Decentralized Control Mechanism Research Articles

Decentralized control mechanism for limb steering in quadruped robot walking

Quadrupedal mammals adaptively change their direction, and their behavior is remarkable when they initiate such turns. They flexibly alter their interlimb coordination patterns when transitioning from forward to turning motion. However, the turning performance of quadruped robots is low compared to that of animals. We attempted to understand the control mechanism underlying the animal's flexible turning behavior by developing a simple robot model. We hypothesize that animals achieve lateral acceleration during transitions by adjusting the position of their limbs sideways at ground contact. On this basis, we proposed a decentralized control model for limb steering in quadrupedal turning behavior. The results obtained from the robot simulation demonstrated that either a turn initiated by the medial forelimb or the lateral forelimb occurred depending on the timing of the turn command. The fact that the proposed control algorithm could reproduce the behavior observed in animals suggests that a mechanism similar to the algorithm may exist in animals. Biological verification is expected in the future.

Conceptualizing digital service: coconstitutive essence and value cocreation dynamics

PurposeThis paper presents a new conceptualization of digital service anchored in a coconstitutive ontology of digital “x” phenomena, illuminating the pivotal role of the digital qualifier in the service context. Our objective is to provide a theoretically grounded conceptualization of digital service and its impact on the nature of the value cocreation process that characterizes digital phenomena.Design/methodology/approachDrawing from scholarly works on digital phenomena and fundamental principles of service-dominant logic, this paper delineates the essence of digital service based on the interplay between digitization and digitalization as well as the operational dynamics of generativity and its constitutive dimensions (architecture, community, governance).FindingsThe paper defines digital service as a sociotechnical process of value cocreation, where participants dynamically architect, govern and leverage digital resources. This perspective highlights the organic development of digital service and the prevalence of decentralized control mechanisms. It also underscores how the intersection between generativity’s dimensions—architecture, community and governance—shapes the dynamic evolution and outcomes of digital services.Originality/valueOur conceptual framework sheds light on our understanding of digital service, offering a foundation to further explore its nature and implications for research and practice, which we illustrate using the case of ChatGPT.

Uncertain Commuters Assignment Through Genetic Programming Hyper-Heuristic

Traffic assignment problem (TAP) is of great significance for promoting the development of smart city and society. It usually focuses on the deterministic or predictable traffic demand and the vehicle traffic assignment. However, in the real world, traffic demand is usually unpredictable, especially the foot traffic assignment inside buildings such as shopping malls and subway stations. In this work, we consider the dynamic version of TAP, where uncertain commuters keep entering the traffic network constantly. These dynamically arriving commuters bring new challenges to this problem where planning paths for each commuter in advance is incompetent. To address this problem, we propose a genetic programming (GP) hyper-heuristic method to assign uncertain commuters in real-time. Specifically, a low-level heuristic rule called reactive assignment strategy (RAS) is proposed and is evolved by the proposed method. All commuters obey the same strategy to route themselves based on their local observations in a traffic network. Through training based on a designed heuristic template, all commuters will have the ability to find their appropriate paths in real-time to maximize the throughput of the traffic network. This decentralized control mechanism can address dynamically arriving commuters more efficiently than centralized control mechanisms. The experimental results show that our method significantly outperforms the state-of-the-art methods and the evolved RAS has a certain generalization ability.

ANN-Based Intelligent Secure Routing Protocol in Vehicular Ad Hoc Networks (VANETs) Using Enhanced AODV

A vehicular ad hoc network (VANET) is a sophisticated wireless communication infrastructure incorporating centralized and decentralized control mechanisms, orchestrating seamless data exchange among vehicles. This intricate communication system relies on the advanced capabilities of 5G connectivity, employing specialized topological arrangements to enhance data packet transmission. These vehicles communicate amongst themselves and establish connections with roadside units (RSUs). In the dynamic landscape of vehicular communication, disruptions, especially in scenarios involving high-speed vehicles, pose challenges. A notable concern is the emergence of black hole attacks, where a vehicle acts maliciously, obstructing the forwarding of data packets to subsequent vehicles, thereby compromising the secure dissemination of content within the VANET. We present an intelligent cluster-based routing protocol to mitigate these challenges in VANET routing. The system operates through two pivotal phases: first, utilizing an artificial neural network (ANN) model to detect malicious nodes, and second, establishing clusters via enhanced clustering algorithms with appointed cluster heads (CH) for each cluster. Subsequently, an optimal path for data transmission is predicted, aiming to minimize packet transmission delays. Our approach integrates a modified ad hoc on-demand distance vector (AODV) protocol for on-demand route discovery and optimal path selection, enhancing request and reply (RREQ and RREP) protocols. Evaluation of routing performance involves the BHT dataset, leveraging the ANN classifier to compute accuracy, precision, recall, F1 score, and loss. The NS-2.33 simulator facilitates the assessment of end-to-end delay, network throughput, and hop count during the path prediction phase. Remarkably, our methodology achieves 98.97% accuracy in detecting black hole attacks through the ANN classification model, outperforming existing techniques across various network routing parameters.

Decentralized control strategies for resilient power systems using multi-agent systems

The study examines the use of Multi-Agent Systems (MAS) in decentralized control mechanisms to improve the resilience of power systems. The analysis included simulations, agent interactions, and system dynamics. The results demonstrate the durability of Generator 001 in City A, as it constantly maintains an average power production of 46.5 MW. On the other hand, Generator 002 in City B regularly generates around 29 MW. Storage Unit 003 efficiently fulfills requests by distributing 15 MW upon receiving a prompt from Generator 001. The system is notably influenced by consumer behavior, as seen by Consumer 004 in City C consistently demanding 31 MW. Significantly, when Consumer 005 is activated, it increases demand to 27.5 MW. An examination of percentage variations indicates little swings in generator outputs at peak times, underscoring their stability. Nevertheless, consumer engagement during periods of high demand results in significant surges in the need for resources. The agents demonstrate effective communication by swiftly acknowledging and fulfilling requests for extra power. The results emphasize the potential of MAS as a viable framework for effectively distributing resources and coordinating various agents. This research provides useful insights into adaptive solutions for effectively managing changing power system circumstances. It highlights the crucial role of Multi-Agent Systems (MAS) in maintaining stability, maximizing the use of resources, and meeting the developing energy needs.

Design of a Decentralized PID Controller Using the Relative Gain Array Technique for a Coupled Flotation Process

This study focuses on the design of the decentralized Proportional-Integral-Derivative (PID) controller for a coupled flotation system. It emphasizes the difficulties encountered when dealing with interconnected Multiple-Input Multiple-Output (MIMO) systems that cannot be effectively regulated using traditional linear feedback controllers. The significance of this article lies in its examination of how the Relative Gain Array (RGA) can be utilized to mitigate the impact of process connections. With the use of a thoughtful selection of single-loop pairings, the decentralized controller is created following the RGA technique. The decentralized controller that has been developed serves the purpose of reducing the influence caused by process interfaces. A set-point tracking technique, based on Internal Model Controllers (IMCs) is adopted in the design. The system time response and overshoot were also analyzed. The paper proposed a decentralized control mechanism and provided a comprehensive process for applying it to both the system under investigation and different MIMO industrial processes. The performance of the suggested closed-loop system was simulated and confirmed using Matlab/Simulink.

Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles

The charging of electric vehicles (EVs) at residential premises is orchestrated through either centralized or decentralized control mechanisms. The former emphasizes adherence to power grid constraints, employing demand management techniques to restrict EV charging when the aggregated demand exceeds a predetermined threshold, which may result in user discontentment. Conversely, the latter endows EV users with the authority to self-regulate their charging behavior to optimize cost, allowing a multitude of interconnected EVs to charge during the same off-peak window. However, this decentralized approach gives rise to the herding problem, wherein a simultaneous surge in EV charging during off-peak periods burdens the power grid, leading to potential system overloads. This paper presents a hybrid coordinating scheme that integrates a fuzzy inference mechanism to synergistically blend the merits of centralized and decentralized coordinations. The proposed hybrid coordination scheme aims to minimize peak load, alleviate herding, and optimize charging costs while ensuring adherence to EV users’ charging obligations at the lowest feasible expense. The problem is formulated with the introduction of a novel fuzzy objective function and subsequently resolved through the fuzzy inference mechanism. The fuzzy inference encapsulates independent and uncertain price profiles, consumption load patterns, and state-of-charge data collected from the power grid, households, and EV domains, which are effectively integrated into weighted variables for the requesting EVs. The proposed hybrid coordinating scheme leverages weighted variables to optimize the objective function, enabling the determination of an optimal charging schedule that satisfies the charging requirements of the requesting EVs, while adhering to stringent power grid operational constraints and minimizing charging costs. To assess the efficacy of the hybrid coordination scheme, we conducted two meticulous case studies employing the IEEE 34 bus system as a testbed, thoroughly evaluating performance metrics encompassing charging cost, load profile impact, and peak-to-average ratio. The results demonstrate the superior performance of the proposed hybrid coordination scheme compared to alternative charging strategies, including uncoordinated charging, standard-rate charging, time-of-use charging, and two-layer decentralized approaches.

Decentralized formation cooperative control for homing of a swarm of underactuated AUVs via singular perturbation

This paper addresses a decentralized control mechanism for the homing process of underactuated AUVs. The mechanism can be decoupled into foraging and tracking. During the homing process, the mother submarine is regarded as a Gaussian type of nutrient profile and underactuated AUVs are regarded as agents in swarm. The problem of homing is transformed into the social foraging. In the swarm, each individual has a double-integrator dynamic. Under the proposed artificial potential field, the motion of each individual is determined by repulsion or attraction from other individuals, attraction from nutrient profile and repulsion from toxicant profile. Therefore, each agent generates a collision-free trajectory tend to the nutrient profile. The trajectories can be used as reference trajectories for the underactuated AUVs. For the trajectory tracking, the speed of attitude dynamics is much faster than that of position dynamics. Such characteristic can be naturally treated by time scale decomposition method and singular perturbation theory which allows independent analysis of the dynamics in each time scale. In addition, the stability of the collective behavior of the swarm and the trajectory tracking controller are proposed by Lyapunov theorem. Finally, the effectiveness of the proposed control mechanism is demonstrated via a set of simulation results.

Adaptive Centipede Walking via Synergetic Coupling Between Decentralized Control and Flexible Body Dynamics.

Multi-legged animals such as myriapods can locomote on unstructured rough terrain using their flexible bodies and legs. This highly adaptive locomotion emerges through the dynamic interactions between an animal’s nervous system, its flexible body, and the environment. Previous studies have primarily focused on either adaptive leg control or the passive compliance of the body parts and have shown how each enhanced adaptability to complex terrains in multi-legged locomotion. However, the essential mechanism considering both the adaptive locomotor circuits and bodily flexibility remains unclear. In this study, we focused on centipedes and aimed to understand the well-balanced coupling between the two abovementioned mechanisms for rough terrain walking by building a neuromechanical model based on behavioral findings. In the behavioral experiment, we observed a centipede walking when part of the terrain was temporarily removed and thereafter restored. We found that the ground contact sense of each leg was essential for generating rhythmic leg motions and also for establishing adaptive footfall patterns between adjacent legs. Based on this finding, we proposed decentralized control mechanisms using ground contact sense and implemented them into a physical centipede model with flexible bodies and legs. In the simulations, our model self-organized the typical gait on flat terrain and adaptive walking during gap crossing, which were similar to centipedes. Furthermore, we demonstrated that the locomotor performance deteriorated on rough terrain when adaptive leg control was removed or when the body was rigid, which indicates that both the adaptive leg control and the flexible body are essential for adaptive locomotion. Thus, our model is expected to capture the possible essential mechanisms underlying adaptive centipede walking and pave the way for designing multi-legged robots with high adaptability to irregular terrain.

Towards energy-efficient and cost-effective DC nanaogrid: A novel pseudo hierarchical architecture incorporating V2G technology for both autonomous coordination and regulated power dispatching

Most recently, DC nanogrid incorporating effective energy management has attracted widespread attention. Due to its favorability to integrate renewable energy sources and emerging power electronic loads, such as photovoltaics and electric vehicles (EVs), DC nanogrid is believed to be able to improve the energy utilization efficiency and mitigate the carbon footprint in the coming decades. Towards a compact, cost-effective, and easy-to-build energy management scheme for nanogrid, this paper presents a pseudo hierarchical management architecture built upon the smart charging point. The proposed architecture incorporates the upper-level central controller with the local power role creatively and comprises two timescale management levels with corresponding operation strategies. In the short-timescale local management level, a state-triggered droop strategy based on the decentralized control mechanism is introduced to realize the autonomous power coordination without extensive communication links. The autonomous vehicle-to-grid (V2G) operation is also implemented with providing real-time power balance capability to unpredicted and short-timescale load variation in peak periods. In the power dispatching level, a multi-mode power dispatching strategy involving six operation modes is introduced to realize the efficient power scheduling for the nanogrid. The effectiveness of the proposed architecture and operation strategy is verified in the detailed simulation model and hardware-in-loop experiment platform. The results show that the real-time, autonomous, and stabilized power coordination in nanogrid could be realized along with a self-regulated V2G operation. Additionally, the peak-shaving and valley-filling of load curve, the satisfaction of EV charging demand, and an improved operation economy are achieved under the proposed architecture and operation strategy.

Simple decentralized control mechanism that enables limb adjustment for adaptive quadruped running.

Quadrupeds exhibit versatile and adaptive running by exploiting the flying phase during the stride cycle. Various interlimb coordination mechanisms focusing on mechanical loads during the stance phase have been proposed to understand the underlying control mechanism, and various gait patterns have been reproduced. However, the essential control mechanism required to achieve both steady running patterns and non-steady behaviours, such as jumping and landing, remains unclear. Therefore, we focus on the vertical motions of the body parts and propose a new decentralized interlimb coordination mechanism. The simulation results demonstrate that the robot can generate efficient and various running patterns in response to the morphology of the body. Furthermore, the proposed model allows the robot to smoothly change its behaviour between steady running and non-steady landing depending on the situation. These results suggest that the steady and non-steady behaviours in quadruped adaptive running may share a common simple control mechanism based on the mechanical loads and vertical velocities of the body parts.

Fast-MICDTN: a new decentralized control mechanism for content-centric disruption tolerant networks

Information-Centric Networking (ICN) emerges as a promising architecture for the future Internet to keep up with the tremendous growth of Internet users and the explosive increase of mobile data traffic. ICN can be coupled with Disruption Tolerant Networking (DTN) to overcome the limitations of the current Internet architecture in some challenging environments where we cannot establish a network connection, and also lighten the load on the Internet backhaul. Unfortunately, resources constraints, such as energy and buffer space, are among the most serious issues in Mobile Information-Centric Disruption Tolerant Networking (MICDTN). In this paper, we introduce an opportunistic DTN-based forwarding mechanism of Interest and Data for ICN, named Fast-MICDTN. The propagation of the content have been modeled using Markov-Decision Process (MDP). Hence, we characterize the living period in transit of the content to reach the maximum possible number of mobiles. Through extensive simulations based on synthetic mobility model and real-world traces, we prove the efficiency of the new approach in sharing content within a large number of users under a low cost.

Decentralized and prioritized algorithm for AGV fleet management

In this paper we propose an algorithm based on prioritization for coordinating autonomously guided vehicles (AGVs) in a grid/mesh topology, where the tasks arrive online into the system. The method combines a decentralized control mechanism based on prioritization with an optimization subroutine to resolve eventually occurring deadlock situations. The merits of the method are evaluated on a set of benchmark instances.

Decoding Decentralized Control Mechanism Underlying Adaptive and Versatile Locomotion of Snakes.

Snakes have no limbs and can move in various environments using a simple elongated limbless body structure obtained through a long-term evolutionary process. Specifically, snakes have various locomotion patterns, which they change in response to conditions encountered. For example, on an unstructured terrain, snakes actively utilize the terrain's irregularities and move effectively by actively pushing their bodies against the "scaffolds" that they encounter. In a narrow aisle, snakes exhibit concertina locomotion, in which the tail part of the body is pulled forward with the head part anchored, and this is followed by the extension of the head part with the tail part anchored. Furthermore, snakes often exhibit three-dimensional (3-D) locomotion patterns wherein the points of ground contact change in a spatiotemporal manner, such as sidewinding and sinus-lifting locomotion. This ability is achieved possibly by a decentralized control mechanism, which is still mostly unknown. In this study, we address this aspect by employing a synthetic approach to understand locomotion mechanisms by developing mathematical models and robots. We propose a Tegotae-based decentralized control mechanism and use a 2-D snake-like robot to demonstrate that it can exhibit scaffold-based and concertina locomotion. Moreover, we extend the proposed mechanism to 3D and use a 3-D snake-like robot to demonstrate that it can exhibit sidewinding and sinus-lifting locomotion. We believe that our findings will form a basis for developing snake-like robots applicable to search-and-rescue operations as well as understanding the essential decentralized control mechanism underlying animal locomotion.

Beacon-referenced pursuit for collective motions in three dimensions.

Motivated by real-world applications of unmanned aerial vehicles, this paper introduces a decentralized control mechanism to guide steering control of autonomous agents manoeuvring in the vicinity of multiple moving entities (e.g. other autonomous agents) and stationary entities (e.g. fixed beacons or points of reference) in a three-dimensional environment. The proposed control law, which can be perceived as a modification of the three-dimensional constant bearing (CB) pursuit law, provides a means to allocate simultaneous attention to multiple entities. We investigate the behaviour of the closed-loop dynamics for a system with one agent referencing two beacons, as well as a two-agent mutual pursuit system wherein each agent employs the beacon-referenced CB pursuit law with regards to the other agent and a stationary beacon. Under certain assumptions on the associated control parameters, we demonstrate that this problem admits circling equilibria with agents moving on circular orbits with a common radius, in planes perpendicular to a common axis passing through the beacons. As the common radius and distances from the beacon are determined by the choice of parameters in the pursuit law, this approach provides a means to engineer desired formations in a three-dimensional setting.

Decentralized Control Mechanism Underlying Adaptive and Versatile Locomotion of Snakes

Decentralized Control Mechanism Underlying Adaptive and Versatile Locomotion of Snakes

Flexible Coordination of Flexible Limbs: Decentralized Control Scheme for Inter- and Intra-Limb Coordination in Brittle Stars' Locomotion.

Conventional mobile robots have difficulties adapting to unpredictable environments or performing adequately after undergoing physical damages in realtime operation, unlike animals. We address this issue by focusing on brittle stars, an echinoderm related to starfish. Most brittle stars have five flexible arms, and they can coordinate among the arms (i.e., inter-arm coordination) as well as the many bodily degrees of freedom within each arm (i.e., intra-arm coordination). They can move in unpredictable environments while promptly adapting to those, and to their own physical damages (e.g., arm amputation). Our previous work focused on the inter-arm coordination by studying trimmed-arm brittle stars. Herein, we extend our previous work and propose a decentralized control mechanism that enables coupling between the inter-arm and intra-arm coordination. We demonstrate via simulations and real-world experiments with a brittle star-like robot that the behavior of brittle stars when they are intact and undergoing shortening or amputation of arms can be replicated.

Decentralized Control Mechanism for Determination of Moving Direction in Brittle Stars With Penta-Radially Symmetric Body.

A brittle star, an echinoderm with penta-radially symmetric body, can make decisions about its moving direction and move adapting to various circumstances despite lacking a central nervous system and instead possessing a rather simple distributed nervous system. In this study, we aimed to elucidate the essential control mechanism underlying the determination of moving direction in brittle stars. Based on behavioral findings on brittle stars whose nervous systems were lesioned in various ways, we propose a phenomenological mathematical model. We demonstrate via simulations that the proposed model can well reproduce the behavioral findings. Our findings not only provide insights into the mechanism for the determination of moving direction in brittle stars, but also help understand the essential mechanism underlying autonomous behaviors of animals. Moreover, they will pave the way for developing fully autonomous robots that can make decisions by themselves and move adaptively under various circumstances.

Decentralized control mechanism for body–limb coordination in quadruped running

As a mechanism for survival, quadrupeds have obtained skills involving coordination between limbs and the body (i.e. body–limb coordination), providing fast and adaptive locomotion compared with motion using only limbs. Several bio-inspired robotics studies have resulted in the development of legged robots that utilize a flexible spine, similar to cheetahs. However, the control principle of body–limb coordination has not been established to date. From the perspective of a decentralized control scheme, a minimal body–limb coordination mechanism is proposed in this study, in which body parts aid each other via a sensory feedback mechanism. The two-dimensional simulation and hardware experiments reveal that bilateral sensory feedback between limbs and body is essential for the robot to adaptively generate a body–limb coordination pattern and achieve faster locomotion speed than that by only limbs in efficient manner.

Body-limb coordination mechanism underlying speed-dependent gait transitions in sea roaches

The sea roach is an isopod with 14 legs; owing to its many degrees of freedom and coordination thereof, it can walk rapidly on rough terrain. Although there likely exists a remarkable decentralized control mechanism that facilitates fast and adaptive locomotion of sea roaches, it still remains elusive. To address this issue, we performed behavioural experiments and revealed that sea roaches often change their gait patterns depending on the locomotion speed. We suggest that the bending of the body trunk in the pitch direction is essential for the gait transitions, and we propose a decentralized control mechanism for body-limb coordination. We demonstrate this with a sea-roach-like robot whose gait transition is achieved by the proposed mechanism. This mechanism has some points in common with control mechanisms proposed for other legged animals. Thus, our findings will help unveil the common principle of legged locomotion and aid the design of multi-legged robots that move like animals.