Control Objective Research Articles

Inferring control objectives in a virtual balancing task in humans and monkeys

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal’s control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject’s control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.

Inferring control objectives in a virtual balancing task in humans and monkeys.

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal's control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject's control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.

Data-driven economic MPC with asymptotic stability and strong duality verification using Hankel matrix

We consider the problem of dynamic regulation with an economic cost function to control unknown linear systems, in which improving the economic performance and guaranteeing the stability of economical optimal equilibrium point are control objectives. A data-driven economic MPC scheme is presented using measured input-output trajectories without a prior system identification step. Our method uses Hankel matrices which include one input-output data trajectory for prediction in economic MPC, while persistently exciting of the input generating the data is needed. One of the novelties of the presented framework is directly verifying the strong duality property from input-output trajectory with the general cost function, considered as the supply rate. This is used to find a Lyapunov function for data-driven economic MPC. Under the strong duality assumption, asymptotic stability of the economical optimal equilibrium point for the closed-loop system with terminal equality constraint is guaranteed. The proposed data-driven economic MPC approach needs only persistently exciting data trajectory along with an upper bound on the system order and need no model description and no online parameter estimation. The proposed scheme applicability compared to the existing model-based economic MPC and data-driven MPC is illustrated for continuous stirred tank reactor (CSTR) and a numerical example and the robustness of the proposed scheme is evaluated in the case of measurement noise, as well as nonlinear model for CSTR system.

АНАЛИЗ КАЧЕСТВА ВЕДЕНИЯ МЕДИЦИНСКОЙ ДОКУМЕНТАЦИИ ПРИ ОЦЕНКЕ ДЕЯТЕЛЬНОСТИ СТОМАТОЛОГИЧЕСКОЙ КЛИНИКИ

One of the criteria for assessing the quality of medical care is the complete maintenance of medical records. Defects in the preparation of medical documents lead to serious errors, such as incorrect diagnosis, unreasonable choice of diagnostic methods and treatment. To clarify the causes of their occurrence and adverse consequences, the study and analysis of medical records in dental organizations is of no small importance. Properly completed medical documentation serves as the basis for conducting forensic investigations within the framework of a criminal case in case of defects in the provision of medical dental care. The outpatient card of a dental patient is the object of quality control of medical care in dental organizations in the event of conflict situations. Purpose of the study: To analyze the quality control and safety of medical activities and the examination of the quality of medical dental care carried out in the dental clinic of the Military Medical Academy named after. CM. Kirov. Material and methods. During the study, analytical and statistical methods were used. The collection of primary information was carried out on the basis of data from primary medical documentation - 1067 outpatient records of dental patients. Results and condemnation. A statistically significant influence of a doctor’s work experience on the completeness of providing information about patients’ complaints was revealed. Doctors with less experience provide more complete descriptions of patient complaints. Among all complaints, aesthetic ones were most often described; complaints of a morphological and functional nature were noted quite rarely. In the cards of form No. 043/u, in 46.67% there was no information about the bite, the hygiene index was not determined, treatment plans and visit diaries were not filled out correctly. Conclusions. Internal quality assessment helps to detect defects in filling out dental patient outpatient records. The importance of adequate medical record keeping is beyond doubt; the form of the medical record must meet the needs of dentists and contain information that complies with the legal and regulatory framework.

Suppression of Initial Charging Torque for Electric Drive-Reconfigured On-Board Charger

This paper presents a new electric drive-reconfigured on-board charger and initial electromagnetic torque suppression method. This proposed reconfigured on-board charger does not need many components added to the original electric drive system: only a connector is needed, which is easy to add. Specifically, the inverter for propulsion is reconfigured as a buck chopper and a conduction path to match the reconfigured windings. Two of the machine phase windings serve as inductors, while the third phase winding is reutilized as a common-mode inductor. In addition, the initial charging torque is generated at the outset of the charging process, which may cause an instant shock or even rotational movement. In order to prevent vehicle movement, the reason for the charging torque and suppression method were analyzed. Further, predictive control of the model based on mutual inductance analysis was adopted, where the charging torque was directly used as a control object in the cost function. Finally, experimental performances were applied to verify the proposed reconfigured on-board charger under constant current and constant voltage charging.

A Comprehensive Review on Advanced Control Methods for Floating Offshore Wind Turbine Systems above the Rated Wind Speed

This paper presents a comprehensive review of advanced control methods specifically designed for floating offshore wind turbines (FOWTs) above the rated wind speed. Focusing on primary control objectives, including power regulation at rated values, platform pitch mitigation, and structural load reduction, this paper begins by outlining the requirements and challenges inherent in FOWT control systems. It delves into the fundamental aspects of the FOWT system control framework, thereby highlighting challenges, control objectives, and conventional methods derived from bottom-fixed wind turbines. Our review then categorizes advanced control methods above the rated wind speed into three distinct approaches: model-based control, data-driven model-based control, and data-driven model-free control. Each approach is examined in terms of its specific strengths and weaknesses in practical application. The insights provided in this review contribute to a deeper understanding of the dynamic landscape of control strategies for FOWTs, thus offering guidance for researchers and practitioners in the field.

Knowledge-shareable adaptive deep dynamic programming for hierarchical generation control of distributed high-percentage renewable energy systems

The increased proportion of distributed renewable energy sources connected to systems leads to frequency regulation difficulty, such as uncoordinated algorithms, inconsistent optimization and control objectives, and long training time. This work proposes a knowledge-shareable adaptive deep dynamic programming (KSADDP) to improve the active control accuracy and generation economy of the proposed hierarchical generation control framework, which contains two-layer control structures. In the first layer, droop control is employed to optimize the outputs of controllable generators, follow the frequency changes, reduce frequency deviation, and improve the operation economy of battery energy storage systems. In the second layer, a KSADDP is proposed to mitigate local optimum and accelerate the hybrid cooperative structure optimization by sharing the parameters of neural networks. These two layers synergistically optimize control performance and reduce generation costs. The simulation results of a three-high-percentage renewable energy system show that: with two layers of cooperation and sharing training information, the KSADDP outperforms the comparison algorithms in seven evaluation indices and reduces the generation cost by 4.85%–7.41 % compared to the comparison algorithms. The proposed KSADDP cooperates the time scales between multiple layers, cooperates the objectives between multiple layers, increases the parameter-sharing process, and reduces training time.

Control of elongated plasmas in superconductive tokamaks in the absence of in-vessel coils

Abstract The roadmap for the commissioning and first operations of superconductive tokamaks envisages the possibility of running discharges with fairly elongated plasmas before the complete installation of the in-vessel components, including vertical stabilization coils, or any other specific sets of coils to be used for the magnetic control of fast transients. In the absence of dedicated actuators, the magnetic control system shall perform the essential fast control actions by using the out-vessel superconductive coils, if needed. These are typically less efficient in reacting to fast transients, due to the shielding effect of the vessel and imply a coupling with other control tasks relying
on the same actuators, such as plasma current, position, and shape control. Hence, effective actuator-sharing strategies must be put in place. This paper presents an architecture and a possible control strategy that is able to cope with vertically unstable elongated plasmas subject to fast varying disturbances, in the absence of dedicated in-vessel coils. The architecture exploits a model-based actuator-sharing approach to effectively accomplish the main magnetic control objectives while minimizing the crosscouplings among the various tasks. The effectiveness of the approach is demonstrated by means of nonlinear simulations of realistic JT-60SA scenarios. In particular, an
isoflux plasma shape controller is integrated with plasma current control and vertical stabilization. The proposed control approach proves to control vertical displacement events and plasma deformations due to fast variations of poloidal beta with satisfactory performance.

Theoretical substantiation of system for organising preventive treatment of asphalt concrete road pavements

Introduction. Over the past 20 years, the fleet of vehicles in the Republic of Belarus has increased significantly, and, consequently, the intensity of traffic on roads with a proportional increase in wear and tear of their surfaces. The need to protect asphalt concrete pavements from premature destruction dictates the search for new technological solutions. To effectively protect asphalt concrete pavements from the complex effects of water and traffic loads in the autumn-winter and spring-winter periods, the author has developed and implemented one of the options for protecting asphalt concrete pavements of a highway – treating them with a hydrophobic preventive Protekt- 01composition.Materials and methods. The research used theoretical and practical results from the implementation of the developed hydrophobic prophylactic composition.Results. The article presents an overview of the state of the problem of preventing destruction of asphalt concrete pavements abroad and in the Republic of Belarus, an analysis of the measures taken to implement the developed hydrophobic preventive Protekt-01composition at transport infrastructure facilities, and also, based on the data obtained from production testing a ‘System for organizing preventive treatment’ has been proposed, which will be aimed at preventing the beginning and future destruction of the asphalt concrete pavement of highways and will be based on monitoring the technical condition of the control object, planning, organizing, implementing and managing preventive and repair measures using navigation equipment and software that makes it possible to optimize the balance of costs and road surface defects.Originality. Thus, based on the theoretical substantiation and the results of practical implementation of the developed composition, the following are proposed:- method for ensuring the operation of a control system for liquid road-building materials which enables to eliminate overconsumption of the distributed substance;- ‘System for organizing preventive treatment’, which enables to increase the service life of asphalt concrete pavement by 1.2–1.5 times.

Dynamics Event-Triggered-Based Time-Varying Bearing Formation Control for UAVs

This article addresses the leader-follower formation maneuver control problem of multiple unmanned aerial vehicles (UAVs), taking into account the time-varying velocity and time-varying relative bearing. An event-triggered bearing-based distributed velocity observer was designed, using only the desired position and velocity of the leaders. Furthermore, a dynamic event-triggered mechanism was introduced to reduce continuous communication between UAVs, thus effectively saving communication bandwidth and resources. Building on this, a bearing-only formation maneuver control strategy was proposed, integrating the event-triggered velocity observer with the backstepping control approach. To conclude, numerical simulations have been conducted to confirm the effectiveness of the proposed scheme in accomplishing formation maneuver control objectives, including translation, scaling, and rotation control. Furthermore, the advantages of the dynamic event-triggering strategy have been demonstrated through comparative simulations with traditional event-triggering strategies. Additionally, the effectiveness of the proposed observer and controller has been demonstrated by a comprehensive hardware-in-the-loop (HITL) simulation example.

Global joint position regulation of a class of torque-driven robot manipulators within actuators prescribed safe operating torque–speed area

This paper addresses the joint position regulation of a class of n degrees of freedom torque-driven robot manipulators under a novel practical motivated control objective: Simultaneous Regulation & Prescribed Safe Operating Area (SR&PSOA). More specifically, torque–speed characteristic safe limit functions associated to each actuator are taking into account to ensure that besides of global joint positioning, the requested torque control inputs to robot actuators remain inside user prescribed safe operating torque–speed areas, so avoiding thermal and physical actuator damages. A static smooth nonlinear controller is proposed to achieve global position regulation under prescribed speed-depending bound torque input. Numerical simulations and experimental results are included to illustrate the effectiveness of the proposed controller.

Frequency Control of Interconnected Power System via SBO assisted Simultaneous Tuning Strategy in Presence of DFIG

To achieve the objectives of the automatic generation control (AGC) of wind integrated interconnected power system (WIIPS), better tuning and control strategies are required. This paper suggests simultaneous tuning strategy for the AGC and wind system controllers to improve the stability of the WIIPS. The bulk amount of wind is integrated into the grid using the doubly fed induction generator (DFIG) and its simplified model is used to simulate the WIIPS. Initially, classical controllers are opted in AGC mechanism to reduce the frequency disturbances caused by the load and wind generation uncertainties. Further, classical controllers of WIIPS are replaced with cascade controllers to enhance the system frequency profile during the disturbances. The optimal set of solutions of the classical and cascade controllers are examined by the satin bowerbird optimizer (SBO) with the help of integral square error as fitness function of the optimization problem. Comparisons are provided to show the merits of the WIIPS over normal interconnected power system, cascade controller over classical controller and simultaneous tuning strategy over regular tuning mechanism.

Robust Predictive Control Strategy of SCIG-based Drive System

This article presents a robust finite control set predictive scheme for a stand-alone squirrel cage induction generator (SCIG) drive. This technique is considered an alternative to the drive system due to the inclusion of system nonlinearities and fast dynamic response. The control objective in the distributed generation environment is to fix the output voltage to follow the stand-alone requirement. The strategy establishes optimized switching instants for cost function minimization for both source and load converter control and diminished cross-coupling amid active and reactive power during transient scenarios. The scheme is designed to achieve the minimal effect caused by the parameter uncertainties. During source and load changes, this work will also address the maintenance of dc-link voltage, machine, and load variables at the set value, supported by machine and load-end converter control to achieve stand-alone load objectives. In addition, the presented scheme is also tested with random variation of speed to check the efficacy of the control configuration. The drive performance is evaluated by simulation using MATLAB/Simulink environment. Comprehensive real-time findings obtained from a scaled laboratory test bench using dSPACE-1104 are provided to verify the feasibility of the predictive solution.

Cooperative Decision-Making Approach for Multiobjective Finite Control Set Model Predictive Control Without Weighting Parameters

Finite control set model predictive control (FCS-MPC) has gained increasing popularity as an emerging control strategy for electrical drive systems. However, it is still a challenging task to optimize weighting parameters, as multiple objectives are involved in the customized cost function. A cooperative decision-making approach for FCS-MPC is proposed in this article, to solve the optimization problems with manifold control objectives. By splitting the cost function, the optimization problem underlying multi-objective FCS-MPC is separated into a series of decomposed optimization problems. By doing so, the dimension of the decomposed problem is reduced to one. To collect the information for decision-making, an efficient sorting algorithm is applied for each control objective. The theory behind the cooperative decision-making approach is comprehensively analyzed, to validate both the effectiveness and efficiency of the proposed scheme. More specifically, the highlight is the adaptive mechanism on the number of desired candidates, to obtain a decent performance for torque and flux. The candidate which minimizes the switching frequency is selected as the optimal. The proposed scheme is experimentally verified and compared with the existing FCS-MPC without weighting parameters.

Variable-pitch power regulation of tethered-wing systems based on robust gain-scheduling H-infinity control

In this paper, we address the power regulation of tethered-wing systems and illustrate the benefits of employing variable-pitch control to alleviate dynamic mechanical loads and power fluctuations. The proposed control scheme is based on a strategy to maximize the generated power during low-speed wind and prevent force and power overloads during the high-speed wind. To implement this strategy, we employ a tether reeling-speed controller to maintain optimal generator speed in low-speed winds, and a MIMO speed-force controller to prevent power surges in high-speed winds. Additionally, the minimization of the wing’s pitch angle activity during high-speed wind is considered as another control objective in the proposed scheme. The controllers are synthesized using H∞ method and are made robust with respect to the system’s dynamic and parametric uncertainties. The synthesis procedure is predicated on a linear parameter varying (LPV) expression of the dynamics of the system. The effectiveness of the strategy and the performance of the controllers are showcased through simulations conducted with a comprehensive 3-dimensional simulator for tethered-wing systems.

Comparative efficacy of immune checkpoint inhibitors combined with chemotherapy in patients with advanced driver-gene negative non-small cell lung cancer: A systematic review and network meta-analysis

ObjectiveTo evaluate the efficacy of different combinations of immune checkpoint inhibitors (ICIs) and chemotherapy (CT) in the treatment of advanced non-small cell lung cancer (NSCLC). MethodsWe obtained relevant randomized controlled trials (RCTs) from databases such as PubMed, Embase, Web of Science, and The Cochrane Library up to May 31, 2023. The analysis of clinical prognostic factors was performed using R 4.2.3 and STATA 15.0. The main outcomes measured were overall survival (OS) and progression-free survival (PFS), while secondary outcomes included the objective response rate (ORR), disease control rate (DCR), and treatment-related adverse events of grade 3–5 severity (Grade ≥3 TRAE). ResultsA total of 17 randomized controlled trials (RCTs) were conducted between 2012 and 2023, involving 7792 patients. These trials evaluated 11 different treatment methods. The results of these trials showed that in terms of overall survival (OS) and progression-free survival (PFS), the combination of tislelizumab with chemotherapy and the combination of camrelizumab with chemotherapy were particularly effective. Moreover, when compared with other combination therapies, pembrolizumab combined with chemotherapy showed superiority in terms of disease control rate (DCR) and objective response rate (ORR). Subgroup analyses further demonstrated that the addition of immune checkpoint inhibitors (ICIs) to chemotherapy significantly improved PFS and OS in patients without liver metastasis and in those with brain metastasis. Additionally, carboplatin-based combination therapy was found to confer favorable survival benefits in terms of PFS, while cisplatin-based combination therapy showed the most favorable outcomes in terms of OS. The results of subgroup analyses for overall survival (OS) showed that the combination of immunotherapy and chemotherapy yielded positive outcomes in specific subgroups. These subgroups were characterized by PD-L1 Tumor Proportion Score (TPS) of 50 % or higher, usage of anti-PD-1 medications, age below 65, male gender, smoking history, and non-squamous cell carcinoma histology. Superior effectiveness was demonstrated only in extending the progression-free survival (PFS) of female patients and patients with squamous carcinoma. Meanwhile, other patient cohorts did not show the same level of improvement. ConclusionsTislelizumab, camrelizumab or pembrolizumab combined with chemotherapy may be the optimal first-line treatment strategies for NSCLC.

Optimized model predictive control for solar assisted earth air heat exchanger system in greenhouse

Agricultural greenhouses play a crucial role in addressing the threat of climate change to agricultural systems. The greenhouse systems control exhibits nonlinear characteristics and large lag, both affecting the regulation of the greenhouse thermal environment. In this paper, a control strategy was designed to set the dynamic reference value of the control objective of the greenhouse model, considering factors such as solar radiation and the heating capacity of water body. A complete greenhouse model was developed using TRNSYS, and then the model predictive control building and optimization were implemented through MATLAB. The control effects of traditional proportional-integral-differentiation control, initial model predictive control, and optimized model predictive control were compared. The results showed that the regulation of greenhouse temperature was improved by 10.6 % in the coldest mouth compared to the conventional proportional-integral-differentiation control by the optimized model predictive control. During a typical cold month, the violation of constraints was reduced by 29.7 % by dynamically setting the target of the greenhouse with the optimized model predictive control. The performance of greenhouse climate control is enhanced by the proposed optimized model predictive control method, ensuring a stable regulation of the crop growth environment.

Multifunctional bionanohybrids of graphene oxide/β-cyclodextrin for applications in methylene blue adsorption, solvent response, and smart light-driven

In this study, a multifunctional graphene oxide/β-cyclodextrin bionanohybrids (BWGO) was prepared successfully. The structure, morphology, adsorption capacity, solvent response, and light-driven properties of the BWGO were systematically investigated through the in-situ formation of an asymmetric gradient structure. The maximum adsorption value of BWGO based on bio-nanohybrids was 81.27 mg·g−1 for methylene blue (MB), which fitted the Langmuir isotherm in accordance with the pseudo-secondary kinetic model. Additionally, the host–guest interaction model of between BWGO and MB (in ratios of 1:1 or 1:2) was proposed by ROESY. Remarkably, the BWGO exhibited not only unique and exceptional responses to organic hazard solvents, self-driven, and photothermal responses, but also demonstrated controllable object loading and shape memory useful for soft grasping. More importantly, the related mechanisms of adsorption and behaviors driven by multiple stimuli (solvent, light) were elucidated through the host–guest interaction, wrinkled structure, gradient solvent swelling effects, and conformational changes in the macromolecular chain. This work not only introduces the multifunctional bionanohybrid materials with a wrinkled structure for the adsorption of organic dyes, but also opens avenues for potential applications in smart windows, soft grasping, and biomimetic industrial materials.

Синтез параметрически грубых систем управления с регуляторами и наблюдателями состояния на основе грамианных технологий

Automatic control systems based on regulators with state observers are effective means to control linear and linearized objects of a high degree of complexity. One of the key problems in the synthesis of modal systems is the development of parametrically rough (robust) systems that retain their performance, as well as the main quality indicators with possible variations of the parameters of both the control object and the controller itself. The synthesis of a robust system with a state observer is carried out by the modal control method based on the matrix model of the controlled object. To ensure the parametric robustness of the system, the authors have proposed a technique which based on the mathematical apparatus of Gramians of controllability and observability as well as on the similarity transformation of observer matrices. Computer simulation of the system with state controller and observer is carried out by means of the MatLab software. The authors have proposed a method to form an observer state structure that is optimal in the sense of parametric roughness of the system, which is based on the procedure of transforming the similarity of the object model. And the transformation matrix is formed by varying the singular numbers of the controllability and observability gramians. The proposed method allows us to obtain an observer structure with a certain ratio of controllability and observability that ensures the fulfillment of the condition of parametric roughness i.e., the absence of positive feedback in the control device. The results obtained make it possible to clearly demonstrate the high efficiency of using the Gramian method for the synthesis of control systems with state observers with low sensitivity to variations of the controller own parameters.

Determining the Quality of Measuring the Level of Lower Extremity Joint Movement in Inclusive Physical Education Using Electronic IT Resources

Objectives. The study aimed to investigate the quality characteristics of the tool developed based on electronic IT resources for measuring the level of movements in the joints of the lower limbs of students with disabilities caused by injuries. Material and methods. The experimental study involved 32 first-year students who had sustained lower limb injuries as a result of the war and were in remission. The methods used included analysis, synthesis, systematization, generalization, technical modeling, pedagogical experiments, and mathematical statistics. Results. A means of measuring movements in the joints of the lower limbs has been developed using electronic IT resources. The basis of the tool is a measuring line consisting of a printed circuit board on which is placed a design of capacitive sensors, a switching line, and a signal converter that measures the signal received by the sensors. The measurement results are transmitted to the controller and then to the PC via an interface implemented based on Bluetooth wireless technology. To implement the measuring tool, a controller is used, which has a board built on the synthesis of the Arduino electronic hardware platform and the Raspberry Pi minicomputer. The test results are displayed on the PC monitor screen. The determination of the qualitative characteristics of the test, in the case of recording the results of a tool developed on the basis of electronic IT resources for measuring the level of movements in the joints of the lower limbs of students with disabilities, established that the level of reliability of the test is above 0.90 (“excellent”) validity – from 0, 6 (“high”). Empirical data collected directly from the experiment have a low level of reliability: qualitative indicators of reliability in the range are below 0.70 (“may have limited applicability”), validity – < 0.3 (“low validity”). Conclusions. Developed based on electronic IT resources, the tool for measuring the level of movements in the joints of the lower limbs of students with disabilities due to limb injuries has significant advantages, such as the availability of functions, ease of use and efficiency. Ensuring high efficiency and objectivity of control contributes to performing control operations in real-time. By using assessment tools with a high level of reliability and validity, we ensure the detection of reliable changes in the state of the joints of the lower limbs of students with disabilities, thus eliminating the influence of errors in making managerial decisions in the planning process of their PE.