Direct Control Research Articles

Room for responsibility: Kant on direct doxastic voluntarism

ABSTRACT Kant's theory of assent seems to combine two incompatible claims that (i) we are responsible for our assent and (ii) we have no direct voluntary control over our assent. But how can we be responsible for something over which we have no direct voluntary control? Scholars have tried to resolve this tension by arguing that, according to Kant, assent is under our indirect voluntary or intellectual control. This paper defends a different solution. It is argued that contrary to first impressions, Kant is actually committed to the view that most assent is under our direct voluntary control, which, in turn, accounts for our doxastic responsibility. From this emerges the outline of a unified Kantian theory of doxastic agency.

Dual-Loop μ-Synthesis Direct Thrust Control for Turbofan Engines

As the power unit of an aircraft, the engine’s primary task is to provide the demanded thrust, making research on direct thrust control crucial. However, being a complicated multivariable system, effective multivariable direct thrust control methods are currently lacking. The main content of this paper is threefold. First, it presents a dual-loop multivariable μ-synthesis direct thrust control scheme for mixed-exhaust low-bypass turbofan engines, which is a typical rotationally symmetric machine. The scheme adjusts fuel flow for thrust control and nozzle area to control the turbine pressure ratio, ensuring thrust tracking while maintaining the engine’s key parameters within safe limits. Second, a fast, accurate thrust estimation algorithm based on aerodynamic thermodynamics and component characteristics is introduced. At last, considering the model uncertainties between off-design and design points, a weight function frequency shaping μ-synthesis control design method is proposed to address internal loop coupling and external disturbance suppression. Nonlinear simulations within the flight envelope show that μ-synthesis direct thrust control achieves robust servo tracking and disturbance rejection, with a maximum steady-state thrust error of no more than 0.1%, and the key parameters are not over their safety boundaries.

Demand response strategies for air-conditioning systems based on direct load control: Considering envelope structures

In recent years, the surge in rural air-conditioning (AC) electricity consumption has led to an overall increase in peak loads in both winter and summer, presenting a major challenge to the reliability and stability of low-voltage distribution networks. Demand response (DR) strategy not only relieves the peak load, but also reduces the energy consumption and achieves the purpose of energy saving and emission reduction. Among the many DR strategies, direct load control (DLC) stands out as an effective way to quickly reduce building AC loads. Meanwhile, the building envelope is also one of the important factors affecting the AC load. A typical rural house in the Xi’an area of Shaanxi Province was used as a case study. A ground source heat pump system was developed, installed and used as an experimental platform in order to aid the study. Therefore, in this study, the combination of external envelope and DLC strategies was investigated to establish a simulation model of energy consumption in rural building complexes. Two DLC load control strategies were implemented under different external envelope conditions for annual AC energy simulation. The results show that the thickness of the external insulation layer has the greatest impact on the AC load of the building compared to the window-wall ratio and orientation. With a thickness of 0 mm–75 mm insulation, the DCCM strategy can effectively reduce AC energy consumption by 16%–18%; With a thickness of 0 mm–75 mm insulation, the TSCM strategy can effectively reduce AC energy consumption by 5%–8%.

A Diffusion Approach to Radiance Field Relighting using Multi‐Illumination Synthesis

AbstractRelighting radiance fields is severely underconstrained for multi‐view data, which is most often captured under a single illumination condition; It is especially hard for full scenes containing multiple objects. We introduce a method to create relightable radiance fields using such single‐illumination data by exploiting priors extracted from 2D image diffusion models. We first fine‐tune a 2D diffusion model on a multi‐illumination dataset conditioned by light direction, allowing us to augment a single‐illumination capture into a realistic – but possibly inconsistent – multi‐illumination dataset from directly defined light directions. We use this augmented data to create a relightable radiance field represented by 3D Gaussian splats. To allow direct control of light direction for low‐frequency lighting, we represent appearance with a multi‐layer perceptron parameterized on light direction. To enforce multi‐view consistency and overcome inaccuracies we optimize a per‐image auxiliary feature vector. We show results on synthetic and real multi‐view data under single illumination, demonstrating that our method successfully exploits 2D diffusion model priors to allow realistic 3D relighting for complete scenes.

DTC-SVM strategy of double star induction motor using sliding mode controller enhanced by fuzzy logic

Extensive research and numerous articles on Direct Torque Control (DTC) systems have consistently highlighted various deficiencies associated with the employment of hysteresis control units. Specifically, these issues include significant torque and stator flux ripples, as well as distortions in stator current. Additionally, the sensitivity to parametric variations stemming from Proportional-Integral (PI) controllers poses a challenge due to the complexities involved in their adjustment. To address these drawbacks, this article explores the implementation of Space Vector Modulation DTC (SVM-DTC) technology integrated with a Sliding Mode Controller (SMC). The proposed control scheme for DTC amalgamates the benefits derived from SMC control and the SVM algorithm. The SMC controller is utilized to oversee PI controllers, employing this nonlinear technique ensures superior dynamic performance and robust resistance against external disturbances. Notwithstanding its advantages, one notable issue with SMC is chattering. To mitigate this phenomenon, we adopt an approach that integrates Fuzzy Logic with SMC. By replacing the saturation function (Sat) with a fuzzy inference system, we effectively minimize chattering. The simulation is conducted using MATLAB SIMULINK. Comparative analysis between DTC-SVM strategy and traditional methods including standard SMC and Fuzzy-enhanced Sliding Mode Controller (FSMC), demonstrates that our hybrid nonlinear controller exhibits high efficiency and remarkable robustness.

Unlocking the Potential: An In-Depth Analysis of Factors Shaping the Success of Smart and Bidirectional Charging in a Cross-Country Comparison

The increasing utilisation of the distribution grid caused by the ramp-up of electromobility and additional electrification can be eased with flexibility through smart and bidirectional charging use cases. Implementing market-oriented, grid-, and system-serving use cases must be tailored to the different national framework conditions, both in technical and regulatory terms. This paper sets out an evaluation methodology for assessing the implementation of smart and bidirectional charging use cases in different countries. Nine use cases are considered, and influencing factors are identified. The evaluation methodology and detailed analysis are applied to Austria, the Czech Republic, Denmark, Finland, France, Germany, Italy, the Netherlands, Spain, and Sweden. In every country, the implementation of vehicle-to-home use cases is possible. Realising market-oriented use cases is feasible in countries with a completed smart meter rollout and availability of tariffs with real-time pricing. Grid-serving and ancillary service use cases depend most on country-specific regulation, which is why no clear trend can be identified. Use cases that require direct remote controllability are the most distant from implementation. The overarching analysis provides orientation for the design of transnational products and research and can serve as a basis for a harmonisation process in regulation.

Application of DPC to improve the integration of DFIG into wind energy conversion systems using FOPI controller

While the direct power control (DPC) approach has proven effective in improving the efficiency of wind energy conversion systems (WECS) using doubly fed induction generators (DFIG), its applicability is currently confined to a single usage and has not been extended to meet numerous applications. This work aimed to modify the implementation of DPC in WECS-DFIG for several objectives. This is accomplished by updating the reference power of the conventional DPC method into an adapted one to achieve two goals independently. The first objective is to track the maximum power during wind speed variations. This tracking is performed by updating the reference power to match the maximum available power at the current wind speed. The second purpose is to ensure that the WECS remains connected to the grid and continues to operate smoothly even in the event of faults; supporting fault-ride through (FRT) capability. That is achieved by reducing the reference power during these faults. The discrimination between these two objectives is based on the voltage level at the point of connecting WECS to the grid. The controller provided is an improved fractional order PI controller developed using arithmetic optimization technique (AOA). A comparison between the AOA and cuckoo search is presented. The results demonstrate the efficacy of the suggested configuration and regulator in enhancing the performance of integrating DFIG into the WECS in the presence of wind fluctuations and short circuit faults occurring. It is worth noting that AOA is better than cuckoo search in fine-tuning the settings of the FOPI controller.

Optimization-Based Pairwise Interaction Point Process (O-PIPP): A Precise and Universal Retinal Mosaic Modeling Approach.

A retinal mosaic, the spatial organization of a population of homotypic neurons, is thought to sample a specific visual feature into the feedforward visual pathway. The purpose of this study was to propose a universal modeling approach for precisely generating retinal mosaics and overcoming the limitations of previous models, especially in modeling abnormal mosaic patterns under disease conditions. Here, we developed the optimization-based pairwise interaction point process (O-PIPP). It incorporates optimization techniques into previous simulation approaches, enabling directional control of the simulation process according to the user-designed optimization target. For the convenience of the community, we implemented the O-PIPP approach into a Python package and a website application. We showed that the O-PIPP can generate more precise neural spatial patterns of healthy and diseased mosaics compared to previous phenomenological approaches. Notably, through modeling the retinal neural circuitry with O-PIPP-simulated retinitis pigmentosa cone mosaics, we elucidated how the cone mosaic rearrangement impacted the information processing of ganglion cells. The O-PIPP provides a precise and universal tool to simulate realistic mosaics, which could help to investigate the function of retinal mosaics in vision.

Experimental analysis of enhanced finite set model predictive control and direct torque control in SRM drives for torque ripple reduction

The magnet-less switched reluctance motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the emerging direct torque control (DTC) operated magnitude flux and torque estimation with voltage vectors (VVs) gives high torque ripples due to the selection of effective switching states and sector partition accuracy. On the other hand, the existing model predictive control (MPC) with multiple objective and optimization weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPC can result in high torque ripples. This paper proposed a finite set (FS)-MPC with a single cost function objective without weighting factor: the predicted torque considered to evaluate VVs to minimize the ripples further. The selected optimal VV minimizes the SRM drive torque and flux ripples in steady and dynamic state behaviour. The classical DTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in SRM drives experimental results to prove the effective minimization of torque and flux ripples compared to the existing DTC.

Delayed reinforcement learning converges to intermittent control for human quiet stance

The neural control of human quiet stance remains controversial, with classic views suggesting a limited role of the brain and recent findings conversely indicating direct cortical control of muscles during upright posture. Conceptual neural feedback control models have been proposed and tested against experimental evidence. The most renowned model is the continuous impedance control model. However, when time delays are included in this model to simulate neural transmission, the continuous controller becomes unstable. Another model, the intermittent control model, assumes that the central nervous system (CNS) activates muscles intermittently, and not continuously, to counteract gravitational torque. In this study, a delayed reinforcement learning algorithm was developed to seek optimal control policy to balance a one-segment inverted pendulum model representing the human body. According to this approach, there was no a-priori strategy imposed on the controller but rather the optimal strategy emerged from the reward-based learning. The simulation results indicated that the optimal neural controller exhibits intermittent, and not continuous, characteristics, in agreement with the possibility that the CNS intermittently provides neural feedback torque to maintain an upright posture.

Who was entrusted with the development of the “Eastern Lands of the Ainu” in 1799 (According to the Diary Entries of Matsuda Denjuro)

In 1799, the military government Bakufu 幕府 transferred the Lands of the Ainu Ezochi 蝦夷地, which had previously been subordinate to the Matsumae Family 松前藩, under its direct control. These territories were divided into the Eastern Lands of the Ainu Higashi Ezochi 東蝦夷地 and the Western Lands of the Ainu Nishi Ezochi 西蝦夷地. The Japanese also included the southern islands of the Kuril ridge, Kunashir and Iturup, in the Eastern Lands; the border between the lands ran along the island of Hokkaido. It is known that by this time Japanese administration had been created only in the southern part of this island. It was extremely important for the bakufu to establish full control over these territories, as well as to prevent the penetration of Russian researchers and traders into the lands of the Ainu. Proxies of the military government were sent there to carry out this task. The diary entries of Matsuda Denju:ro:’s Tales of the Northern Barbarians provide a list of the leaders of the first sea crossing in Japanese history from Edo to Akkeshi in Hokkaido. An analysis of the titles and ranks of the listed leaders allows us to see the seriousness of the military government’s approach to preparing the expedition. This article is devoted to the translation and analysis of the list given in the Tales.

Interactive Path Editing and Simulation System for Motion Planning and Control of a Collaborative Robot

Robots in hazardous environments demand precise and advanced motion control, making extensive simulations crucial for verifying the safety of motion planning. This paper presents a simulation system that enables interactive path editing, allowing for motion planning in a simulated collaborative robot environment and its real-world application. The system includes a simulation host, a control board, and a robot. Unity 3D on a Windows platform provides the simulation environment, while a virtual Linux environment runs ROS2 for execution. Unity sends edited motion paths to ROS2 using the Unity ROS TCP Connector package. The ROS2 MoveIt framework generates trajectories, which are synchronized back to Unity for simulation and real-world validation. To control the six-axis Indy7 collaborative robot, we used the MIO5272 embedded board as an EtherCAT master. Verified trajectories are sent to the target board, synchronizing the robot with the simulation in position and speed. Data are relayed from the host to the MIO5272 using ROS2 and the Data Distribution Service (DDS) to control the robot via EtherCAT communication. The system enables direct simulation and control of various trajectories for robots in hazardous environments. It represents a major advancement by providing safe and optimized trajectories through efficient motion planning and repeated simulations, offering a clear improvement over traditional time-consuming and error-prone teach pendant methods.

Utilizing Metasurfaces for Directional Control of LED Emission

This study provides a detailed modeling and analysis of four different three-dimensional GaN-based LED structures. The results reveal that incorporating DBRs effectively focuses light and enhances the light extraction efficiency (LEE). Additionally, the integration of Metasurface in the Micro-LED+DBRs+M structure allows for precise control of light emission direction and further radiation focusing. Furthermore, in the Micro-LED+DBRs+M2 structure with improved periodic nanocolumns, the light beam can be deflected simultaneously in multiple directions. These findings offer new possibilities for the advancement of LED technology.

Enhancing LVRT capability of single stage grid connected PV system in accordance with Indian grid code using proportional direct axis current control technique

Enhancing LVRT capability of single stage grid connected PV system in accordance with Indian grid code using proportional direct axis current control technique

Novel deadbeat direct torque and flux control for interior permanent magnet synchronous motor

Novel deadbeat direct torque and flux control for interior permanent magnet synchronous motor

Power regulation of variable speed multi rotor wind systems using fuzzy cascaded control

Power quality is a crucial determinant for integrating wind energy into the electrical grid. This integration necessitates compliance with certain standards and levels. This study presents cascadedfuzzy power control (CFPC) for a variable-speed multi-rotor wind turbine (MRWT) system. Fuzzy logic is a type of smart control system already recognized for its robustness, making it highly suited and reliable for generating electrical energy from the wind. Therefore, the CFPC technique is proposed in this work to control the doubly-fed induction generator (DFIG)-based MRWT system. This proposed strategy is applied to the rotor side converter of a DFIG to improve the current/power quality. The proposed control has the advantage of being model-independent, as it relies on empirical knowledge rather than the specific characteristics of the DFIG or turbine. Moreover, the proposed control system is characterized by its simplicity, high performance, robustness, and ease of application. The implementation of CFPC management for 1.5 MW DFIG-MRWT was carried out in MATLAB environment considering a variable wind speed. The obtained results were compared with the direct power control (DPC) technique based on proportional-integral (PI) controllers (DPC-PI), highlighting that the CFPC technique reduced total harmonic distortion by high ratios in the three tests performed (25%, 30.18%, and 47.22%). The proposed CFPC technique reduced the response time of reactive power in all tests by ratios estimated at 83.76%, 65.02%, and 91.42% compared to the DPC-PI strategy. Also, the active power ripples were reduced by satisfactory proportions (37.50%, 32.20%, and 38.46%) compared to the DPC-PI strategy. The steady-state error value of reactive power in the tests was low when using the CFPC technique by 86.60%, 57.33%, and 72.26%, which indicates the effectiveness and efficiency of the proposed CFPC technique in improving the characteristics of the system. Thus this control can be relied upon in the future.

Integrated Weed Management: A Comprehensive Review of Conventional, Non-Conventional, and Emerging Strategies for Sustainable Agriculture

This manuscript comprehensively reviews integrated weed management (IWM) strategies, emphasizing the need for sustainable agricultural practices. It explores conventional methods, such as herbicide and mechanical control, and non-conventional techniques, including mulching, cover crops, and thermal methods. The review also delves into emerging technologies like precision agriculture, genomic approaches, and robotic weed control. The discussion is framed around five pillars of IWM: diverse cropping systems, cultivar selection, field and soil management, direct control, and monitoring and evaluation. Environmental and socioeconomic impacts of weed management are considered, highlighting the need for a new paradigm that integrates diverse control tactics to enhance agricultural resilience and sustainability.

Egyptian Art in Colonized Nubia: Representing Power and Social Structure in the New Kingdom Tombs of Djehutyhotep, Hekanefer and Pennut

Monumental rock-cut tombs decorated with wall paintings or reliefs were rare in New Kingdom colonial Nubia. Exceptions include the 18th Dynasty tombs of Djehutyhotep (Debeira) and Hekanefer (Miam), and the 20th Dynasty tomb of Pennut (Aniba). The three tombs present typical Egyptian artistic representations and inscriptions, which include tomb owners and their families, but also those living under their direct control. This paper compares the artistic and architectural features of these decorated, monumental rock-cut tombs in light of the archaeological record of the regions in which they were located in order to contextualize art within its social setting in colonized Nubia. More than expressing cultural and religious affiliations in the colony, art seems to have been essentially used as a tool to enforce hierarchization and power, and to define the borders of the uppermost elite social spaces in New Kingdom colonial Nubia.

A COMBINED MANAGEMENT MODEL FOR RESTRUCTURING A REPRODUCTION SYSTEM

This paper considers a management model for a reproduction system with the synchronous change of the technological matrix during its restructuring. Such models can be characterized as models with combined (direct and indirect) control links. In the case of production resource reserves, the processes of changing control parameters and transforming technological links should be simultaneous. Invariants are obtained for the relationship between the volume of inputs and outputs of a multi-sector (diversified) economy. As a result, the formalized representation of the structural management model of a reproduction system is modified, and the linear reproduction model is replaced by a nonlinear one. The results of numerical calculations using this model and the real data of a diversified economy are presented. Based on the results, the obtained model is compared with the original restructuring model of a reproduction system.

Layered learning in a quadrotor drone: Simultaneous controlling and path planning using optimal fuzzy fractional order proportional integral derivative and proximal policy optimization

Unmanned aerial vehicles (UAVs), particularly quadrotors, have seen a surge in applications ranging from surveillance to delivery services. However, autonomous control remains a challenge due to the complexity of their dynamics and the need for real-time responsiveness. This paper addresses the significant problem of autonomous quadrotor control by introducing a novel learning method that integrates a deep neural network with advanced control techniques. Novelty of the work is distribution of different learning tasks in different layers of learning and combining the total learning system in a applicable UAV. The purpose is to enhance the quadrotor’s ability to perform complex maneuvers autonomously, which is crucial for expanding its application scope. The proposed method begins with the acquisition of direction control using a fractional order proportional–integral–derivative (FOPID) controller. The learning parameters are refined through a fuzzy method, ensuring adaptability and precision. For the optimization of the FOPID parameters, we apply two stochastic algorithms: Genetic Algorithm and Particle Swarm Optimization, comparing their efficacy. Our approach successfully teaches the quadrotor to generate and control a flight path autonomously. The second stage of learning involves proximal policy optimization, enabling the execution of intricate maneuvers. The experimental setup includes a quadrotor on a test stand with three degrees of freedom, where we validate the method through rigorous simulation and physical tests. The results demonstrate that our method not only teaches the quadrotor complex maneuvers but also ensures robust and precise execution, marking a significant advancement in UAV control systems. The implications of this research extend to improving UAV reliability for critical applications, potentially transforming the landscape of autonomous aerial operations.