudes operator’s competence, training quality, system of internal control, and Siskeudes usage on the village fund accountability. Furthermore, Siskeudes usage mediates Siskeudes operator’s competence, training quality, and system of internal control on accountability of village fund management. To ensure effective accountability reporting from village governments, it is important to strengthen officials' competencies, provide targeted training to improve operational efficiency, and implement robust control systems. In addition, the development of an integrated village financial system can facilitate transparent reporting and minimize the risk of misappropriation of funds.

Cells Prioritize the Regulation of Cell Mass Density.

A cell's global physical state is characterized by its volume and dry mass. The ratio of cell mass to volume is the cell mass density (CMD), which is also a measure of macromolecular crowding and concentrations of all proteins. Using the Fluorescence eXclusion method (FXm) and Quantitative Phase Microscopy (QPM), we investigate CMD dynamics after exposure to sudden media osmolarity change. We find that while the cell volume and mass exhibit complex behavior after osmotic shock, CMD follows a straightforward monotonic recovery in 48 hours. The recovery is cell-cycle independent and relies on a coordinated adjustment of protein synthesis and volume growth rates. Surprisingly, we find that the protein synthesis rate decreases when CMD increases. This result is explained by CMD-dependent nucleoplasm-cytoplasm transport, which serves as negative regulatory feedback on CMD. The Na + /H + exchanger NHE plays a role in regulating CMD by affecting both protein synthesis and volume change. Taken together, we reveal that cells possess a robust control system that actively regulates CMD during environmental change.

Adaptive Prescribed-Time Nonlinear Control for Chain Magazine

Abstract To address the issue of the chain magazine system failing to achieve stability within a specified timeframe during operation and to enhance the precision and robustness of its performance, an adaptive prescribed-time robust controller (APTRC) was designed for position control of the chain magazine. The newly introduced controller enables the system to reach stability within the designated time, regardless of initial conditions, thereby improving the robustness of control system against uncertainties and external disturbances. The stability of the controller itself and the closed-loop system was verified using the Lyapunov stability criterion. Simulation results indicate that the controller achieves the desired performance with high control accuracy under three different load conditions: no load, half load, and full load.

Robust Control System Tuner and Cascaded Adaptive Vectorial Filter-Based PV-Battery System With a Dual-Loop ANF-PLL

Robust Control System Tuner and Cascaded Adaptive Vectorial Filter-Based PV-Battery System With a Dual-Loop ANF-PLL

IntelliDoor: Smart Access Control System with Automated Door Operation

Abstract: The Intelligent Access Control System with Automatic Door Operation is a project aimed at providing secure and efficient access control using artificial intelligence (AI) and automated door mechanisms. This system utilizes facial recognition technology for user identification, Firebase for data storage and management, and Arduino for controlling the automatic door operation. The objective is to develop a robust and intelligent access control system that automatically identifies authorized individuals through facial recognition and opens the door for them. The system also maintains a record of entry for each individual for attendance tracking or security purposes. The project features include facial recognition, automatic door operation, Firebase integration, an alert system, and real-time monitoring. The project workflow involves initialization, facial recognition, recognition results, database updates, and automatic door operation. The project report covers the introduction, literature review, methodology, implementation, results, and conclusion. The Intelligent Access Control System with Automatic Door Operation provides an efficient and secure solution for access control, enhancing security while offering convenience. With further refinement and integration, it has the potential to become a standard solution for access control in modern buildings and facilities.

Implementing Situational Crime Prevention Theory in the Matter of Financial fraudulent

Fraud and financial crime continue to pose significant challenges for private companies, making prevention efforts essential through the identification of their root causes. This study examines the relationship between situational crime prevention and financial fraud, with a focus on employee tenure as a moderating variable. An empirical research method was employed, with data collected from employees of PT Budi Jaya and its subsidiaries through questionnaires. A total of 60 valid responses were analyzed using WarpPLS. The findings reveal that situational crime prevention—measured through indicators such as minimal benefits, high risks, limited opportunities, and strict sanctions—has a significant negative impact on financial fraud. Additionally, the study demonstrates that employee tenure moderates the relationship between situational crime prevention measures and financial fraud. This research makes a theoretical contribution to situational crime prevention theory by incorporating the concept of rationalization, which fraud perpetrators often use to justify their actions. The study offers practical insights, suggesting that companies and regulators should implement robust internal control systems to minimize opportunities for fraud and establish clear, stringent rules and sanctions to deter fraudulent behavior.

Analysis of potential risks during the control of an unmanned underwater vehicle (UUV)

This article explores the analysis of potential risks associated with controlling unmanned underwater vehicles (UUVs), focusing on operational, environmental, and technological challenges. UUVs play a critical role in marine research, defense, and offshore industries but are subject to unique risks due to limited visibility, communication latency, and unpredictable underwater conditions. While UUVs have revolutionized underwater exploration and navigation, their reliance on advanced technologies introduces unique challenges. The study identifies the primary risk domains of UUV operations, including operational risks, human-machine interaction vulnerabilities, and environmental unpredictability. Using comprehensive scenario analysis and data from practical implementations, the article evaluates key risks such as navigation errors, system malfunctions, and communication disruptions. It further examines how artificial intelligence (AI) can be leveraged to mitigate these risks through real-time trajectory optimization, adaptive learning, and enhanced situational awareness. This research incorporates scenario-based analyses for UUVs to evaluate the most critical risk factors affecting mission safety. Furthermore, it explores how modern technologies can mitigate these risks by enhancing trajectory optimization and monitoring of UUVs during underwater navigation. By providing a holistic understanding of UUV risks, the findings underscore the need for robust control systems and operator training protocols. The research contributes actionable insights for improving UUV safety, efficiency, and reliability, laying the groundwork for further advancements in maritime robotics

Asymmetric full-state constrained attitude control for a flexible agile satellite with multiple disturbances and uncertainties

In this paper, an asymmetric full-state constrained attitude control method for a flexible agile satellite with multiple disturbances and uncertainties is proposed. Both the attitudes and angular velocities of the flexible agile satellite are guaranteed in the asymmetric/symmetric bounds by utilizing the time-varying integral barrier Lyapunov function (TVIBLF) and constant integral barrier Lyapunov function (IBLF) respectively. Compared with the existing error-based barrier Lyapunov functions, the asymmetric TVIBLF does not need error transformation, relaxes the conservation of the initial requirements, and has more compatibility. Furthermore, the proposed asymmetric TVIBLF can deal with the asymmetric time-varying constraints without loss of generality. In addition, the high-frequency flexible vibrations, inertial uncertainties, and unknown external disturbance torques affected on the agile satellite are considered respectively. On one hand, a modal observer is utilized to suppress the high-frequency flexible vibration effects on the attitudes. On the other hand, the inertial uncertainties and unknown external disturbance torques are estimated with a multi-variable nonlinear disturbance observer. Therefore, both the asymmetric full-state constrained performances and robustness of the attitude control system for the flexible agile satellite are achieved. The stability of the closed-loop system is proved and numerical simulations have validated the effectiveness of the proposed method.

Simulation and evaluation of lateral/directional dynamics in an aircraft autopilot control system

The objective of the research was to design and simulate the lateral/directional dynamics control of an aircraft’s autopilot system to automate the landing approach execution, complying with the requirements of the Instrument Landing System (CAT III C). The design methodology involved integrating a Linear Quadratic Regulator (LQR) with Affine Parameterization techniques to create a robust control system. The prototype was developed using Matlab and simulated in Simulink. Through various simulations, adjustments were made to the Q and R matrices of the LQR controller based on Bryson’s rule, allowing the system to adapt to the nonlinearities and dynamic constraints of the aircraft model. These adjustments included modifying the lateral attitude control parameters to achieve the desired damping factors and time constants, ensuring flight quality standards according to MIL-8785C. Validation under real conditions through a flight simulator confirmed the control system’s effectiveness under various operational conditions. The controllers are able to maintain the aircraft’s alignment with the runway centerline, even in the presence of external disturbances, thus demonstrating the system’s robustness and reliability. The methodologies and results provide a solid foundation for future improvements and comparative analyses of autopilot systems within CAT III C requirements.

Event‐Triggered Robust Control of Robot Manipulators

ABSTRACTThis paper proposes a new event‐triggered robust control system for robot manipulators, based on two event‐triggered mechanisms (ETMs), which lead to intermittent communication not only for the sensor‐to‐controller channel but also for the controller‐to‐actuator channel. The proposed control system enjoys the advantage of requiring fewer resources of data communication and less signal updating of the control actuators. The control performance of the proposed control system is analyzed based on the Lyapunov approach. Furthermore, the absence of the Zeno behavior in the triggering sequence is proved rigorously. Finally, experiments are carried out on a two‐link robot manipulator system to support the theoretical results.

Adaptive algorithms for drone flight control under communication constraints and information incompleteness

Abstract With the rapid increase in the use of drones in various applications, including commercial and governmental, and the increasing probability of communication failures and contingencies, research becomes critical to ensure the safety and efficiency of their operations. The aim of this research is to develop adaptive drone flight control algorithms capable of operating effectively under conditions of limited communication and incomplete information to ensure reliable and safe autonomous operation of these systems. The applied methods include computer modelling and simulation, analytical, statistical, functional, deductive and descriptive methods. The study found that the use of performance evaluation methods for complex systems enables the identification of safety and performance criteria for drones, and drone flight control provides basic principles and methods that can be adapted for drones, including autopiloting and navigation. In addition, analyses of satellite communication and navigation prove the need to consider the limitations of this technology when developing drone control algorithms. The combination of these techniques allows for more robust and adaptive drone control systems that can function effectively in complex environments such as communication limitations and incomplete information. Additionally, it was found that the integration of adaptive control algorithms based on these methods allows drones to effectively adapt to variable environmental conditions and make decisions quickly even when communication is lost or information is limited.

A Bayesian-Based Credible and Reliable Control Method for Active Vibration Suppression of Structures with Uncertain Parameters

As a classical design method for addressing uncertainty in control systems, robust control is designed with the goal of complete reliability of the control system. Nevertheless, the pursuit of robustness can inadvertently give rise to considerable performance degradation, rendering the resultant closed-loop control system excessively conservative in its design. Reliability-based design methods serve as an effective approach for managing uncertainties, which will achieve a balance between the robustness and performance of the active control system by taking advantage of the characteristic of reliability that allows for a certain level of permissible failure probability. The accurate quantification of uncertainty is the key to achieving reliable control, but common uncertainty quantification methods cannot achieve credible quantification of uncertainty in small samples and update the distribution of new samples. In this paper, a nonprobabilistic Bayesian inference based interval uncertainty quantification method is proposed. This method updates the distribution of interval boundaries and radii by introducing a small number of samples, and obtains interval parameters under a given confidence level. On the basis of uncertainty quantification, the dynamic reliability of the vibration system is derived, and nonprobabilistic reliability is introduced into the design of active controllers through optimization strategies. The reliable control strategy aims to select the optimal controller parameters on a reliable path with a given credibility, in order to solve the problem of overly conservative robust control theory. Two numerical examples were used to verify the feasibility and applicability of this method.