Virtual Control System Research Articles

Robust proximity rendezvous and coordinated control of space robots

This paper investigates the robust proximity rendezvous and coordinated control of space robots. A robust rendezvous controller is meticulously devised to guarantee the H∞ performance of space rendezvous mission by addressing the Hamilton–Jacobi–Isaacs inequality. Additionally, a virtual control system is formulated to guarantee that the robust control inputs adhere to saturation constraints. Furthermore, this study introduces a novel fixed-time convergence constraint function aimed at constraining coordinated tracking missions for end-effector. The proposed coordinated controller ensures the achievement of end-effector pose tracking within a predetermined fixed time, while concurrently stabilizing the base attitude and bounding the transient responses of tracking errors within user-defined ranges. Notably, all these accomplishments are demonstrated under conditions of parameter uncertainty and input disturbance. Simulation results validate the effectiveness of the proposed control scheme.

GUI-Driven Real-Time PID Control Tool for Educational Virtual Systems

Abstract: This research presents a pioneering approach in virtual control systems, focusing on developing a highly intuitive Graphical User Interface (GUI) for real-time PID control of LED brightness using Arduino IDE. By embracing a robust pedagogical framework, the study meticulously outlines specific learning objectives that adhere to the SMART criteria, ensuring precise educational outcomes. The key to this research is the tailored design of the GUI, which considers diverse audience needs, prior knowledge, and learning styles. The interfaces are meticulously crafted for optimal user experience, ensuring seamless navigation and engagement. Interactive elements, encompassing simulations, virtual experiments, problem-solving scenarios, and quizzes, foster active participation and hands-on learning. Multimedia elements, such as text, images, videos, animations, and audio, are thoughtfully integrated to cater to varied learning preferences. This paper underscores the critical role of collaborative learning facilitated through discussion forums, chat functionalities, and collaborative virtual environments. The study emphasizes continuous improvement through regular assessments and detailed user feedback analysis. Notably, the research highlights the significant educational impact of the designed GUI. By offering a practical platform where students can dynamically adjust PID parameters and observe immediate effects on LED brightness, the GUI enhances the learning experience in classroom settings. This approach equips students with a tangible understanding of complex PID principles, preparing them for real-world applications. In summary, this research showcases the creation of engaging, practical virtual control system tools, fostering profound and meaningful learning experiences for users within educational contexts. Keywords : control systems, pedagogy, facilitation

Distributed virtual formation control for railway trains with nonlinear dynamics and collision avoidance constraints

To improve the model accuracy and control efficiency for the movements of a virtual formation, this paper investigates distributed optimal control for the virtual formation control system in railways. Adopting the relative distance braking mode, a coupled optimal control problem with nonlinear train dynamics and constraints regarding collision avoidance and jerk is formulated for the virtual formation. To handle the non-convex constrained problem efficiently, a distributed augmented Lagrangian based alternating direction inexact newton (ALADIN) method under the model predictive control (MPC) framework is developed. For the execution of the distributed computational process, the copied variables are introduced to reformulate the original coupled problem in an objective separable form. By exploiting the problem separability, the ALADIN method decomposes the reformulation into a coordinated quadratic programming problem of small-scale and several local nonlinear programming problems that can be calculated in parallel, thereby facilitating real-time control and relieving communication burden. Numerical experiments on a metro line are carried out to verify the effectiveness of the proposed model and method. Experimental results demonstrate that high-performance tracking control for virtually coupled train units can be achieved in real time.

An asymmetrically variable wingtip anhedral angles morphing aircraft based on incremental sliding mode control: Improving lateral maneuver capability

This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft, inspired by biomimetic mechanisms, to enhance lateral maneuver capability. Firstly, we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process, and convert it into a Multiple Input Multiple Output (MIMO) virtual control system by importing virtual inputs. Secondly, a classical dynamics inversion controller is designed for the outer-loop system. A new Global Fast Terminal Incremental Sliding Mode Controller (NDO-GFTISMC) is proposed for the inner-loop system, in which an adaptive law is implemented to weaken control surface chattering, and a Nonlinear Disturbance Observer (NDO) is integrated to compensate for unknown disturbances. The whole control system is proven semi-globally uniformly ultimately bounded based on the multi-Lyapunov function method. Furthermore, we consider tracking errors and self-characteristics of actuators, a quadratic programming-based dynamic control allocation law is designed, which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder. Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law. Finally, comparative experimental results validate the effectiveness of the designed control system and control allocation law. The NDO-GFTISMC features faster convergence, stronger robustness, and 81.25% and 75.0% reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO (NDO-INDI) and Incremental Sliding Mode Controller based on NDO (NDO-ISMC), respectively. The design of the morphing aircraft significantly enhances lateral maneuver capability, maintaining a substantial control margin during lateral maneuvering, reducing the burden of the rudder surface, and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.

A Virtual Laboratory for Control System Engineering

The use of virtual laboratory is becoming increasingly common. These virtual laboratories are beneficial in such situations when practical laboratories are inaccessible or when there is lack of expensive hardware equipment. This paper presents a virtual Control System Laboratory that can be used in Electrical Engineering education for undergraduate students and researchers. A set of experiments have been introduced that have been developed using free-open-source-software (Hyper Text Markup Language 5 (HTML5), Cascading Style Sheets 3 (CSS3), and JavaScript) and uploaded into web for remote access. The case studies of these experiments are presented. This laboratory can be accessed in (http://vlabs.iitkgp.ac.in/psac/newlabs2024/ctrl/).

Intelligent ADRC‐based inertia control for offshore wind farm

AbstractThis paper proposes a virtual inertia control strategy for wind farms based on auto disturbance rejection controller with artificial bee colony (ABC) algorithm. First, based on the system frequency dynamic response equation, an active disturbance rejection controller is designed according to the non‐linear feedback control law and the extended state observer to improve the anti‐interference capability of the virtual inertia control system. Second, in order to solve the problem of difficulty in tuning the parameters of the active disturbance rejection control (ADRC), an ABC algorithm based on nectar collection behaviour was proposed to iteratively optimize the parameters of ADRC. Finally, the proposed control method is effectively verified based on Matlab/Simulink. The simulation results show that compared with traditional algorithms, the proposed ABC‐ADRC can effectively control the rotor speed to adjust the frequency of the power grid system, achieve power sharing and adaptive noise elimination, reduce the complexity of parameter settings, not only improve anti‐interference ability, but also enhance the robustness of the system.

High-Speed Virtual Flight Testing Platform for Performance Evaluation of Pitch Maneuvers

To research serious nonlinear coupling problems among aerodynamics, flight mechanics, and flight control during high maneuvers, a virtual flight testing platform has been developed for a large-scale, high-speed wind tunnel, based on the real physical environment, and it can significantly mitigate risks and reduce the costs of subsequent flight tests. The platform of virtual flight testing is composed of three-degrees-of-freedom model support, measuring devices for aerodynamic and motion parameters, a virtual flight control system, and a test model. It provides the ability to realistically simulate real maneuvers, investigate the coupling characteristics of unsteady aerodynamics and nonlinear flight dynamics, evaluate flight performance, and verify the flight control law. The typical test results of a pitch maneuver with open-loop and closed-loop control are presented, including a one-degree-of-freedom pitch motion and a two-degrees-of-freedom pitch and roll motion. The serious pitch and roll-coupled motion during a pitch maneuver at a high angle of attack is revealed, and the flight control law for decoupled control is successfully verified. The comparison of the test results and the flight data of a real pitch maneuver proves the reliability and capability of virtual flight testing.

Research on Optimal Control Method of Load Side Virtual Power Plant Based on Cloud Edge Collaboration

With the advancement of new power system construction, the large-scale layout of new energy power generation has gradually become a new format, and the overall new energy presents the characteristics of “rapid development of installed capacity, an increased proportion of low-voltage grid connection, and ultra-high penetration rate in some areas”. Under the new situation of power generation, power transmission, power distribution, and power consumption, to solve the problem of efficient and friendly interaction of “source, network, load and storage” in the power system and the consumption of renewable energy, “virtual power plant” came into being. However, there are limitations in aggregating resources in virtual power plants. To improve the effective participation of users, such as medium and low loads in power grid interaction, this article designs and implements a load-side virtual power plant control software system based on cloud-side collaboration. We use the virtual power plant operation control system to realize resource bidding and flexible participation in the response. The system can flexibly aggregate multiple types of resources through deployment verification, effectively realize precise tracking of instructions, and guarantee effective grid interaction.

Improved yellowness index (YI) control in ABS compounding process through virtual control using an RNN-based neural network soft-sensor model

Soft sensors have gained widespread acceptance due to their ability to handle highly complex systems. However, their application in process control remains limited, primarily due to the lack of interpretability associated with most soft sensors, which are often black-box models without a clear physical basis. In an effort to address this issue, this study proposes a novel approach to soft-sensor construction by integrating the eXtreme Gradient Boosting (XGBoost) technique with the Gated Recurrent Unit (GRU) in chemical engineering. The approach is applied to a real-world industrial ABS (Acrylonitrile-Butadiene-Styrene) resin compounding process. After the predictive performance and physical correctness of the soft sensor are validated, a virtual fuzzy control system is constructed using data from the soft-sensor prediction. The results show that the proposed method with superior predictive performance and physical correctness, and its use in the control system improves the stability of the product quality and decreases grade transition times.

Modified Differential Evolution Algorithm for Governing Virtual Inertia of an Isolated Microgrid Integrating Electric Vehicles

In modern power systems, there is a greater penetration of renewable sources, resulting in the expansion of microgrid. By implementing RES instead of conventional synchronous machines, the system’s overall inertia is significantly reduced. Modern and future power systems must reduce system inertia and keep the frequency at its nominal value since frequency oscillation impacts on the functionality, stability, and resilience of the system. Therefore, creating a stable, scalable, and reliable virtual inertia control system is crucial to effectively minimize the deviations during significant contingencies. Consequently, taking into account the probable issues, the foremost objective of this research work is to improve the dynamic security of an island microgrid through the implementation of a frequency control concept based on virtual inertia control. In the research study, the proposed microgrid system comprises of photovoltaics, wind-generating units, thermal power units, storage units, electric vehicles (EVs), and loads. A cascaded PIDFN controller is optimally designed using a novel metaheuristic modified differential evolution (MDE) algorithm that regulates the frequency based on virtual inertia control. In the MATLAB®/SIMULINK environment, various operating situations such as load variations, RES, and EVs disconnection are investigated, and the performance of the VIC-based MDE controller was compared to that of other controllers based on evolutionary optimization algorithms such as DE and TLBO. The results validate that the recommended virtual inertia control strategy enhances the reliability of the system.

Adaptive Virtual Inertia Control for Stable Microgrid Operation Including Ancillary Services Support

This article proposes an adaptive virtual inertia control system for stable operation of microgrids: it theoretically improves recent related results in the literature. The overall control system is conceived to provide ancillary services support (namely, enhanced frequency regulation with inertial response and voltage support) to an ac/dc microgrid that consists of a dc bus providing power to the ac one, being, in turn, composed of a diesel generator and loads. The ac voltages and currents are controlled via a nonlinear algorithm based on control-induced time-scale separation and singular perturbation analysis, whose use greatly simplifies the control design and the choice of the tuning gains, when compared with the classical linear controls. With the aim of reducing oscillations from the grid by assuring suitable short circuit ratio (SCR) and proper <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$X/R$</tex-math> </inline-formula> characteristics, a virtual impedance is also implemented, along with frequency and voltage droops: they constitute high-level controllers that give references to the virtual inertia scheme and compose a comprehensive control. Detailed simulations illustrate, in different relevant settings, the performance of the proposed scheme.

Virtual Inertia Control of Isolated Microgrids Using an NN-Based VFOPID Controller

Reduction in system inertia and maintaining the frequency at the nominal value is a staple of today's and future power systems since their operation, stability, and resiliency are degraded by frequency oscillation and cascading failures. Consequently, designing a stable, scalable, and robust virtual inertia control system is highly relevant to skillfully diminishing the deviations during major contingencies. Therefore, considering the potential problems in predesigned nonflexible control systems with offline tuning techniques, we propose a variable fractional-order PID controller for virtual inertia control applications, which is tuned online using a modified neural network-based algorithm. The new proposed tuner algorithm is trained using a deep reinforcement learning strategy with a simplified deep deterministic policy gradient, which considers microgrid uncertainties. Compared with existing methods, all the tuning knobs of the discrete type and fully tunable variable FOPID controller (for both gain and order) can be captured based on the proposed hybrid algorithm, which inherits features from both classical and advanced techniques. To demonstrate the effectiveness of the training of the proposed controller, a comparative analysis with the standard FOPID and PID controllers is given under three different scenarios with a smooth (dis)connection of renewable energy sources and loads.

Development of a Virtual Environment-Based Electrooculogram Control System for Safe Electric Wheelchair Mobility for Individuals with Severe Physical Disabilities

Conventional wheelchairs are predominantly manual or joystick-operated electric wheelchairs. However, operating these wheelchairs can be difficult or impossible for individuals with severe physical disabilities. Due to losing control of their physical limbs, they depend on an attendant for assistance. As a remedy, bio-signals may be used as a control mechanism since they are readily available and can be acquired from any body part. This research proposes to use EOG signals to vail a control mechanism and test it in a virtual and actual electric wheelchair. The main contribution of the study is an investigation of the use of EOG to control an electric wheelchair in a virtual environment to determine safe control parameters for wheelchair use in complex environments. A customized data acquisition circuit was developed to acquire single-channel EOG signals using wet electrodes. The acquired signal was filtered and processed using feature extraction and classification techniques in MATLAB software. Two customized control environments were developed in Unity 3D, one with equally partitioned sections and the other with sections decreasing in size as the robot wheelchair approaches the target. Twenty-two test subjects (mean age 24.5, std 1.5) participated in the study, controlling the robot wheelchair in real-time with non or least instances of collision and oversteering. The system achieved an accuracy of 96.5% with a response time of 0.7s, translating to an ITR of 70.6 bits/min. Overall, the participants managed to navigate the virtual environment with a completion time of 101.94s ± 19.71 and 109.07s ± 13.25 for the male and female participants, respectively. In the scene with decreasing section sizes, 72% and 54% instances of collision and oversteering were reported, respectively, highlighting the need to consider the complexity of the control environment and the sufficiency of the participants' control skills to ensure safety in operations. The results confirm the usefulness of EOG as a control interface, with little or no need for recalibration. It provides a promising avenue for individuals with severe physical disabilities to operate wheelchairs independently in complex environments, enhancing their quality of life.

Development of Virtual Production Camera Control System based on Arduino

Development of Virtual Production Camera Control System based on Arduino

Cooperative Optimal Control of the Following Operation of High-Speed Trains

The following operation of multiple high-speed trains (HSTs) with high speed and great density based on the moving block and virtual coupling control system can significantly improve the performance of railway systems concerning operation safety and line capacity. However, it is difficult for HST’s conventional control approach to satisfy the service demand, including safety, energy-saving, and ride comfort, due to the significantly increasing longitudinal interaction between adjacent trains in the following operating conditions. In this paper, the characteristic model of multiple HSTs’ following operation was formulated to effectively and accurately describe train control constraints derived from the coupling relationship among adjacent trains’ operation states. Then, the cooperative model predictive control (CMPC) strategy with a multiobjective rolling optimization scheme is developed. The overall line capacity, energy consumption, and ride comfort of train platoons in the railway section are defined as optimization indexes. Furthermore, some sufficient conditions for the consensus stability of the CMPC of HST are given, based on the proposed multiple HSTs following characteristic model and cooperative optimal control strategy. Simulation experiments are carried out by using HST’s operation data collected from real-world runs. Results demonstrate the effectiveness and feasibility of the proposed modeling and control method.

Fuzzy control based virtual synchronous generator for self-adaptative control in hybrid microgrid

Maintaining the stability of low-inertia microgrid becomes a key challenge in the presence of high penetration of renewable energy sources. However, in such systems, the virtual inertia values are often fixed constants, and the choice of their values will significantly affect the frequency and voltage stability of the microgrid. Higher frequency and voltage oscillations may occur due to improper selection of fixed virtual inertia values. Therefore, virtual inertia-based control has attracted a lot of attention. In this paper, an adaptive virtual inertia control system using a fuzzy system is proposed by setting fuzzy logic rules and affiliation functions to provide adaptive inertia control for the system to ensure the frequency and voltage stability. In the proposed adaptive control strategy, the virtual inertia values are automatically adjusted according to the signal deviation and rate of change of the actual system, avoiding the selection of inappropriate inertia values and providing fast inertial response. Simulation and experimental results show that the proposed adaptive control algorithm, by combining the advantages of large inertia and small inertia, enables effective improvement of the dynamic response of the system voltage and frequency in both rectifier and inverter modes. The effectiveness of the proposed control strategy is verified.

(Retracted) Virtual reality painting dexterous hand gesture control algorithm and simulation

With the expansion of the application field of robots and the complexity of the work environment and tasks, ordinary robots and various simple end-holding devices that cooperate with them are far from being able to meet the requirements of various dexterity and fine operation tasks. Immersion means that the process of painting is virtual immersion; the expression requirement for painting must be immersive. This research mainly discusses the posture control algorithm and simulation of dexterous hand in virtual reality painting. The research combines the related theoretical basis of the dexterous hand posture control algorithm with VR painting, and explores the immersive experience characteristics brought by VR immersive painting. This research will focus on the three aspects of the action state pattern recognition based on the surface electromyogram (EMG) signal, the algorithm of the dexterous hand virtual control system, and the simulation of the bionic dexterous hand EMG control system. The collection and processing of the surface EMG signal of the forearm were completed. The experiment verified the effectiveness and accuracy of the surface EMG signal feature extraction, feature dimensionality reduction, and classification algorithm, and realized the pattern recognition of eight action states. Using musculoskeletal simulation software and a finite state machine control model, an intelligent bionic dexterous hand virtual control system was established, which realized offline gesture recognition and performance evaluation of the virtual control system. In the environment of large time delay, many painting experiments were carried out, the tasks were successfully completed, and the average completion time was about 4 min. At this stage, most of the finger structures of dexterous hands are in series, and the accumulated error is large, which greatly affects the accuracy of dexterous hands. VR painting is an innovative form of painting with potential space in the future. The results of this research and exploration can reflect the potential possibilities of future painting creation forms.

A Train Protection Logic Based on Topological Manifolds for Virtual Coupling

Virtual coupling is a promising innovation aimed at increasing railway capacity. Compared to current railway signaling systems, it allows two or more trains to run with reduced headway between them. However, such reduced headways are a challenge to safety. In this work we consider this challenge by formally describing and verifying an approach to virtual coupling. We propose a general modeling method based on topological manifolds to describe the protection logic for virtual coupling train control systems. We also describe the basic train control elements in topological terms and analyze the line condition of our virtual coupling logic. We establish that the line condition safety requirements and its representation as a manifold are equivalent and further provide a formal definition of the concept of a movement authority with manifold notations. This allows us to consider the dynamic behavior of trains and a series of theorems that establish the correctness of our protection logic for virtual coupling. Finally, we apply the presented methods to a case study. The results show that the proposed method provides a suitable way to realize a virtual coupling logic safely.

Wind-Storage Combined Virtual Inertial Control Based on Quantization and Regulation Decoupling of Active Power Increments

With the increasing proportion of wind turbines in power grids, they are required to have capabilities of active and efficient virtual inertial response to maintain grid frequency stability. However, the virtual inertial control methods currently used in doubly-fed induction generator (DFIG) units suffer from a secondary frequency drop (SFD) problem. Although the SFD can be inhibited by reducing the active power support strength of the DFIG units during inertia response, it will undoubtedly weaken the virtual inertia of the units. Therefore, how to eliminate the SFD while increasing the virtual inertia of the units is a worthy issue for studying. To solve this issue, a wind-storage combined virtual inertial control system based on quantization and regulation decoupling of active power increments is proposed in this paper. First, by setting the parameters of a proportional–differential (P-D) algorithm, the total active power increments required for virtual inertial response are quantified at the DFIG level. Secondly, a curve-shifting method based on the rate of change of frequency is adopted to adjust the active power output of the DFIG units. Finally, a battery energy storage system (BESS) is used to compensate for the power shortages of the units according to the quantized value of the active power increments. Simulations show that the control method can not only eliminate SFD but also effectively increase the system’s virtual inertia.

Establishment and Validation of Continuously Operating Reference Stations Geosystems Network on Static and Real-Time Kinematic in Benin City, Nigeria

An infrastructure highly treasured by Geomatics Engineers is the continuously operating reference stations (CORS). CORS technology is a complete paradigm shift from the previously known ground control system to a virtual control system. In this paper, we present the steps taken to install CORS Geosystems in Benin City and further test its efficacy by observing fifteen existing control points located far and near using two Tersus GNSS receivers (A&amp;B) concurrently. We perform statistical adjustment using Trimble Business Center software. Successful adjustment took two (2) iterations with Chi square test at (95%) precision confidence level and degree of freedom being nine (9) showed that the result of the adjustment was reliable. Means of 0.007m, 0.003m 0.000m for Easting, Northings and Heights were obtained while the standard errors (σ) in E, N and H are 0.003m, 0.007m and 0.000m respectively. The achieved RMS errors obtained from the attempted validation confirmed further that the newly installed CORS is capable of providing reliable 3D geo-spatial data for prospective authorized users to proffer solutions to engineering, scientific, environmental and research driven challenges.