Types Of Control Strategies Research Articles

Advancing spatial repellents for malaria control: effectiveness and cost-effectiveness of a spatial repellent under operational use in Northern Uganda—study protocol for a cluster randomized controlled trial

BackgroundSpatial repellents (SRs) have been widely used for the prevention of mosquito bites, and preliminary findings suggest efficacy against both malaria (1) and Aedes-borne viruses (2) but their effectiveness in reducing mosquito-borne diseases under operational use has never been evaluated. SRs have the potential of being critical tools in the prevention of mosquito-borne diseases in contexts where typical vector control strategies, such as insecticide-treated nets (ITNs) and indoor residual spraying, are inaccessible or underutilized such as among displaced persons or in emergency relief settings.MethodsChildren will be enrolled in 3 separate cohorts to establish the effectiveness of SRs in reducing malaria infection in different distribution channels. One cohort will estimate the direct effect of the SR distributed through a reference channel (study personnel distribution). The two remaining cohorts will estimate the protection of the SR distributed through a voucher channel and the Village Health Team channel. Cohorts will be followed twice a month (approximately every 15 days): during the first scheduled household visit in the month, a blood sample will be taken for malaria rapid diagnostic test (Monthly Visit #1); and, during the second scheduled household visit, a blood sample will only be taken if the participant has a recent history of fever (Monthly Visit #2). The incidence of malaria in each cohort will be estimated and compared to the reference cohort to determine the benefit of using a SR in an area with high, year-round transmission of malaria.DiscussionThis study will address the knowledge gap of whether or not SRs are effective in reducing human malaria disease in humanitarian assistance and emergency response settings in sub-Saharan Africa where underlying transmission rates are historically high and ITNs may or may not be widely deployed. This research will inform policy makers on whether to recommend SRs as a means to further reduce malaria transmission for such operational programs.Trial registrationClinicalTrials.gov NCT06122142. Registered on November 8, 2023.

A Novel Semi-Active Control Approach for Flexible Structures: Vibration Control through Boundary Conditioning Using Magnetorheological Elastomers

This research study explores an alternative method of vibration control of flexible beam type structures via boundary conditioning using magnetorheological elastomer at the support location. The Rayleigh–Ritz method has been used to formulate dynamic equations of motions of the beam with MRE support and to extract its natural frequencies and mode shapes. The MRE-based adaptive continuous beam is then converted into an equivalent single-degree-of-freedom system for the purpose of control implementation, assuming that the system’s response is dominated by its fundamental mode. Two different types of control strategies are formulated including proportional–integral–derivative control and on–off control. The performance of controllers is evaluated for three different loading conditions including shock, harmonic, and random vibration excitations.

A recompression supercritical CO2 cycle using heat source storage to achieve low-frequency reactor regulation: Analysis and optimization of load capacity under safe compressor operation

This study focuses on proposing a heat source storage mode for the indirect recompression supercritical CO2 cycle (RSCC) coupled with a sodium-cooled fast reactor, aiming to achieve low-frequency regulation of the reactor and enhance the load capacity of system. A deep neural network-based turbomachinery performance prediction approach is employed to assess the system's part-load and overload performance under several typical control strategies. The turbine inlet temperature of the system under all control strategies except the intermediate heat exchanger (IHX) bypass rises with decreasing load. The system's part-load performance is positively correlated with its corresponding overload power. The findings reveal that the adjustable load ranges of the heat source storage tanks under inventory, turbine bypass, turbine throttle, and IHX bypass controls are 10%–156.10%, 10%–156.10%, 30%–147.30%, and 10%–146.88%, respectively, along with the safe compressor operation. As the near-choke operation of the compressor limits the rise in overload power, a turbine fitted with variable inlet guide vanes is tried. The optimization results demonstrate that the largest overload power of the system can reach 161.18 % without reducing the thermal efficiency. This study provides a heuristic insight into the variable load operation for indirect nuclear-powered Brayton cycles under low-frequency reactor regulation.

Disturbance Rejection Control of Grid-Forming Inverter for Line Impedance Parameter Perturbation in Weak Power Grid

When a grid-forming (GFM) inverter is connected to a low- or medium-voltage weak power grid, the line impedance with resistive and inductive characteristics will cause power coupling. Typical GFM decoupling control strategies are designed under nominal line impedance parameters. However, there are deviations between the nominal line impedance and actual parameters, resulting in poor decoupling effects. Aiming at this problem, this paper proposes a power decoupling strategy based on a reduced-order extended state observer (RESO). Firstly, the power dynamic model of the GFM is established based on the dynamic phasor method. Then, the model deviation and power coupling due to line impedance parameter perturbation are estimated as internal disturbances of the system, and the disturbances are compensated on the basis of typical power control strategy and virtual impedance decoupling. Good decoupling performance is obtained under different impedance parameters, improving the control strategy’s robustness. Finally, the effectiveness of the proposed method is verified by the results of RT Box hardware-in-the-loop experiments.

Robust fixed‐time synchronization of fuzzy shunting‐inhibitory cellular neural networks with feedback and adaptive control

AbstractThis article addresses the robust fixed‐time synchronization of fuzzy shunting‐inhibitory cellular neural networks (FSICNNs) with delays by utilizing two different types of control strategies. First, a feedback controller is proposed to achieve fixed‐time synchronization of FSICNNs. Secondly, a novel adaptive controller is designed to guarantee fixed‐time synchronization of FSICNNs, automatically adjusting all control gains without the need for advanced settings. The use of differential inequality techniques and the Lyapunov function method yields several sufficient conditions to ensure fixed‐time synchronization for the considered FSICNNs. Finally, an example, along with its numerical simulation, is presented to demonstrate the validity of the proposed theoretical results.

Self-Organized Polygon Formation Control Based on Distributed Estimation

This paper studies the problem of controlling a multi-robot system to achieve a polygon formation in a self-organized manner. Different from the typical formation control strategies where robots are steered to satisfy the predefined control variables, such as pair-wise distances, relative positions and bearings, the foremost idea of this paper is to achieve polygon formations by injecting control inputs randomly to a few robots (say, vertex robots) of the group, and the rest follow the simple principles of moving towards the midpoint of their two nearest neighbors in the ring graph without any external inputs. In our problem, a fleet of robots is initially distributed in the plane. The so-called vertex robots take the responsibility of determining the geometric shape of the entire formation and its overall size, while the others move so as to minimize the differences with two direct neighbors. In the first step, each vertex robot estimates the number of robots in its associated chain. Two types of control inputs that serve for the estimation are designed using the measurements from the latest and the last two time instants respectively. In the second step, the self-organized formation control law is proposed where only vertex robots receive external information. Comparisons between the two estimation strategies are carried out in terms of the convergence speed and robustness. The effectiveness of the whole control framework is further validated in both simulation and physical experiments.

Performance analysis of FEC based SR motor drive using fuzzy tuned PI controller

PurposeIn this paper, a new front end converter (FEC) topology has been proposed for the switched reluctance (SR) motor drive. This study aims to present the performance analysis of FEC-based SR motor drive using various types of control schemes like conventional proportional integral (PI) controller, fuzzy logic controller (FLC) and fuzzy-tuned proportional integral controller (Fuzzy-PI).Design/methodology/approachThe proposed FEC-based SR motor drive with various control strategies is derived for the torque ripple minimization and speed control.FindingsThe steady state and the dynamic response of the FEC-based SR motor drive are analyzed using three different controllers under change in speed and loading conditions. The Fuzzy-PI-based control scheme improves the dynamic response of the system when compared with the FLC and the conventional PI controller.Originality/valueThe hardware prototype has been implemented for the FEC-based SR motor drive by using the Xilinx SPARTAN 6 FPGA processor. The experimental verification has been conducted and the results have been measured under steady state and dynamic conditions.

Active Vibration Control of Flexible Structures with Super-Coiled Actuators

Flexible structures show low natural frequencies and light damping and often suffer from various dynamic loads, leading to low-frequency vibrations. Active vibration control is necessary for precision operation and long-term service of such structures, and a flexible actuator with a large actuation force and stroke is a key limitation. In this paper, super-coiled (SC) actuators, fabricated from fibers by twisting and inserting, were introduced to actively suppress the low-frequency vibration of flexible structures. Two SC actuators were symmetrically mounted on both surfaces of a cantilever beam to generate actuation forces. The force model of thermally driven SC actuators was developed, and a dynamic model of a cantilever beam with SC actuators was then proposed and validated via experimental actuation. Three types of control strategies, open loop, velocity negative feedback, and linear quadratic regulator (LQR), were adopted for vibration suppression. The results show that the proposed model fits quite well with the experimental data, and the maximum error between the experiment and the prediction is 3.90% among various driven currents. In velocity negative feedback control and LQR control, a 91.83% reduction of dynamic response is achieved, which validates the feasibility of using the actuator for low-frequency vibration control.

Adaptive and intelligent control of a dual-arm space robot for target manipulation during the post-capture phase

Dual-arm space robots provide a promising solution for efficiently and flexibly completing complex on-orbit servicing tasks. However, their effectiveness is often hindered by strong dynamic coupling between the robotic arms and the satellite base in the microgravity environment. In this paper, both robotic arms are used as task arms, and a system model that considers the closed-loop constraint formed after a dual-arm space robot captures a target is established. On this basis, two types of control strategies, namely self-tuning control strategy (STC) and radial basis function neural network control strategy (RBF) are proposed for trajectory tracking of the target transferred or detumbled by the robot arms in the presence of system uncertainty or external disturbances. The control methods are verified and compared against the traditional computed torque control strategy (CTC) in terms of control accuracy and system robustness through simulation. The results demonstrate the excellent robustness of both RBF and STC strategies. RBF outperforms the other strategies in terms of control accuracy, while STC proves to be the most energy-efficient.

Anti-synchronization of inertial neural networks with quaternion-valued and unbounded delays: Non-reduction and non-separation approach

This article investigates the anti-synchronization (AS) problem for quaternion-valued inertial neural networks (QVINNs) with unbounded time delays. Using two different types of control strategies (feedback and adaptive controllers) and Lyapunov theory, various conditions are established to guarantee the AS of QVINNs. Most of the results available for QVINNs are based on the variable substitution approach, which reduces the order of the original second-order system into the first-order system. The quaternion-valued networks can be separated into four equivalent real-valued neural networks (RVNNs), which have made the process more complicated. However, in the present study, the authors deal with the non-reduction order method and non-separation approach for QVINNs, making the analysis approach more concise and easier to deal with inertial neural networks (INNs). Here, the QVINNs have unbounded time-varying delays since neurons’ actions are related to their previous states. Hence the approach adopted here is more realistic and easy to deal with the QVINNs with unbounded time delays, which has not yet been considered by any researcher. Finally, two numerical examples are provided to demonstrate the efficiency and effectiveness of the proposed approach. In the first example, the present theoretical results have been validated, whereas the second example contains the application of quaternion-valued neural networks (QVNNs) related to associative memory to demonstrate their capacity to restore true color image patterns accurately.

A Comprehensive Review of Flexible Power-Point-Tracking Algorithms for Grid-Connected Photovoltaic Systems

The rapid increase in the penetration of photovoltaic (PV) power plants results in an increased risk of grid failure, primarily due to the intermittent nature of the plant. To overcome this problem, the flexible power point tracking (FPPT) algorithm has been proposed in the literature over the maximum power point tracking (MPPT) algorithm. These algorithms regulate the PV power to a certain value instead of continuously monitoring the maximum power point (MPP). The proposed work carries out a detailed comparative study of various constant power generation (CPG) control strategies. The control strategies are categorized in terms of current-, voltage-, and power-based tracking capabilities. The comparative analysis of various reported CPG/FPPT techniques was carried out. This analysis was based on some key performance indices, such as the type of control strategy, irradiance pattern, variation in G, region of operation, speed of tracking, steady-state power oscillations, drift severity scenario, partial shading scenario, implementation complexity, stability, fast dynamic response, robustness, reactive power, cost, and tracking efficiency. Among existing FPPT algorithms, model-based control has a superior performance in terms of tracking speed and low steady-state power oscillations, with a maximum tracking efficiency of 98.57%.

Stability and bifurcation analysis of an infectious disease model with different optimal control strategies

This paper deals with the non-linear Susceptible–Infected–Hospitalized–Recovered model with Holling type II incidence rate, treatment with saturated type functional response for the prevention and control of disease with limited healthcare facilities. The well-posedness of the model is ensured with the help of the non-negativity and boundedness of the solution of the system. The feasibility of the model with DFE (Disease-free equilibrium) and EE (endemic equilibrium) is analysed. The local and global stability are discussed with the help of the computed basic reproduction number R0. At R0=1, we use the Centre manifold theory to analyse the transcritical bifurcation exhibited by the system. It is found that the disease is not eradicated even if R0<1 due to the occurrence of backward bifurcation. The occurrence condition of Hopf bifurcation is obtained. The optimal control theory is used to analyse the effects of the minimum possible medical facilities, hospital beds, and awareness creation on the population dynamics. The Hamiltonian function is constructed with the extended optimal control model and solved by Pontryagin’s maximum principle to get the minimum possible expenditure. Different types of control strategies are shown by numerical simulation. The sensitivity analysis is discussed with the help of a crucial parameter that depends on the reproduction number. Further, the model is simulated numerically to support the theoretical studies. This paper emphasizes the significance of treatment intensity, the total number of hospital bed available and their occupancy rate as vital parameters for prevention of disease prevalence.

Experimental study on precise control air quantity on demand by the cooperation of multiple main fans in mine

Due to the global energy crisis worsening, numerous businesses have prioritized energy conservation and consumption reduction. However, in mines with multiple main fans, the main fans' operation efficiency is low to meet the ventilation on-demand, and the ventilation system's energy consumption is very high. This paper proposes an energy-saving control strategy for ventilation on demand with multiple fans network, which can save much energy in mines. We use the circuit method to calculate the operating condition parameters required for the joint control of multiple main fans by analyzing the influence features of multiple fans' mutual disturbance. We study the advantages and shortcomings of the traditional fan control method and create control strategy expressions for multiple fans. The two-step fan control strategy uses the adjusting wheel blades' angle method to determine the high-efficiency operating angle and the modulating fan speed method for accurate air quantity control. Furthermore, the effectiveness of the control strategy in ventilation on demand and fan energy-saving are verified on the three-dimensional complex ventilation pipe network experimental platform. The research results show that, compared to the two typical fan control strategies, our control strategy can save energy by 27.74% and 26.92%, respectively. If this strategy is applied to a mine with two main fans rated power of 500 kW, it can save energy 2,429,806 kW per year, saving USD 442.69 per day or USD 161,582.1 per year. The payback period for this strategy is approximately 14.1 months. Therefore, this research can provide a promising step towards intelligent control of air quantity on-demand while indicating enormous potential for energy savings in mine ventilation systems.

Smooth switching control strategy with complete process of frequency support for photovoltaic grid-connected converter

The continuous increase in the penetration of renewable energy sources such as photovoltaics (PV) brings operational challenges to the traditional distribution network. With a large-scale PV integration, the power system behaves as a weak grid, which leads to more frequent and wider changes in system strength. In order to improve the system stability, the PV system is required to operate stably while providing necessary system support under different operating conditions. However, there are two issues for the PV system needs to address to satisfy this requirement. Nowadays, there are two types of control strategies for PV systems: the grid-following (GFL) control and the grid-forming (GFM) control. The two control strategies differ in inertia support capability and control stability under different operating conditions. To guarantee the grid connection stability as well as the operating stability under AC systems with different strengths, the smooth switching between the GFL and GFM is an urgent topic. In addition, how to maintain the system frequency support performance during the control switching of the PV system is also a challenge. In this paper, an advanced smooth switching control strategy is proposed to enhance the operational stability and flexibility of the PV system while maintaining the frequency support performance during the switching process. Firstly, the small-signal stability of typical control strategies of GFL and GFM under different system strengths is compared to analyze the necessity of the control switching between the two control modes. Then, a smooth switching control strategy is proposed to realize the smooth switching when AC grid strength changes. More importantly, to improve the system frequency performance and realize continuous frequency support during the switching process, a power correction function is developed on the smooth switching control strategy. The effectiveness and universality of the proposed control strategy are verified by case studies on a modified IEEE 33 bus distribution network with high PV system integration.

A Review on Vibration Control Strategies Using Magnetorheological Materials Actuators: Application Perspective

Magnetorheological (MR) materials are a group of smart materials used in new technologies with controlled reliability. The development of these materials is expanding, starting from MR fluids, elastomers, grease, and gel. This large number of material types further expands the various applications of MR materials as a creative technology to support performance enhancement. For example, MR fluid is used to improve the performance of shock absorbers such as vehicle suspension, the damping of building structures, and polishing of the workpiece. MR elastomers are used for engine mounting, insulation base, and many other applications with intelligent material properties such as stiffness controllability. However, there are still complexities in the practical implementation of the control system beyond reliability. Many previous studies have focused on the performance improvement and reliability of MR materials as smart materials for application devices and systems. In this review article, the specific discussion related to vibration control strategies in MR material-based systems was thoroughly investigated. To discuss this point, many MR applications including transportation system and vibration isolation were adopted using different types of control strategies. Many different control strategies that have been used for MR applications such as fuzzy logic control, optimal control, and skyhook control are discussed in-depth in terms of the inherent control characteristics of merits and demerits.

On a Vision-Based Manipulator Simulator

This paper presents a typical grasp–hold–release micromanipulation simulator based on MATLAB and Simulink. Closed-loop force and position control were implemented only based on a camera. The work was mainly focused on control performance improvements and GUI design. Different types of control strategies were investigated in both the position and force control processes. Finally, incremental PID and positional PID were adopted in the gripper position control and force control processes, respectively. The best performance of the gripper position control was the fast response of 0.3 s without overshoot and steady-state errors in the range of 10–40 Hz. The new camera control algorithm kept a big motion range (4.48 × 4.48 mm) and a high position resolution of 0.56 µm, with a high force resolution of 1.56 µN in the force control stage. The maximum error between the measured force and the real force was maintained below 4 µN. The steady-state error and the setting time were less than 1.2% and less than 1.5 s, respectively. A separate app, the Image Generation Simulator app, was developed to assist users in getting suitable initial coordinates, camera parameters, desired position resolutions, and force resolutions, which are packed as a standalone executable file. The main app can run the simulation model, debug, playback, and report simulation results, and calculate the calibration equation. Different initial coordinates, camera parameters, sample frequencies, controller parameters, and even controller types can be adjusted from this app.

Evaluation of transit signal priority at signalized intersections under connected vehicle environment

ABSTRACT Conventional transit signal priority (TSP) control strategies generally have negative impacts on other traffic. In this study, two typical signal control strategies under connected vehicle (CV) environment that give priority to transit vehicles at signalized intersections are investigated, i.e. actuated TSP with CV and optimized TSP with CV. The optimization algorithm used in this study is genetic algorithm (GA) and the goal of the optimization is to minimize the total person delay. A real-world intersection is modeled in a microsimulation environment to evaluate the performance. The results are compared with fully actuated signal control strategies with and without TSP. Results show that the proposed optimization control strategy can reduce the average bus delay by 24.5% during peak hours while minimizing the negative impacts on conflicting traffic. Under the low traffic demand condition, the actuated controller with TSP using CV has a better performance in terms of average delay.

Energy-Saving Optimization for Electric Vehicles in Car-Following Scenarios Based on Model Predictive Control

In this paper, an economy-oriented car-following control (EOCFC) strategy is proposed for electric vehicles in car-following scenarios. Specifically, a controller based on model predictive control (MPC) is developed to optimize the host vehicle’s speed for better energy economy while ensuring good car-following performance and ride comfort. The vehicle’s energy consumption is accurately quantified in the form of demand power, which is incorporated in the cost function for energy optimization. The proposed EOCFC strategy is evaluated using three standard test cycles, i.e., New European Driving Cycle (NEDC), Urban Dynamometer Driving Schedule (UDDS) and Worldwide Harmonized Light Vehicles Test Cycle (WLTC), in comparison with a typical multi-objective adaptive cruise control strategy. The evaluation results demonstrate that the proposed EOCFC improves the energy economy of the host vehicle by 0.53%, 3.33% and 1.51%, under the NEDC, UDDS and WLTC test cycles respectively.

Modeling and stability analysis of interaction between converters in AC-DC distribution systems

With the development and promotion of AC-DC distribution systems, the stability of multi-terminal systems has drawn much interest. This paper analyzes the instability phenomena in AC-DC distribution systems by considering the interactions between converters. The typical structure and control strategy of double-terminal AC-DC distribution systems under master-slave control is introduced. Then an AC-DC distribution system model is developed taking into account the interaction of the converter control system. The resonant spikes generated by the interaction between the converters are used as the reference object of the interaction to analyze the influence of the converter control parameters and the system electrical parameters on the system stability and interaction. Finally, a double-terminal AC/DC distribution system model is built using PLECS and RTBOX for simulation and semi-physical experimental verification.

Asymptotic synchronization of second-fractional -order fuzzy neural networks with impulsive effects

Without transforming the second-fractional-order terms to the first-fractional-order, this paper focuses on the global asymptotic synchronization (GAS) of second-fractional-order fuzzy neural networks (SFOFNNs) with delay and impulsive effects in the Caputo fractional derivative (CFD) sense. Based on the fractional Lyapunov functional approach and applying the impulsive fractional-order delayed comparison principle, several effective criteria in terms of algebraic inequalities are directly obtained to ensure the GAS of two SFOFNNs by proposing two different types of control schemes with the fractional derivative of states. Compared with the current variable substitution methods, the GAS is firsthand discussed by presenting a few new fractional Lyapunov functionals. Finally, two numerical simulations are given to demonstrate the validity of the derived findings.