Control Approach Research Articles

A systematic review on state of modeling, clinical issues, and advanced control approaches for artificial ventilator: traditional control to soft computing-based control approach

A systematic review on state of modeling, clinical issues, and advanced control approaches for artificial ventilator: traditional control to soft computing-based control approach

A Neural Network-Based State-Constrained Control Strategy for Underactuated Aerial Transportation Systems Within Narrow Workspace

The aerial transportation system belongs to a symmetrical system and has recently garnered increasing attention from researchers due to its broad application range and convenient operation. The control difficulty of the aerial transportation system lies in the fact that the load is not directly actuated, posing a significant challenge for state-constrained control. Taking the motion of an unmanned aerial vehicle (UAV) suspension transportation system within complex pipelines as an example, this paper employs the the swept volume signed distance field (SVSDF) method to search for state boundaries, which is an aspect not considered or elaborated in many state-constrained control approaches. Furthermore, adaptive state-constrained control based on the radial basis function (RBF) neural network is utilized for the case of experiencing unknown air resistance. The convergence of the proposed method for underactuated and actuated state variables is theoretically demonstrated based on the Lyapunov technique. Compared with existing methods, the error integral index demonstrates that the proposed method displays better convergence capability in the simulation section when considering state constraints under disturbance and air resistance.

Clubroot Disease ( Plasmodiophora brassicae ) as a Threat to Worldwide Rapeseed or Canola (Brassica napus)

Abstract The clubroot disease is a devastating threat to Brassica crops throughout many parts of the world. Recently, it has become more prevalent in several European countries, particularly in rapeseed (canola, Brassica napus ). The disease is difficult to control and only a few chemical treatments are available. The majority of control approaches focus on hygiene, crop rotation and in particular resistant cultivars. However, such resistance often relies on single genes and is rarely employed in Europe. Other possibilities include the exploitation of biocontrol agents, which have not yet proven effective in combating this disease. Rapeseed is not the only crop susceptible to the soilborne protist Plasmodiophora brassicae (Kingdom Chromista), but it may account for a large proportion of the commercial cash crops. Since the protist cannot be cultivated outside of its host, research relies on either investigating interactions with the host or using heterologous expression systems, which will not be discussed here. In this case study, a worldwide perspective on infested rapeseed plants that pose a threat to clubroot dissemination is presented. The complex life cycle is discussed, as well as possible control strategies such as breeding or interactions with beneficial microbes. Information © The Author 2024

Agreeing to Disagree: Translating Representations to Uncover a Unified Representation for Social Robot Actions

Researchers and designers of social robots often approach robot control system design from a single perspective; such as designing autonomous robots, teleoperated robots, or robots programmed by an end-user. While each design approach presents a tradeoff between some advantages and limitations, there is an opportunity to integrate these approaches where people benefit from the best-fit approach for their use case. In this work, we propose integrating these seemingly distinct robot control approaches to uncover a common data representation of social actions defining social expression by a robot. We demonstrate the value of integrating an authoring system, teleoperation interface, and robot planning system by integrating instances of these systems for robot storytelling. By relying on an integrated system, domain experts can define behaviors through end-user interfaces that teleoperators and autonomous robot programmers can use directly thus providing a cohesive expert-driven robot system.

Analysis of Fractional Resonant Controllers for Voltage-Controlled Applications

This paper investigates the application of fractional proportional–resonant controllers within the voltage control loop of grid-forming inverters. The use of such controllers introduces an additional degree of freedom, enabling greater flexibility in manipulating frequency trajectories. This flexibility can be harnessed to improve tracking error and enhance disturbance rejection, particularly in applications requiring precise voltage regulation. The paper conducts a conceptual stability analysis of ideal fractional proportional–resonant controllers using the Nyquist criterion. A tuning procedure based on robustness criteria for the proposed controller is also addressed. This tuning strategy is used to compare different controllers under the same conditions. In addition, a sensitivity analysis is provided, comparing the performance of fractional proportional–resonant controllers with traditional proportional–resonant controllers equipped with harmonic compensation. The controller’s formulation and performance are validated through simulations and tested with a 20 kVA inverter under high non-linear loads. Compared to classical control approaches, the fractional tuning parameter enhances tracking performance, reduces phase delay, and improves disturbance rejection. These improvements are achieved with a controller designed to minimise computational demands in terms of memory usage and execution time.

A multi-objective optimal control approach to motor strategy changes in older people with mild cognitive impairment during obstacle crossing.

Mild cognitive impairment (MCI) may lead to difficulty maintaining postural stability and balance during locomotion. This heightened susceptibility to falls is particularly evident during tasks such as obstacle negotiation, which demands efficient motor planning and reallocation of attentional resources. This study proposed a multi-objective optimal control (MOOC) technique to assess the changes in motor control strategies during obstacle negotiation in older people affected by amnestic MCI. Motion data from 12 older adults with MCI and 12 controls when crossing obstacles were measured using a motion capture system, and used to obtain the control strategy of obstacle-crossing as the best compromise between the conflicting objectives of the MOOC problem, i.e., minimising mechanical energy expenditure and maximising foot-obstacle clearance. Comparisons of the weighting sets between groups and obstacle heights were performed using a two-way analysis of variance with a significance level of 0.05. Compared to the controls, the MCI group showed significantly lower best-compromise weightings for mechanical energy expenditure but greater best-compromise weightings for both heel- and toe-obstacle clearances. This altered strategy involved a trade-off, prioritising maximising foot-obstacle clearance at the expense of increased mechanical energy expenditure. The MCI group could successfully navigate obstacles with a normal foot-obstacle clearance but at the cost of higher mechanical energy expenditure. MCI alters the best-compromise strategy between minimising mechanical energy expenditure and maximising foot-obstacle clearances for obstacle-crossing in older people. These findings provide valuable insights into how MCI impacts motor tasks and offer potential strategies for mitigating fall risks in individuals with MCI. Moreover, this approach could serve as an assessment tool for early diagnosis and a more precise evaluation of disease progression. It may also have applications for individuals with impairments in other cognitive domains.

Simulation framework and development of the Future Systems Simulator

Abstract The Aerospace Integration Research Centre (AIRC) at Cranfield University offers industry and academia an open environment to explore the opportunities for efficient integration of aircraft systems. As a part of the centre, Cranfield University, Rolls-Royce, and DCA Design International jointly have developed the Future Systems Simulator (FSS) for the purpose of research and development in areas such as human factors in aviation, single-pilot operations, future cockpit design, aircraft electrification, and alternative control approaches. Utilising the state-of-the-art modularity principles in simulation technology, the FSS is built to simulate a diverse range of current and novel aircraft, enabling researchers and industry partners to conduct experiments rapidly and efficiently. Central to the requirement, a unique, user-experience-centred development and design process is implemented for the development of the FSS. This paper presents the development process of such a flight simulator with an innovative flight deck. Furthermore, the paper demonstrates the FSS’s capabilities through case studies. The cutting-edge versatility and flexibility of the FSS are demonstrated through the diverse example research case studies. In the final section, the authors provide guidance for the development of an engineering flight simulator based on lessons learned in this project.

A Novel Enhanced Fire Hawks Optimization Approach for Improving the Efficiency of Converter‐Based Controllers in Switched Reluctance Motors

ABSTRACTSwitched reluctance motors (SRMs) have gained popularity in various industrial applications due to their advantages, including structural simplicity, high reliability, low cost, and operational stability over a wide speed range without relying on rare‐earth permanent magnet materials. However, these motors exhibit drawbacks such as weak torque density, low efficiency, and significant torque ripple, particularly in high‐speed operation. An efficient converter‐based control approach is proposed to manage speed and torque variations in SRM motors, addressing these issues. A multilevel converter (MC) is introduced as a fundamental component. The novel multilevel converter (NMC) accommodates SRMs with varying numbers of phases and exhibits quick demagnetization and excitation behaviors, enabling independent operation of each phase even during conduction overlaps. Subsequently, an effective controller is developed for the SRM motor, combining proportional integral derivative (PID) control with enhanced fire hawks optimization (EFHO). The EFHO optimizes the PID gain values to enhance controller performance. The converter operation minimizes torque ripple and facilitates speed management. The EFHO technique is a fusion of fire hawks optimization (FHO) and the sine cosine algorithm (SCA). This amalgamation improves the updating process of FHO by incorporating SCA. The proposed methodology is implemented in MATLAB and evaluated through various metrics, including SRM motor current, voltage, speed, and torque, under electric vehicle (EV) load conditions. Performance comparisons are conducted with traditional optimization algorithms such as the whale optimization algorithm (WOA) and ant colony optimization (ACO). The results validate the effectiveness of the proposed methodology in achieving improved SRM motor control and performance.

New Beauveria bassiana aerial conidia-based bioinsecticide obtained by spray-dried microencapsulation of the entomopathogenic fungi in biopolymers for crop protection

BackgroundDue to their environmentally friendly character, entomopathogenic fungi (EPF) are becoming increasingly used as microbial agents in biological pest control over chemical pesticides. However, EPF are sensitive to the influence of abiotic factors, such as temperature, radiation, and humidity. To improve their efficiency as bioinsecticides, in this work, the development of a new microparticles-based formulation loading EPF conidia (B. bassiana aerial conidia) into sodium alginate/maltodextrin microparticles obtained by spray-drying was proposed. Different concentrations of both polysaccharides were tested to reach the optimal ratio and ensure a high viability of encapsulated conidia.ResultsAll the produced formulations showed a moisture content < 10% and water activity (aw) < 0.4. Microparticles obtained with 2% sodium alginate and 8% maltodextrin were able to retain 89.5% of the viability of encapsulated conidia, thus being selected for further characterization. Scanning electron microscopy showed microparticles with a smooth surface, varied sizes, and irregular morphology. Microparticles retained 5.44 × 108 conidia/g, presented high hygroscopicity and high suspensibility rate, yet low wettability and water activity (aw) of 0.33. The pH value ranged from 6.46 to 6.62. Microparticles were able to complete release the loaded conidia after 30 min, under constant stirring. When exposed to thermal stress (45 °C), microparticles promoted thermal protection to conidia. Enhanced pathogenicity of B. bassiana conidia against P. xylostella was also confirmed achieving 83.1 ± 5.5%, whereas non-encapsulated conidia reached only 64.8 ± 9.9%.ConclusionsThis study confirms that the encapsulation of B. bassiana fungus conidia in sodium alginate/maltodextrin microparticles by spray-drying is a promising technological approach for the biological control of agricultural pests.

Developing a Cloud and IoT-Integrated Remote Laboratory to Enhance Education 4.0: An Approach for FPGA-Based Motor Control

Remote laboratories are essential in addressing access and quality challenges in technical education. They enable students from various locations to engage with real equipment, overcome geographic and economic constraints, and provide solutions during crises, such as pandemics, when in-person learning is limited. As a key element of Education 4.0, remote labs promote technical skill development, enhance engineering education, and support diverse learning approaches. This study presents a remote laboratory based on Field Programmable Gate Arrays (FPGAs), developed using a waterfall methodology integrating IoT and Cloud Computing technologies to facilitate close interaction between hardware and software. The lab focuses on controlling DC, servo, and stepper motors, allowing students to apply theoretical concepts such as digital signals, pulse-width modulation (PWM), and data representation in bits in a practical setting. The testing phase involved 50 robotics and mechatronics engineering students who participated in hands-on sessions for one month, followed by a structured survey evaluating their experience, interaction, and the educational relevance of the platform. The survey shows high student satisfaction, highlighting the platform’s strengths and identifying areas for improvement. The results also underscore the system’s potential to significantly enhance the educational experience in remote environments, aligning with the United Nations Sustainable Development Goals (SDGs).

Editorial: Novel chemical, microbiological and physical approaches in food safety control, volume II

Editorial: Novel chemical, microbiological and physical approaches in food safety control, volume II

Nurse practitioner oversight ratios and labor market outcomes

AbstractNurse practitioners are important to the US healthcare system; however, many states impose physician oversight ratios, which limit the number of NPs a physician may supervise. In this study, we evaluate the effect of eliminating physician oversight ratios on the supply of NPs by conducting case studies of three states—New York, Nevada, and Pennsylvania—using synthetic control and related approaches. Surprisingly, we find that eliminating oversight ratios had little effect on the labor supply of NPs. For New York, we also analyze the effects of eliminating oversight ratios on wages and hours worked and again find null results.

On penalized goal-reaching probability minimization under borrowing and short-selling constraints

Abstract We consider a robust optimal investment–reinsurance problem to minimize the goal-reaching probability that the value of the wealth process reaches a low barrier before a high goal for an ambiguity-averse insurer. The insurer invests its surplus in a constrained financial market, where the proportion of borrowed amount to the current wealth level is no more than a given constant, and short-selling is prohibited. We assume that the insurer purchases per-claim reinsurance to transfer its risk exposure to a reinsurer whose premium is computed according to the mean–variance premium principle. Using the stochastic control approach based on the Hamilton–Jacobi–Bellman equation, we derive robust optimal investment–reinsurance strategies and the corresponding value functions. We conclude that the behavior of borrowing typically occurs with a lower wealth level. Finally, numerical examples are given to illustrate our results.

Antimicrobial Activity of Diffusible Substances Produced by Lactococcus lactis Against Bacillus cereus in a Non-Contact Co-Culture Model

The symptoms of foodborne illness caused by Bacillus cereus often go unreported, complicating the effectiveness of conventional chemical and physical methods used to inhibit its growth in food production. This challenge, combined with the increasing use of lactic acid bacteria (LAB) in the food industry and consumer preference for minimally processed products, prompted this study. The antibacterial activity of diffusible substances produced by Lactococcus lactis ATCC 11454 against Bacillus cereus NC11143 and Escherichia coli K-12 MG1655 was investigated using a non-contact co-culture model utilising deMann Rogosa and Sharpe broth, with glucose as a carbon source. This study employed plate counting and flow cytometry to assess the impact of these substances on bacterial growth and to analyse their composition and antimicrobial efficacy. The co-culture of Lactococcus lactis ATCC 11454 resulted in the production of a stable antimicrobial peptide, which was heat resistant and acid tolerant. Purification was achieved via ammonium sulphate precipitation and preparative HPLC, yielding a peptide with a molecular mass of 3.3 kDa, with daughter ion fractions similar to nisin A. Antimicrobial activity studies demonstrated that the diffusible substances effectively inhibited B. cereus growth over a period of eight days and exhibited bactericidal activity, killing 99% of the B. cereus cells. Additionally, these substances also inhibited Escherichia coli K-12 MG1655 grown under similar conditions. Comparative analysis revealed that in the co-culture assay, L. lactis produced a 50% higher yield of the antimicrobial peptides compared to pure cultures. Similarly, the specific growth rate of L. lactis was four times higher. With respect to protein purification and concentration, ammonium sulphate precipitation coupled with solid phase extraction was most effective in the purification and concentration of the diffusible substances. The findings provide a basis for utilising bacteriocin-producing strains as a preservation method, offering an alternative to traditional chemical and physical control approaches especially for the food industry.

Adaptive Integral Sliding Mode Control with Chattering Elimination Considering the Actuator Faults and External Disturbances for Trajectory Tracking of 4Y Octocopter Aircraft

This paper presents a control strategy for a 4Y octocopter aircraft that is influenced by multiple actuator faults and external disturbances. The approach relies on a disturbance observer, adaptive type-2 fuzzy sliding mode control scheme, and type-1 fuzzy inference system. The proposed control approach is distinct from other tactics for controlling unmanned aerial vehicles because it can simultaneously compensate for actuator faults and external disturbances. The suggested control technique incorporates adaptive control parameters in both continuous and discontinuous control components. This enables the production of appropriate control signals to manage actuator faults and parametric uncertainties without relying only on the robust discontinuous control approach of sliding mode control. Additionally, a type-1 fuzzy logic system is used to build a fuzzy hitting control law to eliminate the occurrence of chattering phenomena on the integral sliding mode control. In addition, in order to keep the discontinuous control gain in sliding mode control at a small value, a nonlinear disturbance observer is constructed and integrated to mitigate the influence of external disturbances. Moreover, stability analysis of the proposed control method using Lyapunov theory showcases its potential to uphold system tracking performance and minimize tracking errors under specified conditions. The simulation results demonstrate that the proposed control strategy can significantly reduce the chattering effect and provide accurate trajectory tracking in the presence of actuator faults. Furthermore, the efficacy of the recommended control strategy is shown by comparative simulation results of 4Y octocopter under different failing and uncertain settings.

Chaotic vibration control of an axially moving string of multidimensional nonlinear dynamic system with an improved FSMC

A new control approach based on fuzzy sliding mode control (FSMC) is proposed to regulate the chaotic vibration of an axial string. Hamilton’s principle is used to formulate the nonlinear equation of motion of the axial translation string, and the von Kármán equations are used to analyse the geometric nonlinearity. The governing equations are nondimensionalized as partial differential equations and transformed into a nonlinear 3-dimensional system via the third-order Galerkin approach. An active control technique based on the FSMC approach is suggested for the derived dynamic system. By using a recurrent neural network model, we can accurately predict and effectively apply a control strategy to suppress chaotic movements. The necessity of the suggested active control method in the regulation of the nonlinear axial translation string system is proven using different chaotic vibrations. The results show that the study of the chaotic vibrations of axially translating strings requires nonlinear multidimensional dynamic systems of axially moving strings; the validity of the proposed control strategy in controlling the chaotic vibration of axially moving strings in a multidimensional form is demonstrated.

Linear Disturbance Observer-Enhanced Continuous-Time Predictive Control for Straight-Line Path-Following Control of Small Unmanned Aerial Vehicles

This paper studies the straight-line path-following problem on the lateral plane for fixed-wing unmanned aerial vehicles (FWUAVs) which are susceptible to uncertainties. Firstly, based on the natural frame’s location on the prescribed reference paths, the command yaw angle (which is the basis for yaw angle control system design) is solved analytically by combining it with the errors of path following, attack angle, sideslip angle, attitude angles, and geometric parameters of the prescribed reference paths. Secondly, by considering complicated dynamic characteristics, a linear extended state observer is designed to estimate uncertainties such as nonlinearities, couplings, and unmodeled dynamics whose estimated values are incorporated into the continuous-time predictive controllers for feedback compensation. Finally, numerical simulations are conducted to demonstrate the advantages of the proposed method, including reduced tracking errors and enhanced robustness in the closed-loop system, as compared to the conventional nonlinear dynamic inversion and sliding mode control approaches.

Transmission Dynamics of Typhoid Fever Outbreak: A Mathematical Modelling and Optimal Control Approach

In this paper, we propose and analyze a deterministic mathematical model for the control of typhoid fever. This model incorporates five effective control strategies, including vaccination, booster vaccination, personal hygiene, treatment, and bacteria sterilization, in order to effectively stop the spread of the disease in the population. The model consists of seven compartments, each representing a different stage in the disease’s progression: vaccinated, susceptible, carrier, infected, recovered, booster vaccinated, and bacterial. Using the next-generation matrix approach, we calculated the reproduction number , which measures the disease’s potential for spreading. Our stability analysis, using the Routh-Hurwitz criteria, revealed that the disease-free equilibrium point is locally asymptotically stable when is less than 1, among other conditions. This means that typhoid can be completely eradicated if the rate of secondary infection is kept below a certain threshold. Further sensitivity analyses were conducted to determine the key parameters that impact . Based on our findings, we formulated an optimal control problem and utilized Pontryagin’s Maximum Principle to determine the most effective strategy for controlling and eliminating the disease. Our results show that a combination of vaccination, booster vaccination, personal hygiene, treatment, and bacteria sterilization is the most optimal approach. With our comprehensive model and effective control strategies, we are one step closer to wiping out typhoid fever for good.

Coordinated control of single-point moored floating multi-wind turbines under fault events and shutdowns

Abstract The emergence of novel concepts aimed at the reduction of floating offshore wind energy cost is increasingly demanding new control approaches. This is the case of floating offshore multi-wind turbine assets (FOMWT), with two or more full wind turbines placed on the same floating platform. The strong dynamic interaction among the sub-components of such systems requires appropriate coordination of the commands driven by the individual wind turbine controllers. The impact of such coupling may increase depending on the asset confguration, as is the case of single-point distribution of mooring lines, commonly applied to FOMWTs. Among the most demanding situations are those under fault events and shutdowns, which may cause large uncontrolled platform rotation and put the system integrity at risk. To address this, a new coordinated control level, mastering the individual turbine controllers hierarchically, is proposed to govern the whole asset. The control concept proves to be effective under a reduced set of extreme load cases in accordance with standards for a two-wind turbine FOMWT. The simulations are performed with the multi-wind turbine simulation tool MUST, which accounts not only for the interaction among the two turbines and the platform, but also for the communication of the coordinated control and the individual turbine control levels.

A feedback linearization sliding mode decoupling and fuzzy anti-surge compensation based coordinated control approach for PEMFC air supply system

With the application of proton exchange membrane fuel cell (PEMFC) in the field of transportation and energy, the requirements for air flow and pressure tracking performance, efficiency and stability of PEMFC air supply system become higher and higher. To improve PEMFC cathode air flow and pressure control performance under load variation and avoid surge of air compressor, a novel feedback linearization sliding mode decoupling and fuzzy anti-surge compensation based coordinated control approach is proposed. Firstly, optimal references of oxygen excess ratio (OER) and cathode air pressure under different load are calculated based on net output power of PEMFC system analysis. Then, an extended state observer is designed to estimate the cathode air pressure and flow in real time, a feedback linearization sliding mode based decoupling controller is designed to enhance OER and air pressure tracking control performance and robustness. Considering on the operating trajectory and surge line of air compressor, a fuzzy logic based anti-surge compensator is designed to prevent air compressor from surge by compensating both air flow and pressure simultaneously. The proposed control approach is implemented in PEMFC air supply control experiments and the results demonstrates its effectiveness.