Dynamic Control Research Articles

Fully Distributed Dynamic Event-triggered Formation-Containment Control for Networked Unmanned Surface Vehicles with Intermittent Wireless Network Communications

Fully Distributed Dynamic Event-triggered Formation-Containment Control for Networked Unmanned Surface Vehicles with Intermittent Wireless Network Communications

Optimal replicator dynamic controller for semi active control of long span cable stayed bridge with considering special variability of seismic excitations

Cable-stayed bridges are lifeline infrastructures. However, due to their design and structural characteristics, they are sensitive to the vibrations. Thus, vibration control in these structures is essential. Semi-active control systems have gained significant attention due to their high performance and adaptability. However, the implementation of these systems has always faced serious challenges particularly when it comes to developing appropriate control algorithms because semi active devices have complex and non-linear characteristics. Inspired by evolutionary game theory, the author utilizes the replicator dynamic controller concept to optimize the performance of MR dampers to improve the vibration reduction of cable-stayed bridges. Two key parameters in the proposed control methodologies using replicator dynamics are the total population (total available resources or the sum of actuator forces) and the growth rate. Instead of using the sensitivity analysis that has been done in previous studies for vibration reduction of highway bridges using a replicator controller, the author used an evolutionary algorithm named the nondominated sorting genetic algorithm (NSGA-II) to create an optimal replicator dynamic controller for more effective vibration reduction. The proposed methodology is evaluated through its numerical application to a second-generation benchmark example based on the Bill Emerson Memorial Bridge, which considers a more realistic behavior of the cable-stayed bridge by accounting for multiple support excitations. The study indicates that the optimal replicator dynamic controller improves the vibration reduction performance of MR dampers. Specifically, deck displacement is reduced by 46 % compared to passive control system and shear forces at the tower base are reduced by 33 % compared to active control systems for the El Centro earthquake. The results indicate that the proposed Replicator Dynamic Controller optimized through NSGA-II provides a robust and effective solution for improving seismic resilience of cable-stayed bridges.

Study on the Influence of Lightweight Mechanical Structure on UAV Dynamic Response Characteristics and Control Strategy Optimization

Study on the Influence of Lightweight Mechanical Structure on UAV Dynamic Response Characteristics and Control Strategy Optimization

Research on Dynamic Control of Robot Joint Based on Neural Network

Research on Dynamic Control of Robot Joint Based on Neural Network

Mott resistive switching initiated by topological defects

Avalanche resistive switching is the fundamental process that triggers the sudden change of the electrical properties in solid-state devices under the action of intense electric fields. Despite its relevance for information processing, ultrafast electronics, neuromorphic devices, resistive memories and brain-inspired computation, the nature of the local stochastic fluctuations that drive the formation of metallic regions within the insulating state has remained hidden. Here, using operando X-ray nano-imaging, we have captured the origin of resistive switching in a V2O3-based device under working conditions. V2O3 is a paradigmatic Mott material, which undergoes a first-order metal-to-insulator phase transition together with a lattice transformation that breaks the threefold rotational symmetry of the rhombohedral metallic phase. We reveal a new class of volatile electronic switching triggered by nanoscale topological defects appearing in the shear-strain based order parameter that describes the insulating phase. Our results pave the way to the use of strain engineering approaches to manipulate such topological defects and achieve the full dynamical control of the electronic Mott switching. Topology-driven, reversible electronic transitions are relevant across a broad range of quantum materials, comprising transition metal oxides, chalcogenides and kagome metals.

Dynamic output feedback model predictive control for polytopic uncertain systems under decode and forward cooperative relay protocol

This paper addresses the robust model predictive control (RMPC) problem for a class of polytopic uncertain systems under the decode and forward cooperative relay protocol (DFCP). In order to combat signal fading from sensors to controllers and improve communication reliability, spatial diversity is achieved through cooperative terminal relay signals. At each transmission instant, the terminal only selects a better signal for transmission and a switched system is constructed. The aim of this paper is to design a set of desired dynamic output feedback controllers in the framework of RMPC such that the switched system with the underlying DFCP is exponentially stable. By taking the influence of the randomness of DFCP derived from a three nodes model composed of DF relay, a new objective function based on the mathematical expectation of the traditional quadratic function of MPC is established. Then, the orthogonal complement technique is applied to handle the inherent couplings of variables to formulate a solvable optimisation problem. Moreover, the sufficient conditions are provided to guarantee the recursive feasibility of the MPC strategy and the stability of the established closed-loop system in terms of the average dwell time (ADT) method. Finally, three experiments are given to illustrate the effectiveness of the proposed method.

Directing Nanoparticle Organization in Response to Diverse Chemical Inputs.

Signaling cascades are crucial for transducing stimuli in biological systems, enabling multiple stimuli to regulate a downstream target with precisely controlled timing and amplifying signals through a series of intermediary reactions. Developing a robust signaling system with such capabilities would be pivotal for programming complex behaviors in synthetic DNA-based molecular devices. However, although "software" such as nucleic acid circuits could potentially be harnessed to relay signals to DNA-based nanostructure hardware, such explorations have been limited. Here, we develop a platform for transducing a variety of stimuli via messenger-mediated reactions to regulate the release and reloading of gold nanoparticles (AuNPs) in a 3D DNA framework. In the first step, an in vitro transcription circuit is engineered to sense and amplify chemical stimuli, including arbitrary DNA sequences and proteins, producing RNA. In the second step, the RNA releases the DNA-coated AuNPs from the DNA framework via a strand displacement reaction. AuNP reloading is controlled by a separate step driven by degradation of the RNA. Our platform holds promise for applications requiring dynamic multiagent control over DNA-based devices, offering a versatile tool for advanced molecular device engineering.

Attitude Practical Stabilization of Underactuated Autonomous Underwater Vehicles in Vertical Plane

Due to the singularity of Euler angles and the ambiguity of quaternions, to further expand the attitude reachable range of underactuated AUVs in the vertical plane, SO(3) is used to represent the attitude change of underactuated AUVs. The transverse function of the attitude on SO(3) is designed, and the exponential mapping method is used to construct the attitude kinematic controller of underactuated AUVs. Considering the changes in the model and ocean current during motion, interval type II fuzzy systems (IT2-FLSs) are used to estimate these changes. The backstepping method and the small gain theorem are adopted to design dynamic controllers to ensure the stability and robustness of the system. A novel saturation auxiliary system is designed to compensate for the influence of actuator saturation characteristics. Finally, the simulation results verify the effectiveness of the proposed controller and ensure the practical stabilization of the underactuated AUV attitude.

Dynamic Acoustic Holography: One-Shot High-Precision and High-Information Methodology

Acoustic holography technology is widely used in the field of ultrasound due to its capability to achieve complex acoustic fields. The traditional acoustic holography method based on single-phase holograms is limited due to its inability to complete acoustic field control with high dynamics and accuracy. Here, we propose a method for constructing an acoustic holographic model, introducing an ultrasonic array to provide dynamic amplitude control degrees of freedom, and combining the dynamically controllable ultrasonic array and high-precision acoustic hologram to achieve the highest acoustic field accuracy and dynamic range. This simulation method has been proven to be applicable to both simple linear patterns and complex surface patterns. Moreover, it is possible to reconstruct the degree of freedom of the target plane amplitude effectively and achieve a breakthrough in high information content. This high-efficiency acoustic field control capability has potential applications in ultrasound imaging, acoustic tweezers, and neuromodulation.

Dynamic load frequency control in Power systems using a hybrid simulated annealing based Quadratic Interpolation Optimizer

Ensuring the stability and reliability of modern power systems is increasingly challenging due to the growing integration of renewable energy sources and the dynamic nature of load demands. Traditional proportional-integral-derivative (PID) controllers, while widely used, often fall short in effectively managing these complexities. This paper introduces a novel approach to load frequency control (LFC) by proposing a filtered PID (PID-F) controller optimized through a hybrid simulated annealing based quadratic interpolation optimizer (hSA-QIO). The hSA-QIO uniquely combines the local search capabilities of simulated annealing (SA) with the global optimization strengths of the quadratic interpolation optimizer (QIO), providing a robust and efficient solution for LFC challenges. The key contributions of this study include the development and application of the hSA-QIO, which significantly enhances the performance of the PID-F controller. The proposed hSA-QIO was evaluated on unimodal, multimodal, and low-dimensional benchmark functions, to demonstrate its robustness and effectiveness across diverse optimization scenarios. The results showed significant improvements in solution quality compared to the original QIO, with lower objective function values and faster convergence. Applied to a two-area interconnected power system with hybrid photovoltaic-thermal power generation, the hSA-QIO-tuned controller achieved a substantial reduction in the integral of time-weighted absolute error by 23.4%, from 1.1396 to 0.87412. Additionally, the controller reduced the settling time for frequency deviations in Area 1 by 9.9%, from 1.0574 s to 0.96191 s, and decreased the overshoot by 8.8%. In Area 2, the settling time was improved to 0.89209 s, with a reduction in overshoot by 4.8%. The controller also demonstrated superior tie-line power regulation, achieving immediate response with minimal overshoot.

A dynamical optimal control theory and cost-effectiveness analyses of the HBV and HIV/AIDS co-infection model.

Studies have shown that the co-infection of Human Immunodeficiency Virus (HIV) and Hepatitis B Virus (HBV) poses a major threat to the public health due to their combined negative impacts on health and increased risk of complications. Even though, some scholars formulated and analyzed the HBV and HIV co-infection model they did not consider the compartment that contains protected individuals against both HBV and HIV infections. They incorporated the optimal control theory and cost-effectiveness analysis simultaneously. With this in mind, we are motivated to formulate and analyze the HBV and HIV co-infection model, considering the protected group and incorporating optimal control theory and cost-effectiveness. In this study, we have theoretically computed all of the models disease-free equilibrium points, all the models effective reproduction numbers and unique endemic equilibrium points. The two sub-models disease-free equilibrium points are locally as well as globally asymptotically stable whenever their associated effective reproduction numbers are less than one. We reformulated the optimal control problem by incorporating five time-dependent control measures and conducted its theoretical analysis by utilizing the Pontryagin's maximum principle. Using the fourth order Runge-Kutta numerical method and MATLAB ODE45, we performed the numerical simulations with various combinations of control efforts to verify the theoretical results and investigate the impacts of the suggested protection and treatment control strategies for both the HBV and HIV diseases. Also, we carried out a cost-effectiveness analysis of the proposed control strategies. Eventually, we compared our model results with other researcher similar model results whenever cost-effectiveness analysis is not carried out the findings of this particular study suggest that implementing each of the proposed control strategies simultaneously has a high potential to reduce and control the spread of HBV and HIV co-infections in the community. According to the cost-effectiveness analysis, implementing the HBV treatment and the HIV and HBV co-infection treatment measures has a high potential effect on reducing and controlling the HBV and HIV co-infection transmission problem in the community.

Electro-optically Modulated Nonlinear Metasurfaces.

Electrically reconfigurable nonlinear metasurfaces provide dynamic control over nonlinear phenomena such as second-harmonic generation (SHG), unlocking novel applications in signal processing, light switching, and sensing. Previous methods, like electric-field-induced SHG in plasmonic metasurfaces and Stark-tuned nonlinearities in quantum well metasurfaces, face limitations due to weak SHG responses from metals and mid-infrared constraints of quantum wells, respectively. Addressing the need for efficient SHG control in the visible and near-infrared ranges, we present a novel approach using the electro-optic (EO) effect to modulate SHG. By leveraging the exceptional EO and SHG properties of lithium niobate (LN), we integrate the EO effect with SHG within a metasurface framework for the first time. Our LN metasurface achieves an 11.3% modulation depth in SHG amplitude under a ±50 V alternating voltage. These results open new avenues for reconfigurable photonic applications. including tunable nonlinear light sources, quantum optics, and nonlinear information processing.

Physics-informed neutral network with physically consistent and residual learning for excavator precision operation control

The data-driven methodologies can establish accurate Inverse Dynamics Model (IDM) of the excavator thus improving control precisions. However, the inherent black-box nature of these models often results in overfitting to the dataset, leading to predictions that deviate from the constraints of physical system. Consequently, this can lead to controller failures, introducing unpredictable behavior that threatens operation precision. In addition, the uncertainty of the external disturbance poses great challenge to the precision of controller. This study presents a physics-informed neural network to build accurate IDM with physical consistency. The Rigid Body Dynamics (RBD) of the excavator are coupled within a Deep Lagrangian Network (DeLaN), while a Convolutional Neural Network (CNN) and a Long Short-Term Memory Network (LSTM) are employed to assimilate the residual nonlinear characteristics, such as hydraulic flexibilities and stick–slip friction. To the uncertainty of the external disturbance, the Prescribed Performance Inverse Dynamics Controller combination with the DeLaN-CNN-LSTM model (PPIDC-DCL) is constructed for precise control by constraining the control error within a finite region. The experimental results demonstrate that the model captures the underlying structure of the dynamic and builds the IDM with high accuracy and robustness. Moreover, the PPIDC-DCL controller effectively constrains the control error and realizes precision control. The proposed method has potential applications and provides novel insights for achieving precise operation control of excavators.

Systematic Evaluation and Application of IDR Domain-Mediated Transcriptional Activation of NUP98 in Saccharomyces cerevisiae.

Implementing dynamic control over gene transcription to decouple cell growth is essential for regulating protein expression in microbial cells. However, the availability of efficient regulatory elements in Saccharomyces cerevisiae remains limited. In this study, we present a novel β-estradiol-inducible gene expression system, termed DEN. This system combines a DNA-binding domain with an estradiol-binding domain and an intrinsically disordered region (IDR) from NUP98. Comparative analysis shows that the DEN system outperforms IDRs from other proteins, achieving an approximately 60-fold increase in EGFP expression upon β-estradiol induction. Moreover, our system is tightly controlled; nontoxic gene expression makes it a powerful tool for rapid and precise modulation of target gene expression. This system holds great potential for unlocking new functionalities from existing proteins in future research.

Examining the effects of non-immersive virtual reality game-based training on knee hyperextension control and balance in chronic stroke patients: a single-blind randomized controlled study.

Post-stroke hemiparesis can lead to decreased mobility, gait disturbances, impaired balance, postural instability, limitations in activities of daily living (ADL), and long-term disability. The aim of this study was to examine the effect of non-immersive virtual reality game-based training (nIVRGT) in addition to conventional rehabilitation in stroke patients on dynamic balance, knee hyperextension control, and ADL. Twenty-five chronic stroke patients aged between 51 and 70 were included in the study. Stroke patients were randomized to a control group (n = 12) and a study group (n = 13). Individuals in control group participated conventional physiotherapy and rehabilitation program for 60min, 3 days a week for 6 weeks. individuals in the study group received 40min of conventional physiotherapy and rehabilitation program plus 20min nIVRGT. Functional Reach Test, Timed Up and Go Test, Computerized Gait Evaluation System and Barthel Index were used in the evaluation. The study group improved significantly in dynamic balance, knee control, and ADL (p < 0.05). In the control group, significant improvements were observed in dynamic balance and knee control (p < 0.05), except ADL (p > 0.05). The study group improved in dynamic balance compared with the control group (p < 0.05). Knee control and ADL improved similarly in both groups (p > 0.05). Our results showed that conventional and additional nIVRGT rehabilitation improved dynamic balance and knee hyperextension control in chronic stroke. However, it was observed that the non-immersive virtual reality (nIVR) approach was more effective in improving dynamic balance in stroke patients than conventional rehabilitation alone. NCT05907473.

Control of coherent phonon dynamics in CoFeB/heavy metal heterojunction structures for future hybrid phononic and spintronic devices

Abstract The heterojunction structure of CoFeB/heavy metal has shown significant potential for spintronics, where both electrons and magnons potentially can serve as information carriers. However, another promising information carrier, coherent phonons, has not been fully explored for hybrid phononic and spintronic devices. In this study, we used time-resolved pump-probe spectroscopy to investigate the dynamic behavior of coherent phonons. We observed variations in reflectivity spectra, corresponding to changes in phonon frequency and relaxation times, with different thicknesses of the heavy metal and CoFeB layers. The experimental results demonstrated a decrease in coherent phonon oscillation frequency as the thickness of the CoFeB and heavy metal layers increased. These findings were further supported by first-principles calculations, which showed that the frequency of the optical modes is suppressed due to interface relaxation between the magnetic and heavy metal layers.&amp;#xD;

Movable surface acoustic wave tweezers: a versatile toolbox for micromanipulation

Surface acoustic wave (SAW) tweezers are a promising multifunctional micromanipulation method that controls microscale targets via patterned acoustic fields. Owing to their device structure and bonding process, most SAW tweezers have limitations in terms of controlling the position and motion of the acoustic traps, as they generate an acoustic field with a fixed region and adjust the manipulation effects via signal modulation. To address this challenge, we propose movable SAW tweezers with a multilayer structure, achieving dynamic control of their wave field and acoustic trap positions; we demonstrate their precise manipulation functions, such as translation, in-plane rotation, out-of-plane rotation, and cluster formation, on a wide spectrum of samples, including particles, bubbles, droplets, cells, and microorganisms. Our method not only improves the degree of freedom and working range of SAW tweezers but also allows for precise and selective manipulation of microtargets via microtools and localized wavefields. Owing to their flexibility, versatility, and biocompatibility, the movable SAW tweezers can be a practical platform for achieving arbitrary manipulation of microscale targets and have the potential to play significant roles in biomedical microrobotics.

Long-term price guidance mechanism for integrated energy systems based on gated recurrent unit - vision transformer prediction and fractional-order stochastic dynamic calculus control

Against the backdrop of global climate change, renewable energy (RE) performs significant effects in reducing carbon emissions. Nevertheless, volatile RE sources disrupt the energy supply-demand balance (ESDB) in the energy market. Flexible energy (FE) can effectively mitigate the problem with high flexibility and controllability. FE sources are widely distributed in integrated energy systems (IESs). However, existing methods guide scattered FE in IESs with insufficient accuracy. To accurately guide FE, this study proposes an improved long-term price guidance mechanism (ILPGM) based on gated recurrent unit (GRU)- vision Transformer (ViT) prediction and fractional-order stochastic dynamic calculus (FSDC) control. The ILPGM combines GRU and ViT for baseline load forecasting and applies the FSDC method. The ILPGM can optimize the energy consumption of IESs and promote the ESDB while decreasing energy costs. The ILPGM is applied to the IES at Arizona State University-Tempe. The experimental results indicate that: the average coefficient of determination of electrical and heat energy under ILPGM is 97.69 %, realizing flexible regulation of energy consumption; the ILPGM can save 26.36 % actual cost and 94.62 % potential cost savings for the IES; compared to the previous long-term price guidance mechanism, the ILPGM provides an additional 5.87 % total cost savings and 28.65 % potential savings.

Dynamics and event-triggered control of rumor propagation model with saturated incidence and time delay on heterogeneous networks

Considering the impact of user’s cognitive ability in rumor propagation, this paper proposes a new susceptible infection recovery (2SIR) rumor propagation model with saturation incidence and time delay on heterogeneous networks. First, the existence of the equilibria is discussed by using mean field theory and basic reproduction number. Second, the dynamic behaviors of the rumor-free and persistent equilibria are analyzed via the local linearization method, Lyapunov stability theory and irreducible matrix properties. Furthermore, an event-triggered impulsive control strategy is proposed to control the rumor spreaders and some corresponding control conditions are given. Finally, some numerical simulation results and a practical example are presented to verify the correctness of the theoretical results and reflect the impact of cognitive ability and time delay on rumor propagation.

Toward a Generic Framework for Mission Planning and Execution with a Heterogeneous Multi-Robot System.

This paper presents a comprehensive framework for mission planning and execution with a heterogeneous multi-robot system, specifically designed to coordinate unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) in dynamic and unstructured environments. The proposed architecture evaluates the mission requirements, allocates tasks, and optimizes resource usage based on the capabilities of the available robots. It then executes the mission utilizing a decentralized control strategy that enables the robots to adapt to environmental changes and maintain formation stability in both 2D and 3D spaces. The framework's architecture supports loose coupling between its components, enhancing system scalability and maintainability. Key features include a robust task allocation algorithm, and a dynamic formation control mechanism, using a ROS 2 communication protocol that ensures reliable information exchange among robots. The effectiveness of this framework is demonstrated through a case study involving coordinated exploration and data collection tasks, showcasing its ability to manage missions while optimizing robot collaboration. This work advances the field of heterogeneous robotic systems by providing a scalable and adaptable solution for multi-robot coordination in challenging environments.