Formation Control Research Articles

Leader-Follower Formation and Obstacle Avoidance for Nonholonomic Mobile Robots Using Velocity Obstacles

A multi-robot system is a group of robots that coordinate and perform complex tasks with the help of a communication system. The commonly adapted approaches in multi-robot formation control include the leader-follower method, where the leading robot acts as the coordination center, and follower robots track the movement of the leading robot. Multi-robot formations are usually faced by static and dynamic obstacles in the operational environment. In this paper, the obstacle-avoidance challenge is tackled by adopting the concept of velocity obstacles in a way that enables the robots to efficiently consider not only the velocity of an obstacle but also its direction in order to avoid collision. The method is evaluated through several simulation scenarios in different environments. The simulation results show that the multi-robot formation version can successfully avoid static and dynamic obstacles and reform a formation right afterward from zero collisions.

Distributed adaptive control of spacecraft formation near an asteroid with input quantization

Distributed adaptive control of spacecraft formation near an asteroid with input quantization

Regulation of UCP1 expression by PPARα and pemafibrate in human beige adipocytes.

Thermogenic adipocytes are able to dissipate energy as heat from lipids and carbohydrates through enhanced uncoupled respiration, due to UCP1 activity. PPAR family of transcription factors plays an important role in adipocyte biology. The purpose of this work was to characterize the role of PPARα and pemafibrate in the control of thermogenic adipocyte formation and function. We used human multipotent adipose-derived stem cells and primary cultures of stroma-vascular fraction cells, transfected with siRNA against PPARα, differentiated into white or beige adipocytes, by the treatment of rosiglitazone or pemafibrate. The expression of key marker genes of adipogenesis and thermogenesis was determined using RT-qPCR and Western blotting. An RNAseq analysis was also performed. We show that inhibition of PPARα mRNA increases UCP1 mRNA and protein expression in beige adipocytes induced by rosiglitazone. Knock-down of PPARα also increases stimulated glycerol release. Pemafibrate, described as a selective PPARα modulator, induces adipogenesis and the expression of UCP1 in the absence of PPARα expression. These effects are inhibited by a specific PPARγ antagonist highly suggesting that the pemafibrate effects in adipogenesis and beiging were mediated by PPARγ. Conversion of white into thermogenic adipocytes is mainly due to the activation of PPARγ. Moreover, we show that PPARα seems to act as a hindrance for PPARγ-dependent beiging. Our data question the role of PPARα in human adipocyte browning and the specificity of pemafibrate in adipocytes.

Anti-saturation distributed fixed-time prescribed performance sliding mode formation control based on FXESO for uncertain USVs

Anti-saturation distributed fixed-time prescribed performance sliding mode formation control based on FXESO for uncertain USVs

Dynamic Event-Triggered Active Disturbance Rejection Formation Control for Constrained Underactuated AUVs

Dynamic Event-Triggered Active Disturbance Rejection Formation Control for Constrained Underactuated AUVs

The Impact of Fluid Flow on Microbial Growth and Distribution in Food Processing Systems

This article examines the impact of fluid flow dynamics on microbial growth, distribution, and control within food processing systems. Fluid flows, specifically laminar and turbulent flows, significantly influence microbial behaviors, such as biofilm development and microbial adhesion. Laminar flow is highly conducive to biofilm formation and microbial attachment because the flow is smooth and steady. This smooth flow makes it much more difficult to sterilize the surface. Turbulent flow, however, due to its chaotic motion and the shear forces that are present, inhibits microbial growth because it disrupts attachment; however, it also has the potential to contaminate surfaces by dispersing microorganisms. Computational fluid dynamics (CFD) is highlighted as an essential component for food processors to predict fluid movement and enhance numerous fluid-dependent operations, including mixing, cooling, spray drying, and heat transfer. This analysis underscores the significance of fluid dynamics in controlling microbial hazards in food settings, and it discusses some interventions, such as antimicrobial surface treatments and properly designed equipment. Each process step from mixing to cooling, which influences heat transfer and microbial control by ensuring uniform heat distribution and optimizing heat removal, presents unique fluid flow requirements affecting microbial distribution, biofilm formation, and contamination control. Food processors can improve microbial management and enhance product safety by adjusting flow rates, types, and equipment configurations. This article helps provide an understanding of fluid–microbe interactions and offers actionable insights to advance food processing practices, ensuring higher standards of food safety and quality control.

A Distributed Actor‐Critic Learning Approach for Affine Formation Control of Multi‐Robots With Unknown Dynamics

ABSTRACTFormation maneuverability is particularly important for multi‐robots (MRs), especially when the robots are operating cooperatively in complex and dynamic environments. Although various methods have been developed for affine formation, it is still a difficult problem to design an affine formation controller for MRs with unknown dynamics. In this paper, a distributed actor‐critic learning approach (DACL) in a look‐ahead rollout manner is proposed for the affine formation of MRs under local communication, which improves the online learning efficiency. In the proposed approach, a distributed data‐driven online optimization mechanism is designed via the sparse kernel technique to solve the near‐optimal affine formation control issue of MRs with unknown dynamics as well as improve control performance. The unknown dynamics of MRs are learned offline based on precollected input‐output datasets, and the sparse kernel‐based approach is employed to increase the feature representation capability of the samples. Then, the proposed distributed online actor‐critic algorithm for each robot in the formation includes two neural networks, which are utilized to approximate the costate functions and the near‐optimal policies. Moreover, the convergence analysis of the proposed approach has been conducted. Finally, numerical simulation and KKSwarm‐based experiment studies are performed to verify the effectiveness of the proposed approach.

A Robust Cooperative Control Protocol Based on Global Sliding Mode Manifold for Heterogeneous Nonlinear Multi-Agent Systems Under the Switching Topology

This study addresses the completely distributed consensus control problem for the heterogeneous nonlinear multi-agent system (MAS) with disturbances under switching topology. First, a global sliding mode manifold (GSMM) is designed for the overall MAS dynamic, which maintains stability without oscillations during topology switching after achieving the sliding mode. Subsequently, a consensus sliding mode control protocol (SMCP) is proposed, adopting the common sliding mode control (SMC) format and ensuring the finite-time reachability of the GSMM under topology switching. Finally, the proposed GSMM and SMCP are applied to the formation control of multiple-wheeled mobile robots (WMRs), and simulation results confirm their feasibility and effectiveness. The proposed SMCP design demonstrates key advantages, including a simple control structure, complete robustness to matched disturbance, and reduced-order dynamics under the sliding mode.

Secure Platooning Control of Connected Vehicles Against Data Injection Attacks

This paper presents an attack-defense formation control framework for connected vehicle platoons. This framework effectively addresses the challenges posed by malicious attacks on multi-intelligent vehicle systems in open network environments. First, from the attacker’s perspective, an optimal data injection attack strategy is designed, taking into account energy constraints and the complexities of the communication environment. This strategy aims to disrupt the multi-intelligent vehicle system with minimal energy expenditure. Next, from the defender’s perspective, a formation compensation control strategy is proposed to enhance the system’s resilience against such attacks. This defense control strategy includes real-time monitoring and adjustments of the communication data between vehicles, ensuring that the vehicle formation remains stable and coordinated even in the case of data injection attacks. Finally, simulation experiments are conducted to validate the effectiveness and robustness of the proposed methods.

Distributed formation control of AUVs under external disturbance and intermittent communication

Distributed formation control of AUVs under external disturbance and intermittent communication

Reinforcement Learning‐Based Prescribed Performance Formation Control for USVs With Collision Avoidance and Preserved Connectivity

ABSTRACTThis paper proposes the reinforcement learning‐based prescribed performance optimal formation control approach for a fleet of unmanned surface vehicles (USVs) with collision avoidance and preserved connectivity. Firstly, to improve the prescribed performance of formation errors while ensuring collision avoidance and preserving connectivity between two successive USVs, the monotone tube boundary functions are designed. Compared to the traditional exponential form of prescribed performance control, the formation error can converge accurately to the vicinity of the origin within a predefined time, and the overshoot of the formation error is constrained. Secondly, in order to derive realistic optimal solutions, an actor‐critic reinforcement learning algorithm is implemented and the unknown parameters are approximated using identifier neural networks, which simplifies the Hamilton‐Jacobi‐Bellman equation to obtain optimal control solutions. Meanwhile, to simplify the computational complexity, a simple positive function is designed, and the gradient descent method is applied to it such that the simplified critic and actor weight updating laws are acquired. Finally, within the framework of the backstepping method, the adaptive optimal formation control strategy ensures that USVs follow a given reference trajectory and maintain the required line‐of‐sight (LOS) range between two consecutive USVs. The feasibility and effectiveness of the proposed control approach are well illustrated by the simulation results.

Shape‐Reconfigurable Crack‐Based Strain Sensor with Ultrahigh and Tunable Sensitivity

AbstractIn the field of wearable electronics and human–machine interfaces, there is a growing need for highly sensitive and adaptable sensors capable of detecting a wide range of stimuli with high precision. Traditional sensors often lack the versatility to adjust their sensitivity for different applications. Inspired by the mechanosensory system of spiders, a shape‐reconfigurable crack‐based sensor with ultrahigh and tunable strain sensitivity based on the precise control of nanocrack formation on a shape memory polymer substrate is demonstrated. This design incorporates a line‐patterned substrate composed of a thermoplastic polyurethane (TPU) matrix and thermo‐responsive shape memory polymer, poly(lactic acid) (PLA), to form parallel nanocracks in a thin platinum film. This design achieves an ultrahigh gauge factor of 2.7 × 109 at 2% strain, significantly surpassing conventional sensors. The shape memory property of the TPU/PLA substrate enables tunable strain sensitivity according to the desired strain range, eliminating the need for multiple sensors. The sensor demonstrates exceptional capabilities in detecting subtle strains (as low as 0.025%), monitoring biological signals, and sensing acoustic waves (100–20 000 Hz) with a response time of 0.025 ms. This work represents a significant advancement toward strain sensors with both ultrahigh and tunable sensitivity.

Vertex-Weighted Consensus-Based Formation Control with Area Constraints and Collision Avoidance

In this paper, a consensus-based formation control strategy is presented, subject to area constraints and collision avoidance. To achieve a desired formation pattern, a control law is proposed that incorporates a vertex-tension function along with signed area constraints. The vertex-tension function provides the capabilities of collision avoidance among agents. Moreover, signed area constraints avoid local minimum stagnation and mitigate ambiguities within the formation shape. Additionally, the proposed approach can be implemented considering a group of differential-drive mobile robots in both centralized and decentralized settings. Simulation and real-world experiments are performed to validate the effectiveness of the proposed approach, where the experimental setup includes a multi-robot system composed of Turtlebot3® Waffle Pi robots.

Event-Triggered Bipartite Formation Control for Switched Nonlinear Multi-Agent Systems with Function Constraints on States

A distributed adaptive fuzzy event-triggered bipartite formation tracking control scheme is proposed for switched nonlinear multi-agent systems (MASs) with function constraints on states. Fuzzy logic systems (FLSs) are used to identify uncertain items. To improve the transient performance of the system, a fixed-time prescribed performance function (FTPPF) is introduced to make the formation error converge to a prescribed boundary range within a fixed time. Considering that the state constraint boundary is restricted by multiple pieces of information (historical state, topological relationship, neighbor agent output, leader signal and time), a tan-type barrier Lyapunov function (BLF) is constructed to address the challenges brought by the state function constraint. The shortcoming of the “explosion of complexity” is compensated by fusing the backstepping control and command filter. To mitigate the communication burden while ensuring a steady-state performance, a distributed event-triggered fixed-time bipartite formation control scheme is proposed. Finally, the performance of the proposed control method is verified by an MAS consisting of four followers and one leader.

Robust formation control of multiple aerial robotic vehicles using near neighbor cyclic deviation with time-varying disturbances.

Cooperative formation flight of multiple aerial robotic vehicles (ARVs) is extensively adopted in emergency rescue and collaborative transport. But the time-varying complex disturbances are inevitable in the cooperative formation flight of multiple ARVs, which can affect the formation stability of multi-ARV systems. This paper investigates the robust formation control problems for multiple ARVs with time-varying disturbances. A novel high-order sliding mode control (HOSMC)-based near neighbor cyclic deviation synchronization control (NNCDSC) scheme for multi-ARV systems is proposed, which can improve the formation control precision and enhance the robustness against time-varying complex disturbances. Firstly, the formation control problem is transformed into the synchronization control problem of multi-ARV systems; a novel NNCDSC strategy is proposed, that can decrease the complexity of the formation control system. Secondly, to better cope with time-varying complex disturbances and improve the formation control accuracy of multi-ARV systems, the HOSMC-based NNCDSC scheme for multi-ARV systems is designed by combining NNCDSC and HOSMC. The finite time stability of the formation control system can be guaranteed by Lyapunov stability theorem, and the desired time-varying or time-invariant formation of multi-ARV systems can also be achieved. Finally, the validity of the theoretical results is verified by several simulation examples and an outdoor experiment.

Synthesis and characterization of ZnO QDs - GO core-shell nanoparticles via sonochemistry

In this work, an innovative approach for the synthesis of ZnO QDs-GO core-shell nanostructures by ultrasonic bath sonochemistry is presented. This method allows the formation of nanostructures with a ZnO QDs core and outer layer of GO sheets, optimizing the formation and interaction. The proposed concentration conditions of the precursors achieve morphological control and structural properties of the nanostructures. The characterizations carried out by FT-IR, Raman and TEM confirm the successful formation of the CS structure. This work provides a significant advance in the compression and control of formation of nanohybrid structures, redesigning the synthesis for various technologies.

Decentralized multi-robot formation control in environments with non-convex and dynamic obstacles based on path planning algorithms

Decentralized multi-robot formation control in environments with non-convex and dynamic obstacles based on path planning algorithms

Modulation of Mitochondria-Endoplasmic Reticulum Contacts (MERCs) by Small Molecules as a New Strategy for Restoring Lipid Metabolism in an Amyotrophic Lateral Sclerosis Model.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease without effective treatment. The progressive motoneuron death in ALS is associated with alterations in lipid metabolism. As its regulation occurs in mitochondria-associated endoplasmic reticulum (ER) membranes (MAMs), modulation of mitochondria-ER contacts (MERCs) is emerging as a crucial factor in MAM formation and lipid metabolism control. Using the MERLIN biosensor in a high-throughput screening within the EU-OPENSCREEN ERIC, we discovered small molecules that increase MERCs in HCT116 cells, enhancing their ability to uptake cholesterol. We demonstrated that cholesterol trafficking is decreased in an ALS patient-derived cell model, and this trafficking is restored after treatment with the discovered MERC modulator 24. Electron microscopy revealed that treatment with compound 24 increases MERCs, promotes lipid droplet formation, and restores mitochondrial cristae. Overall, the brain-permeable MERC modulator, compound 24, may serve as a valuable pharmacological tool for studying MAM function and holds potential for in vivo studies in ALS and other MAM dysfunction diseases.

Income and expenses from the rental of specialized equipment

The subject of the article is the specifics of recognizing income and expenses from leasing specialized equipment under an operating lease agreement from a lessor. The research methods are analysis, synthesis, and deduction. The results of the study can be used in the organization of accounting for specialized equipment from the landlord.The content of the lease agreement affects the formation of information on the income and expenses of the organization. A legal basis has been outlined that determines the conclusion of a lease agreement for specialized equipment and the reflection of information about it in accounting (financial) statements. The main problems of the lease agreement for specialized equipment have been identified. The article justifies the need to determine the legal status of specialized equipment. This is due to its unreasonable identification with ground vehicles in regulatory documents. Methods for determining the amount of rent are highlighted. The problems of determining the rent as the basis for the amount of revenue in the case of dependence of the rent on the time of actual use of the property by the tenant are indicated. The author justified the problems of tracking the time of actual use of the object. The article draws a relationship between the model of the lease agreement and the entity bearing the main costs of maintaining the facility. The transfer of the object for rent with a crew increases the costs of the landlord.

Antagonistic Two‐Color Control of Polymer Network Formation

AbstractOffering high spatiotemporal resolution, dual wavelength‐controlled soft matter network formation paves the way to advanced printing techniques with optimized performance. One of the most promising approaches is the antagonistic control of covalent bond‐forming reactions with two colors of light, where photoexcitation with one wavelength induces a photochemical reaction, while irradiation with the other ceases it in the presence of the first color. Herein, we combine a photoactivatable diene precursor and a photoswitchable dienophile, establishing a dual‐wavelength‐gated cycloaddition reaction capable of controlling polymer crosslinking. Upon incorporation of the diene precursor into a methacrylate copolymer and the synthesis of a difunctional dienophile cross‐linker, selective polymer network formation is promoted under sole UV illumination, while it can be efficiently suppressed with simultaneous redlight irradiation. Critically, the methodology is used for the preparation of solid polymer materials with antagonistic two‐color control of their cross‐linking status, ultimately allowing the fabrication of spatially patterned polymer films.