Stable Control Research Articles

Event-Based Fuzzy Stabilization Controller for Uncertain Nonholonomic Systems With Output Constraints: Application to Mobile Robots

Event-Based Fuzzy Stabilization Controller for Uncertain Nonholonomic Systems With Output Constraints: Application to Mobile Robots

Adaptive precision image stabilization control closed-loop method for space astronomical telescope

Adaptive precision image stabilization control closed-loop method for space astronomical telescope

Stabilization Control of Stackelberg Game-Based System: Continuous-Time Case

Stabilization Control of Stackelberg Game-Based System: Continuous-Time Case

Liquid L-T4 therapy in hypothyroid patients with gastric diseases, an observational study.

This is an observational and retrospective study, in which we have analyzed data from patients affected by gastric diseases (p) who have been treated with liquid L-T4 (L-LT4;84 p), or tablet L-T4 (T-LT4;120 p), for the replacement therapy of hypothyroidism. The aim of the study is to compare the stability of TSH [normal range, 0.3-3.5 μIU/ml] in these patients. All p assumed L-T4 30 minutes before breakfast. The types of gastric disease were: a) T-LT4 group: 74 chronic gastritis (CG); 4 gastrectomy for gastric cancer (GTx); 42 gastro-plastics (GP); b) L-LT4 group: 60 CG; 3 GTx; 21 GP (p>0.05). 66% p in T-LT4 group were chronically treated with proton pump inhibitors (PPI), against 51% in L-LT4 group (p>0.05). The frequency of Helicobacter Pylori infection was 17% in both T-LT4 and L-LT4 groups. The gender distribution, mean age and body weight were similar in the 2 groups (p>0.05). The mean L-T4 dosage in T-LT4 group at the basal evaluation was 1.22+/-0.27 μg/kg/die, in the L-LT4 group 1.36+/-0.22 μg/kg/die (p>0.05). At the basal evaluation the prevalence of patients with a TSH>3.5 μIU/mL in T-LT4 group was 36%, in L-LT4 group 46% (p<0.05). After adjustment of the dosage of the LT-4 therapy, the p were re-evaluated in an interval range of 5-9 months, for 4 times, during an overall period ranging from 23 to 31 months. At the first re-evaluation, the prevalence of p with a TSH>3.5 μIU/mL was 13% in both groups. At the second re-evaluation, the prevalence of p with a TSH>3.5 μIU/mL in T-LT4 group was 26%, in L-LT4 group 13% (p>0.05). At the third re-evaluation, the prevalence of p with TSH<3.5 μIU/mL in T-LT4 group was 19%, in L-LT4 group 9% (p=0.05). At the fourth and last re-evaluation, the prevalence of patients with a TSH>3.5 μIU/mL in T-LT4 group was 18%, in L-LT4 group 5% (p<0.05). Mean FT4 and FT3 circulating levels were not significantly different in the two group at each visit. These data suggest that the liquid L-T4 formulation therapy can result in a more stable control of TSH levels in hypothyroid patients with gastric disorders in the long-term follow-up.

An Adaptive Fuzzy Logic Control Method for Froth Velocity in the Flotation Process

In the flotation process, too high or too low froth velocity can lead to a reduction in the recovery of useful minerals. However, it is difficult to achieve stable control of froth velocity due to complex process characteristics and fluctuating working conditions. Uncertain feed conditions (feed flow rate, feed grade, and feed concentration) can cause large changes in the desired froth velocity and other uncertain conditions, which affect the accurate evaluation of the velocity state for feedback control. In this paper, an adaptive fuzzy logic control method for froth velocity (AFLC-FV) in the flotation process is proposed. In the method, an adaptive fuzzy quantization function with a dead zone is designed and used instead of the constant fuzzy quantization factor in the fuzzification procedure. Thus, the dynamic real domain of the velocity error can be mapped to a fixed standard fuzzy domain. Meanwhile, the width of the dead zone is adaptively adjusted according to froth mobility to improve steady-state performance. In addition, the velocity trend is extracted and used as an input variable to the controller together with the velocity error. The application results show that, compared with manual control, the AFLC-FV significantly enhances the control accuracy and stability under different ranges of velocity set-points, and effectively improves the mineral recovery by 0.18%.

An improved nonsingular adaptive super twisting sliding mode controller for quadcopter.

This paper presents an improved nonsingular adaptive super twisting sliding mode control for tracking of a quadrotor system in the presence of external disturbances and uncertainty. The initial step involves developing a dynamic model for the quadrotor that is free from singularities, achieved through the utilization of the Newton-Quaternion formalism. Then, the super twisting algorithm is used to develop a novel sliding mode control that mitigates chattering. Particle Swarm Optimization (PSO) is employed for the adjustment of the controller gains. Moreover, to maintain stable control of the quadcopter, even in scenarios where the upper limit of disturbances is unknown, an adaptive rule grounded in Lyapunov stability is applied. Simulation results demonstrate that the proposed controller reduces tracking errors to 0.1% for roll, 0.05% for pitch, and 2.2% for altitude, outperforming other state-of-the-art sliding mode controllers. Additionally, the proposed controller effectively rejects disturbances, maintaining minimal steady-state errors of 0.01° for roll, 0.02° for pitch, and 0.001° for yaw, significantly better than conventional controllers. These results highlight tracking and disturbance rejection capabilities of the proposed controller, making its real-time implementation for quadrotor Unmanned Aerial Vehicles (UAVs) feasible.

Intensive start of therapy in modern strategies for managing type 2 diabetes mellitus

Type 2 diabetes mellitus continues to be one of the global medical and social problems. Early administration of combination therapy with hypoglycemic drugs acting on various pathophysiological mechanisms of diabetes development allows prolonging the duration of the therapeutic effect and achieving more stable control of blood glucose levels. Currently, a combination of metformin with dipeptidyl peptidase-4 (DPP-4) inhibitors is recommended as an initial therapy that meets these requirements. This combination has a synergistic effect on various links in the pathogenesis of the disease. The addition of gliptins to metformin enhances insulin secretion by beta cells of the pancreas and increases insulin sensitivity, which ultimately contributes to a longer preservation of the therapeutic effect. The only representative of the DPP-4 inhibitors class recommended as part of the initial combination therapy with metformin, taking into account the results of the VERIFY study, is vildagliptin. The use of a fixed combination of metformin and vildagliptin in one tablet increases patients' compliance with the treatment regimen, which, in turn, reduces the risk of complications and mortality.

Discrete-Time Port-Hamiltonian Systems for Power and Energy Applications

The Port-Hamiltonian formalism has demonstrated to be useful in different applications, allowing to explore structural properties to obtain stable controls. A common approach is to design controls in a continuous domain although, in practice, they are implemented in discrete time. However, the study of discrete-time port-Hamiltonian systems is challenging since the system may lose structural properties such as passivity after discretization. This paper shows that passivity is conserved for the backward Euler discretization method when the Hamiltonian is convex, and its gradient is Lipschitz. This result is relevant for power systems applications such as the control of two-area systems, high-voltage direct-current transmission, and microgrids. Although our method is simple and preserves passivity, it does not preserve the symplectic structure of the hamiltonian.

Distributed Unified Controller Design for Parallel Battery Storage System in DC Shipboard Microgrid

In this paper, a novel distributed unified controller is designed to solve the problems of unbalanced State of Charge (SoC), unreasonable load current sharing, and unstable DC bus voltage for parallel battery storage systems (BSSs) in DC shipboard microgrid (DC-SMG). Different from the droop-based secondary controller, the designed distributed unified controller is a droop-free primary controller, which can incorporate SoC balancing, current sharing, and voltage regulation functions in the primary control layer. On this basis, each BSS uses an improved dynamic diffusion algorithm (DDA) to iteratively estimate the average information, and completes information exchange by a neighbor-to-neighbor communication network. Furthermore, the small-signal stability, large-signal stability, and global steady-state performance of the system is investigated using eigenvalue analysis, mixed potential theory (MPT), and matrix theory, respectively. Finally, the Matlab/Simulink simulation model and the StarSim HIL experimental platform for DC-SMG are built. The results show that the designed distributed unified controller can simultaneously achieve dynamic SoC balancing, proportional load current sharing, and smooth average bus voltage regulation, and has a faster SoC convergence speed and more stable control effect than the state-of-the-art methods.

Precise and coordinated gearshift control for AMT gearshift system equipped with two linear actuators

A type of automated manual transmission gearshift system that uses two linear actuators to perform gearshift events is presented. The shifting mechanism can be made simpler by using linear actuator to drive the shift fork directly. The mathematical model of the actuator is built and analyzed. Coordinated control of the engagement and disengagement processes is created based on a detailed analysis of the gearshift process in order to shorten the shift time. The force characteristics test reveals the nonlinear output characteristics. The precise displacement control need for coordinated control and stable control requirement for the shifting operation are satisfied by a linear extended state observer based controller. To verify the novel gearshift system and the control method, a test bench and control system are constructed. The results of the simulations indicate that the displacement control's accuracy is enhanced. As the speed difference reaches 500 r/min, the testing results demonstrate a noticeably reduced of shift force fluctuation and jerk generated during the gearshift process, from 20 m/s3 to 3.1 m/s3. With the improved gearshift system and control method, the gearshift coordinated control can also save 25 ms of shift time.

Research on SiC Speed Controller for High‐Voltage Distributed Electric Propulsion System

The shift towards green aviation necessitates the adoption of all‐electric aircraft, marking an essential trend in the aviation industry. Distributed propulsion systems enhance aircraft flexibility and reliability, synchronously reducing performance demands and costs of single propulsion units compared to centralized propulsion system. The high reliability and lightweight characteristics of brushless DC motors have made them increasingly popular in distributed propulsion systems. Despite its advantage which helps to build efficient aircraft aerodynamic layout, there are more cables in the distributed propulsion system, which accounts for most of the weight of the aircraft. To address this, all‐electric aircraft utilizes high‐voltage power supply to reduce the current, so it uses SiC MOSFETs as power devices to improve its efficiency and heat dissipation. The speed controller in all‐electric aircraft determines the efficiency and reliability of the propulsion unit. However, the traditional high‐voltage speed controller poses challenges for aircraft maintenance because of high cost. Therefore, this paper emphasizes the significance of designing a low‐cost, high‐performance speed controller for all‐electric aircraft. Challenges such as circuit interference, battery voltage fluctuation, and sampling noise affecting the high‐voltage controller during operation are solved, respectively. First, to address the likelihood of mutual interference in the bridge arm, a self‐bootstrapping voltage reduction drive mode is designed to turn off SiC MOSFET and enhance circuit anti‐interference. Second, to solve the challenge of wide battery voltage fluctuation range and inconsistent controller output, an adaptive pulse width modulation (PWM) regulation mode for battery voltage is proposed, ensuring stable controller output. Finally, to counteract the impact of the comparator threshold on zero‐crossing sampling, an electrical angle delay method based on delay compensation is designed to improve the efficiency of the brushless DC motor during operation. Experimental results show that the three solutions proposed in this paper are helpful to improve the anti‐interference, stability, and efficiency of the controller in the high‐voltage distributed electric propulsion system and contribute to reduce the cost and weight in the propulsion unit.

Multiobjective Robust PI Synthesis in Plants with Uncertain Poles

The use of multiobjective optimization procedures for control tuning has been constantly explored, presenting satisfactory results, and generating significant contributions to control engineering. In this way, the field of robust control can benefit significantly from the integration of multiobjective optimization design procedures for robust Proportional-Integral-Derivative (RPID) controller synthesis, enabling innovative solutions to complex control challenges. Due to this fact, this paper explores an approach to utilize multiobjective optimization algorithms in a simplified procedure, considering uncertain systems in the form of interval plants with uncertain poles, the Kharitonov theorem is used to obtain a region of stability as search space for the multiobjective algorithm, being the optimization process performed over a nominal system model. Two numerical cases and a flexible actuator model were used to demonstrate the procedure for RPI synthesis, resulting in robustly stable controllers with optimized performance over error and control signal effort measures.

A hybrid PCA-SOA-BP approach for predicting converter endpoint temperature in steelmaking

Accurately controlling the temperature of the converter end is a crucial element of the steelmaking process. To enhance the accuracy of predicting the converter end temperature, we propose a hybrid model that utilizes principal component analysis (PCA) and snake optimization algorithm (SOA) in conjunction with a backpropagation algorithm (BP) neural network. The 16 parameters for smelting in converter steelmaking were reduced using principal component analysis to remove shared features. The nine principal components derived from this analysis were then used as input variables for an optimized BP neural network. An optimization algorithm was then employed to refine the initialized weights and thresholds of the BP neural network. The impact of neuron node quantity in the hidden layer on the BP neural network was examined. Results show that the ideal BP neural network is achieved with 19 neuron nodes in the hidden layer. Compared with ordinary BP neural network, PCA-BP neural network and SOA-BP neural network, the model proposed in this study can predict the end temperature of converter most accurately. In the temperature error range of ±10 °C and ±15 °C, the prediction accuracy of the model is 93% and 96%, respectively. Meanwhile, the model has been effectively applied in the industrial production of a steel plant in China. The results show that the prediction results of the model are in good agreement with the actual production data in the field. This accurate prediction can optimize the field operation process and realize the stable control of product quality.

Stochastic stability of an autoresonance model with a center–saddle bifurcation

The purpose of this work is to investigate the effect of stochastic perturbations of the white noise type on the stability of capture into autoresonance in oscillating systems with a variable pumping amplitude and frequency such that a center–saddle bifurcation occurs in the corresponding limiting autonomous system. The another purpose is determine the dependence of the intervals of stochastic stability of the autoresonance on the noise intensity. Methods. The existence of autoresonant regimes with increasing amplitude is proved by constructing and justificating asymptotic solutions in the form of power series with constant coefficients. The stability of solutions in terms of probability with respect to noise is substantiated using stochastic Lyapunov functions. Results. The conditions are described under which the autoresonant regime is preserved and disappears when the parameters pass through bifurcation values. The dependence of the intervals of stochastic stability of autoresonance on the degree of damping of the noise intensity is found. It is shown that more stringent restrictions are required to preserve the stability of solutions for the bifurcation values of the parameters. Conclusion. At the level of differential equations describing capture into autoresonance, the effect of damped stochastic perturbations on the center–saddle bifurcation is studied. The results obtained indicate the possibility of using damped oscillating perturbations for stable control of nonlinear systems.

Case Report: A Nursing Challenge - Postoperative Complications of Pacemaker Implantation in Behçet’s Disease

Background: Cardiovascular system involvement in Behçet’s disease is rare, especially requires surgical intervention. We report a case of a 47-year-old Chinese male with Behçet’s disease, treated with immunosuppressive agents, who developed an infection at the surgical site following the postoperative implantation of a pacemaker. Little is known about the approach to managing postoperative wounds in Behçet’s disease. This article aims to provide a reference for nursing care, improve perioperative management, and assist in achieving a good prognosis for Behçet’s disease with cardiovascular system involvement. Method: We used the following three-phase process: 1. Followed authoritative guidelines for the perioperative management of patients with cardiac implantable electronic devices (CIED), which included strict aseptic techniques, pressure bandaging, and the preventive use of antibiotics. 2. Conducted a literature search for reasons and solutions to pain and infection symptoms at the surgical site. 3. Cleaned the wound using different disinfectants and evaluated the wound’s condition; managed pain through a multimodal approach within an Acute Pain Service (APS) team management model. Determined whether to continue immunosuppressive therapy based on the Pathergy test after the patient had suspended immunosuppressive therapy for over a month. Results: Our case illustrates the wound healing process during the patient’s 50-day hospitalization, from a secondary wound with a 5x5 cm rupture and exudation to Grade A healing. The patient’s Numeric Rating Scale (NRS) pain score decreased from 6 points to 0 points upon discharge. Three months post-discharge, follow-up revealed slight scarring at the wound site, normal pacemaker function, and stable control of Behçet’s disease. Conclusion: Patients with Behçet’s disease under immunosuppressive treatment have a higher risk of infection at the surgical site following pacemaker implantation. Using hydrogen peroxide first, followed by iodine, and finally physiological saline during wound debridement is significantly effective in controlling infection. The APS team management model, composed of attending physicians and nurses, can effectively improve pain relief quality during wound recovery. The Pathergy test is an effective method to evaluate whether disease activity affects wound healing after CIED implantation and whether continued use of immunosuppressive therapies is necessary.

KONTROL FREKUENSI BEBAN MENGGUNAKAN METODE ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) PADA SISTEM HYBRID WIND MIKROHIDRO DAN DIESEL

This study aims to analyze and compare the performance of three frequency load controller methods in a hybrid generator consisting of three types of energy generation, namely microhydro, diesel and wind. The controller methods being compared are the PID (Proportional Integral Derivative) method, ANFIS (Adaptive Neuro-Fuzzy Inference System), and Fuzzy. This analysis was carried out to improve the efficiency and stability of the hybrid generating system by optimizing the frequency load controller. Frequency instability can occur due to load fluctuations, changes in environmental conditions, or system disturbances. Therefore, the use of an effective and adaptive controller method is very important in maintaining the stability and reliability of the hybrid generator system. The analytical method used in this study involved data collection and computer modeling. The required data includes information on load variations, energy production, and environmental conditions. Furthermore, the PID, ANFIS, and Fuzzy methods are applied to the data to build a frequency load controller model. The results of the analysis show that the three controller methods have different performance in maintaining frequency stability in the hybrid generator system. The PID method provides a fast and accurate response to load fluctuations, but is less adaptive to environmental changes. While the ANFIS method is able to adapt well to changes in system conditions, it requires time for model training. Fuzzy methods can provide control that is more adaptive and tolerant to disturbances, but may require more complex tuning. However, in general, the use of intelligent controller methods such as ANFIS and Fuzzy can improve the performance of hybrid generators by producing more adaptive and stable controls. This research has important implications for the development of more efficient and reliable hybrid power systems. By choosing the right controller method, hybrid power plants can provide energy in a more stable and environmentally friendly manner, and reduce dependence on limited fossil resources. Therefore, this research can make a significant contribution to the development of renewable energy and sustainable development in the future.

High-Speed Tracking Controller for Stable Power Control in Discontinuous Charging Systems

The global population is rapidly increasing, and the urban population is on an even faster trend; therefore, the population density is expected to rise. As the number of people in cities grows, the demand for high-rise buildings is anticipated to increase to address the problem of limited land resources. Therefore, efficient energy management using distributed resources has become increasingly important. Elevators are a vital vertical means of transportation in high-rise buildings, and reducing the weight of their components can lead to favorable conditions for energy utilization and increased speed. Therefore, this study presents an elevator system that supplies power inside an elevator car by eliminating the traveling cable and applying a small-capacity energy storage system (ESS). Additionally, we propose a charging algorithm suitable for the proposed system. Generally, batteries have sensitive electrical properties among the distributed energy resources (DERs). Therefore, controlling the stable maintenance of the transient state of the charging current—even when the DC power is unstable or the load changes rapidly in a system requiring fast charging—is crucial. Owing to the nature of the elevator system to be applied, discontinuous charging is frequent, and the active and efficient management of the battery state of charge (SOC) may be challenging. In addition, since it is necessary to be able to charge as much as possible during a short discontinuous charging time, a current control algorithm with a stable and high-speed response is required. The proposed transient high-speed tracking controller (THSTC) is a method for tracking the time of applying an inductor’s excitation voltage without pulse–width modulation (PWM) switching, which is less sensitive to the controller gain values and has fast responsiveness as well as stable transient response characteristics. The proposed method has good dynamic characteristics with a simple control structure without a complex design, which is useful for systems with repeated discontinuous charging. We validate the performance and effectiveness of the proposed controller through simulations and experiments.

Fixed-Time Control of a Robotic Arm Based on Disturbance Observer Compensation

Backstepping-based fixed-time tracking control is proposed for a robotic arm system to solve the problem of trajectory tracking control under system uncertainties, which ensures the robotic arm system can realize stable tracking control within a fixed time independent of the initial state of the system. In addition, to address the uncertainties in the robotic arm system, a control strategy based on disturbance observer compensation is designed, which provides feed-forward compensation through the accurate estimation of the system uncertainties and enhances the system’s robustness. Finally, a two-link robotic arm model is used for simulation experiments, and the comparison results show that the control scheme designed in this article can effectively improve the robotic arm’s tracking accuracy and convergence speed.

Exponentially stable adaptive optimal control of uncertain LTI systems

SummaryA novel method of an adaptive linear quadratic (LQ) regulation of uncertain continuous linear time‐invariant systems is proposed. Such an approach is based on the direct self‐tuning regulators design framework and the exponentially stable adaptive control technique developed earlier by the authors. Unlike the known solutions, a procedure is proposed to obtain a non‐overparametrized regression equation (RE) with respect to the unknown controller parameters from an initial RE of the LQ‐based reference tracking control system. On the basis of such result, an adaptive law is proposed, which under mild regressor finite excitation condition provides monotonous convergence of the LQ‐controller parameters to an adjustable set of their true values, which bound is defined only by the machine precision. Using the Lyapunov‐based analysis, it is proved that the mentioned law guarantees the exponential stability of the closed‐loop adaptive optimal control system. The simulation examples are provided to validate the theoretical contributions.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables. The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets. For this purpose, a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities. Then, an asynchronous fuzzy sampled-data controller, featuring distinct premise variables from the active suspension system, is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership. Furthermore, novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous H2 and H∞ performance requirements. Finally, the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.