Robust Control Research Articles

Robust dynamic real-time control strategies for high-frequency bus service: a multi-agent reinforcement learning framework

Robust dynamic real-time control strategies for high-frequency bus service: a multi-agent reinforcement learning framework

Robust model predictive control for polyhedral uncertain systems under relay and redundancy protocol

Robust model predictive control for polyhedral uncertain systems under relay and redundancy protocol

Etiology, risk factors and outcomes of bacteremia in patients with hematologic malignancies and febrile neutropenia in Uganda

Abstract Background We determined the etiology, risk factors and outcomes associated with bacteremia in patients with hematologic malignancies and febrile neutropenia (FN) at the Uganda Cancer Institute (UCI). Methods UCI adult and pediatric inpatients with hematologic malignancies and FN were prospectively enrolled and followed up to determine 30-day mortality. Blood drawn from participants with FN was cultured in the BACTEC 9120 blood culture system. Antimicrobial susceptibility testing was performed with the disk diffusion method on identified bacteria. Logistic regression and Cox proportional hazards regression were applied to estimate associations between participant characteristics and FN, bacteremia, and mortality. Results Of 495 participants, majority (N=306, 62%) were male. Median age was 23 years (IQR:11-42 years). Of the 132 participants who experienced FN, 43 (33%) had bacteremia. Participants with younger age (OR:0.98, p=0.05), severe neutropenia (OR: 2.9, p=0.01), hypotension (OR: 2.46, p=0.04), mucositis (OR: 2.77, p=0.01) and receiving chemotherapy (OR:2.25, p=0.03) were more likely to have bacteremia. Fifty (78%) bacteria isolated were Gram negative. E. coli (n=25, 50%) was predominant. Thirty-seven (86%) out of 43 episodes were caused by multidrug resistant (MDR) bacteria. 30-day overall survival for participants with bacteremia was significantly lower than that for participants with no bacteremia (p=0.05). MDR bacteremia (HR=1.84, p=0.05) was associated with increased risk of death. Conclusion Bacteremia was frequent in patients with hematologic cancer and FN and was associated with poor survival. MDR bacteria were the main cause of bacteremia and mortality. There is a need for robust infection control and antimicrobial stewardship programs in cancer centers in sub-Saharan Africa.

Type-2 fuzzy adaptive robust fault-tolerant control for manipulators with disturbance observer

A configuration of interval type-2 (IT2) fuzzy adaptive fault-tolerant control strategy is designed for the position trajectory tracking of cooperated robot manipulators carrying a common object. First, a non-zero time-varying parameter is installed in IT2 FLS, then a property of universal approximation of IT2 fuzzy logic system (FLS) is proposed, where the non-zero time-varying parameter has the relation with the approximation precision of IT2 FLS. Second, for the unknown compounded disturbance, a disturbance observer is designed to estimate it and is integrated into the IT2 adaptive control. To improve the approximation accuracies, the novel IT2 FLSs with non-zero parameter are utilized to compensate for the uncertain nonlinear terms with including the uncertainties and fault components in the system, the fault-tolerant control with some adaptive laws are established using the stability theory of barrier Lyapunov function (BLF), where the approximation accuracies can be modified online using the provided adaptive laws with neglecting the number of fuzzy rules, the computation burden of the proposed control is greatly reduced because of a small number of updated laws. Finally, the simulation results are compared with those of several existing control methods, which confirms the validity of the designed control approach.

Anti-disturbance adaptive cruise control method based on H∞ robust controller with optimized safe velocity and following time headway

Abstract To alleviate driver workload, many vehicles are now equipped with adaptive cruise control (ACC) systems. However, ACC performance can significantly deteriorate in real-world conditions due to disturbances such as sensor measurement errors, system uncertainties, and modeling errors. Therefore, an innovative anti-disturbance ACC method is proposed based on H ∞ robust controller with optimized safe velocity and following time headway to overcome the above problems. Initially, we analyze the longitudinal following characteristics that are undergoing disturbances and establish the ACC system model. Then, the optimization models for the safe velocity and the following time headway during ACC are designed. Subsequently, based on H ∞ theory, the design criterion of the H ∞ robust controller for ACC is established by utilizing the linear matrix inequality technique. Finally, two typical experiment scenarios are given for hardware-in-the-loop simulation to demonstrate the effectiveness of the proposed method.

Stimuli-responsive self-regulating assembly of chiral colloids for robust size and shape control.

Most synthetic self-assemblies grow indefinitely into size-unlimited structures, whereas some biological self-assemblies autonomously regulate their size and shape. One mechanism of such self-regulation arises from the chirality of building blocks, inducing their mutual twisting that is incompatible with their long-range ordered packing and thus halts the assembly's growth at a certain stage. This self-regulation occurs robustly in thermodynamic equilibrium rather than kinetic trapping, and therefore is attractive yet elusive. Until now, studies of self-regulating assemblies have focused on non-responsive systems, whose equilibrium point and corresponding size and shape are hardly changeable. Here, we demonstrate a stimuli-responsive, self-regulating assembly. This assembly consists of chiral and magnetically orientable nanorods, where the effective chirality can be changed by balancing chirality-induced twisting and magnet-induced flattening between nanorods. Consequently, the strength of self-regulation in the assembly is modulable by magnetic field intensity, allowing robust, tunable, and reversible control of its size and shape. Our strategy would provide more biomimetic materials with precision and responsiveness.

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.

The interactive effect of the application of accreditation standards (JCIs) and the practice of administrative control in improving the quality of health services: a study on Yemeni hospitals.

This study aimed to examine the interactive effect of applying JCI accreditation standards and administrative control in improving the quality of health services in Yemeni hospitals. By examining the synergistic relationship between these two components, this study sought to shed light on how hospitals can improve their performance and achieve sustainable advancements in healthcare quality. This study utilized a quantitative research design and collected data from Yemeni hospitals. The sample size was determined via the Krejcie and Morgan table, which provides a recommended sample size on the basis of the population. A total of 310 healthcare professionals were selected through a random sampling technique. Hypotheses were formulated to examine the impact of JCI accreditation standards and administrative control on healthcare quality. Statistical analyses were also conducted to test these hypotheses and determine the interaction effect between the two variables. The results confirmed that applying JCI accreditation standards has a statistically significant positive effect on improving the quality of health services in hospitals. Additionally, the practice of administrative control had a statistically significant effect on healthcare quality. Furthermore, there was an interactive effect between the application of JCI accreditation standards and administrative control, indicating that their combined implementation led to even greater improvements in healthcare quality. The significance of this study lies in its potential to inform healthcare policymakers, administrators, and practitioners about the importance of integrating accreditation standards with robust administrative control measures. The findings emphasize the need for hospitals to prioritize both the implementation of accreditation standards and the establishment of effective administrative control systems to ensure the delivery of high-quality healthcare services. This study contributes to the literature by highlighting the interactive impact of these factors and providing insights into their synergistic relationship.

Coordinated Optimization and Management of Oxygen Content and Cathode Pressure for PEMFC based on Hybrid Nonlinear Robust Control

Cathode inlet and exhaust management remains a significant challenge in proton exchange fuel cell (PEMFC). Achieving optimal oxygen content in real-time through precise control of the inlet gas is crucial for maintaining optimal output. Additionally, coordinating the air inlet and exhaust to ensure consistent cathode and anode pressures is essential for balancing the internal stack pressure and preventing nitrogen penetration, thereby enhancing PEMFC’s stability and lifespan. This paper addresses these challenges by introducing a mixed control strategy based on a fifth-order nonlinear mathematical model of the PEMFC stack cathode. Two non-singular fast terminal sliding mode structure controllers are combined as control system to optimize oxygen content and pressure control under dynamic loading conditions. The non-singular terminal sliding mode structure ensures finite-time convergence while mitigating potential singularity issues associated with traditional terminal sliding modes. The results showcase the robustness and effectiveness of the proposed control method in managing load variations, external disturbances, and PEMFC uncertainties.

Adaptive Two-Degree-of-Freedom Robust Gain-Scheduling Control Strategy

This study introduces a novel tracking control strategy tailored to aeroengines, which are highly nonlinear and characterized by significant uncertainty. The proposed method entails a robust extended Kalman filter (REKF) enhanced by a forgetting factor for improved performance. An accompanying augmented, mixed onboard adaptive model based on the REKF precisely estimates and manages engine performance degradation. This advanced model effectively counters the degradation term in the perturbation block of the engine’s uncertain model. Using this strategic approach, a robust gain-scheduling controller was constructed and was found to outperform its predecessors, marking a notable advancement in control system design. Controlling twin rotor multi-input, multi-output (MIMO) systems is a highly complex process due to model uncertainties and unpredictable external disturbances. To address these challenges, we constructed an adaptive two-degree-of-freedom robust gain-scheduling controller (ATDF-RGSC) using a mixed sensitivity approach. Rigorous performance analysis confirms that this controller offers enhanced robustness, faster tracking, and more precise disturbance attenuation compared to other methods. These advanced control strategies successfully manage uncertainties and disturbances, improving performance metrics in both simulated and experimental scenarios. The proposed method may significantly enhance the safety and reliability of aeroengines and MIMO systems in practical applications.

The effect of different mission profiles and ambient temperature on the lifetime of boost converter IGBT with a robust controller in a hybrid electric vehicle

AbstractThe reliability of power electronic converters is one of the essential issues in designing of electric vehicles. This paper estimates the lifetime of the boost converter switch by Semikron and Coffin‐Manson models for two common failure mechanisms of Bond wire and Base plate solder, respectively. Four mission profiles based on the Artemis standard are applied to hybrid electrical vehicle model to determine unidirectional output power. Kharitonov's theory is used to design a robust controller to handle the uncertainty raised by different power cycles of the electric vehicle and the parameters of the converter during simulation. Stability of converter is achieved during simulation by identifying simple proportional integral controller coefficients with Kharitonov's theorem. A prototype 230 W boost converter is designed and utilized to validate average model and switch loss calculation relationships. The lifetime results indicate that the number of cycles, and the average and the maximum junction temperature have a more impact than the duration of the drive cycle on the lifetime of the converter. A mixed mission profile is considered to investigate the effect of sudden change in driving modes and speed on total consumed life and lifetime to enhance the study's applicability. Lifetime of switch is decreased significantly in mixed mode in comparison with other mission profiles in the same driving time. Furthermore, the motorway mission profile has 53%, 39.6%, and 160% less total consumed life in comparison with the urban, rural and mixed mission profiles, respectively. In addition, the effect of ambient temperature changes on IGBT lifetime has been investigated for four mission profiles. While motorway had the least total consumed life in 25°C, the urban had better performance in comparison with other mission profiles from 25 to 55°C.

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.

Enhancing financial reporting quality in village-owned enterprises: The role of organizational competencies

The quality of financial reporting in village-owned enterprises (VOEs) is critical for ensuring transparency and accountability in local governance. This study explores the impact of education level, training programs, work experience, internal control systems, and information technology on the quality of financial reports in VOEs. The objective is to determine how these factors influence financial reporting quality to support effective local governance. The paper involves a sample of 120 VOE managers and employs quantitative analysis to examine the relationships between these factors and the quality of financial reporting in Indonesia. The results indicate that higher education levels, comprehensive training programs, and extensive work experience positively affect the quality of financial reporting. Specifically, the study finds that educated personnel and well-structured training programs enhance the accuracy and reliability of financial reporting. In contrast, the anticipated positive impact of IT utilization on financial reporting quality was not observed, suggesting that issues related to IT infrastructure and integration may limit its effectiveness. Additionally, robust internal control systems significantly improve the quality of financial reports. Overall, the analysis emphasizes the importance of investing in education, training, and internal controls to enhance financial reporting quality in VOEs. The findings highlight the need for further research into the challenges of IT integration to fully harness its benefits for financial transparency.

Cooperative control of leader–follower ships with prescribed performance

With consideration of prescribed performance, the robust cooperative control of leader–follower ships with the existence of ocean disturbances and model uncertainties is studied. The environmental disturbances are modeled as the harmonics disturbances with unknown amplitude and frequency, which are evaluated using an adaptive disturbance observer(ADO). Meanwhile, the model uncertainties is approximated utilizing the neural network, and the prescribed performance method is employed so that the tracking errors can be limited to the predefined set. Then the anti-disturbance cooperative control strategy is presented such that the system states are uniformly ultimately bounded, in addition, the collaborative motion among the leader–follower formation ships are achieved. Eventually, comparative simulations are employed to validate the cooperative control method.

Finite-time robust control of uncertain linear switched systems with comprehensive asynchronous switching

This paper focuses on designing a finite-time robust controller using the sliding mode method for uncertain linear switched systems with comprehensive asynchronous switching in the presence of disturbances, based on an observer with average dwell time. The term ‘comprehensive asynchronous switching,’ introduced for the first time in this research, refers to the possibility of the controller being activated either before or after its corresponding subsystem. This assumption is derived from real-world scenarios. The innovations of this paper are twofold: (1) the introduction of comprehensive asynchronous switching, and (2) the design of a finite-time robust controller for linear switched systems that accounts for simultaneous disturbances, comprehensive asynchronous switching, and bounded uncertainties. The effectiveness of the proposed method is evaluated through a simulation study.

Enhanced robust control based on ESO for high-pressure electro-pneumatic servo valve with strong anti-disturbance performance

Enhanced robust control based on ESO for high-pressure electro-pneumatic servo valve with strong anti-disturbance performance

System Identification for Robust Control of an Electrode Positioning System of an Industrial Electric Arc Melting Furnace

Through system identification for robust control methods and utilizing real-time experimental field data, a comprehensive mathematical model is derived that represents the dynamic performance of a single electrode positioning system (EPS) in an industrial electric arc melting furnace (EAF). This EPS is characterized by large, time-varying dynamic parameters, which fluctuate based on operating conditions, specifically as the electrode weight changes within its operational range. The system identification methodology for robust control is developed in four main steps, progressing from experimental design to model validation. This approach yields a nominal model of the actual system and provides a trustworthy estimate of the region of uncertainty of the model, bounded by models of the real system under maximum and minimum electrode weight conditions (limit operating models). The methodology generates three fourth-order time-delay models using an ARMAX structure. The results are promising, as system identification for robust control enables the derivation of mathematical models specifically tailored for designing robust controllers. These controllers significantly enhance the EPS control system’s performance and substantially reduce energy consumption and environmental emissions.

THE IN-CONTROL PERFORMANCE OF THE ROBUST MULTIVARIATE SYNTHETIC CONTROL CHARTS FOR MONITORING MEAN SHIFT

Multivariate synthetic control chart enables monitoring of multiple process variable simultaneously and hence, negate the inflation of false alarm rates as can be seen in an individual statistical chart. A robust version of the synthetic chart is necessary to mitigate the issue faces by the traditional multivariate synthetic chart, which is unable to produce reliable parameter estimates when Phase I data are contaminated. Therefore, this study proposed three new robust multivariate synthetic control charts (CMRCD, CWS and CWP) which were constructed via minimum regularized covariance determinant (MRCD) and winsorized modified one-step M-estimator (WMOM) for efficient process monitoring. The effectiveness of the proposed robust charts was evaluated in terms of false alarm rates by comparing their in-control performances to the traditional multivariate synthetic chart, Cmean, which is based on the sample mean. Via extensive simulation studies, the findings indicate that the proposed robust control charts outperform the traditional chart regardless of the dimensions or the level of contaminations in the dataset. The real data study further validates that the CMRCD, CWS and CWP perform better than the Cmean. Specifically, the three robust control charts show significant observations, illustrating better capability in monitoring river water quality when compared to the Cmean, i.e., the traditional multivariate synthetic chart.

Robust controller design for robot joint position servo systems

For the position servo control problem of a robot joint control system affected by the uncertainty of external disturbances, a model-based robust controller is designed in this paper. The designed controller is capable of suppressing the effect of external uncertain disturbances on the robot joint control system while improving the position servo accuracy and anti-interference capability of the system. The control scheme consists of two parts, the nominal part represents the model of the system dynamics, which is used to suppress any tendency to deviate from the constraints; the second part is the robust term, which is used to deal with the effects of the system due to uncertainties such as external disturbances. First, the boundedness and stability of the designed controller are proved by applying the Lyapunov function. Then, the effectiveness of the designed controller for trajectory tracking in position servoing is numerically simulated using MATLAB software. Finally, in this paper, the experimental equipment is used to build a test platform for joint control of a robot, and the proposed controller is verified experimentally, which confirms the efficiency and stability of the designed controller after the experimental comparison and analysis with some other control algorithms.

Integration of in-wheel motor sensorless systems and hierarchical direct yaw moment control for distributed drive electric vehicles

Ensuring robust and reliable control of distributed vehicles powered by in-wheel motor systems poses a significant challenge due to the harsh operating environments and high costs of such motor systems. Poor motor control, parameter variations, and sensor malfunction under these conditions can compromise the vehicle yaw stability. Integrating permanent magnet synchronous motor (PMSM) sensorless systems with vehicle yaw moment control offers a cost-effective solution for this issue without wheel angular speed sensors while enhancing yaw stability. In this paper, a composite nonlinear feedback sliding mode controller that can enhance the PMSM speed response is proposed. The proposed scheme exhibits a rotor speed overshoot and transient time of only 0.64% and 0.07s, respectively, which are smaller and shorter compared with other methods under motor parameter changes. Subsequently, the key states and tire-road friction coefficients required for vehicle control were estimated using sensorless rotor speeds and unscented Kalman filters, enabling the integration of the PMSM sensorless system with the vehicle yaw moment control. Additionally, a fuzzy adaptive hybrid sliding mode method is presented for yaw moment control enhancement. This method maintained the smallest sideslip angle root mean square error during double lane changes (0.4192 deg) compared with other methods. Analysis results show that different motor controllers and parameter changes significantly affect the vehicle dynamics performance. The proposed integrated scheme is feasible and effectively enhances the yaw moment control via high-performance sensorless PMSM systems.