Decentralized Control Scheme Research Articles

Rethinking the four-wing problem in plesiosaur swimming using bio-inspired decentralized control

A locomotor system that can function across different environmental conditions and produce a range of performances is one of the most critical abilities needed for extant and extinct animals in order to survive and maximise their competitive fitness. Recent engineering-inspired paleontological studies have reconstructed feasible locomotor patterns in extinct animals. However, it is still challenging to describe how extinct animals successfully adjust their locomotor patterns to new situations (e.g., changes in locomotor speed and morphology). In this study, we develop a novel reconstruction method based on a bio-inspired control system. We focus on plesiosaurs, an extinct aquatic reptile group which has two pairs of flipper-shaped limbs, and demonstrate that a highly optimised, flexible locomotor pattern for all four flippers can be reconstructed based on a decentralized control scheme formulated from extant animals’ locomotion. The results of our robotic experiments show that a simple, local sensory feedback mechanism allows the plesiosaur-like robot to exploit the fluid flow between the flippers and generate efficient swimming patterns in response to changes in locomotor conditions. Our new method provides further evidence how decentralized control systems can produce a pathway between extinct and extant animals in order to understand the how extinct animals moved and how these movement patterns may have evolved.

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.

Robust decentralized controller design for highly Maneuverable Aircraft

Large-scale control systems often encounter challenges due to their intricate control structures, leading to delays and uncertainties when traditional centralized control methods are implemented in engineering applications. In response to these challenges and with the aim of enhancing control efficiency, the exploration of decentralized control approaches has become increasingly prominent. This paper presents two decentralized control strategies: fixed structure control theory, which is built upon the foundational principles of traditional robust controller design, and the weighted model approximation method, which integrates weighted model reduction with optimization strategies. The fixed structure control theory predetermines architecture of the controllers, significantly alleviating the computational burden associated with the development of robust controllers. Conversely, the weighted model approximation method proposes a more intuitive and succinct pathway for controller design and engineering application. The efficacy of these strategies is evaluated through their application to the Highly Maneuverable Aircraft (HIMAT) system. The results demonstrate that, the fixed structure control theory generally exhibits good performance. However, in certain engineering scenarios, the conclusions derived from the weighted model approximation method for decentralized controller design are easier to comprehend and facilitate rapid application.

Decentralized human-like control strategy of mixed-flow multi-vehicle interactions at uncontrolled intersections: A game-theoretic approach

A critical challenge that future autonomous driving systems face is improving the ability to cope with complex real-world interaction scenarios such as uncontrolled intersections. In the near future, a mixed traffic flow of human-driven vehicles (HDVs) and connected autonomous vehicles (CAVs) will coexist in transport networks, which motivates us to explore the interaction between HDVs and CAVs to improve traffic efficiency and safety. To help CAVs better interact with HDVs and adapt to the mixed-flow environment, we propose a human-like decentralized control strategy for CAVs. First, a game-theoretic framework is proposed to model multi-vehicle interactions (including HDV-CAV, CAV-CAV interactions) in the mixed-flow environment. The existence of solutions is proven to ensure the feasibility of the proposed game-theoretic model. Next, a driving style recognition algorithm is embedded into the proposed model to help CAVs understand and predict human drivers’ actions. The proposed model is calibrated via a real-world dataset and used to simulate traffic in several testing scenarios. Real-world vehicle trajectories are used to verify the accuracy of generated vehicle trajectories in simulations. Experimental results indicate that 1) CAVs can take more reasonable actions to determine whether to yield while ensuring safety when competing for the right of way with HDVs using the proposed method compared with conservative driving strategies, 2) a higher penetration rate of CAVs can significantly enhance travel efficiency and lower collision risk at uncontrolled intersections.

Stability control and analysis of hydrogen production using a multi-terminal DC EV charging system with PV

In the shift towards sustainable energy, DC microgrids have emerged as efficient and reliable alternatives to traditional AC systems, particularly suited for low-voltage applications. The adoption of electric vehicles (EVs) in multi-terminal DC (MTDC) systems introduces challenges in maintaining voltage stability, particularly during master station failures. Our research introduces a decentralized control strategy with multi-mode switching to ensure stability under such conditions. We conduct a comprehensive stability analysis of MTDC systems heavily integrated with EVs, identifying the instability risks and proposing mitigation strategies. The effectiveness of our control approach is validated through simulation studies and a detailed state-space model. Additionally, we explore the integration of renewable energy sources and hydrogen production into MTDC systems for EV charging, which minimizes the need for a new power infrastructure and enhances renewable energy use. This integration optimally reduces renewable energy discard rates, thereby improving energy efficiency without compromising system performance. Our study provides practical insights and theoretical support for renewable energy-driven hydrogen production within DC microgrids. The proposed scheme's performance is validated through simulation studies using a state-space model.

A modified droop-based decentralized control strategy for accurate power sharing in a PV-based islanded AC microgrid

This paper introduces a novel droop-based decentralized control scheme to address the power-sharing challenges within a PV-fed islanded AC microgrid. This novel approach integrates both conventional (P-f/Q-V) and virtual impedance concepts to optimize and manage the precise distribution of active and reactive power among parallel operating inverters posing a significant research challenge. The conventional droop control methods encounter limitations such as voltage and frequency deviations and inaccuracies in power-sharing due to line impedance disparities. To overcome these limitations, the proposed solution integrates an enhanced virtual impedance control loop alongside the conventional control loop (P-f/Q-V). The efficacy of this approach is showcased through simulations conducted using the OPAL-RT OP4510 simulator within the MATLAB/Simulink platform. The Real-time simulation outcomes confirm the efficiency of the suggested control strategy, guaranteeing precise distribution of both active and reactive power while upholding stable voltage and frequency profiles within the system.

A wild horse-assisted decentralized control strategy for a PV-battery energy storage system in a DC microgrid

A wild horse-assisted decentralized control strategy for a PV-battery energy storage system in a DC microgrid

Decentralised control strategy for effective utilisation of distributed community energy storage in PV-rich LV distribution network

Integrating a high-capacity residential-scale photovoltaic (PV) system into a low-voltage (LV) network results in voltage rise. Conversely, voltage drops occur during periods of high demand. Furthermore, PV generation characteristics vary with seasonality and daily weather conditions, complicating voltage rise and drop management. On the other hand, community energy storage (CES) emerges as a solution for future community energy management. This study presents an application of distributed CES to effectively manage voltage rise and drop, addressing a prominent challenge accompanying the widespread adoption of PV. However, upon introducing the CES and its accompanying energy capacity, the control strategy must effectively incorporate the utilisation of the CES’s available capacity year-round. In brief, CES control should adapt to the characteristics of PV by charging the CES during high PV generation. It should also release active power to meet high demand by discharging the CES. This will enable both voltage management and effective CES capacity utilisation in response to PV variations due to seasonality and daily weather conditions. The goal mentioned above can be effectively accomplished by forecasting PV output and using the data to adapt to PV characteristics in a centralised manner. However, due to the challenges associated with centralised control, the present paper proposes a decentralised control algorithm that determines charging and discharging power rates for distributed CES, aligning with the PV and load characteristics in an LV distribution network. The proposed control framework consists of two stages: the first stage regularly updates power references based on clear-sky PV profiles, active power measurements at the LV transformer, and CES active power and energy level. The second stage is activated to mitigate voltage transient caused by fast-moving clouds and small increments in solar irradiance, load between consecutive updates of the first stage. To illustrate and validate the concept, a 13-bus LV distribution network is used, and the proposed control algorithm is implemented on a co-simulation platform that combines MATLAB with a real-time digital simulator.

Decentralized Sampled-Data Control for Stochastic Disturbance in Interconnected Power Systems With PMSG-Based Wind Turbines.

The presented work is concerned with the stability performance of frequency response for interconnected power systems (IPSs) with permanent magnet synchronous generator (PMSG)-based wind turbines (WTs) via a decentralized control scheme against external and stochastic disturbances. To do this, initially, the state-space model is derived when a PMSG is penetration into IPSs. Differing from existing works, IPSs with PMSG-based WTs, including the stochastic disturbance, are modeled as a stochastic state-space model. Then, decentralized sampled-data load frequency control is designed to regulate the frequency response of the proposed model against the deterministic and stochastic noises. By constructing bilateral looped Lyapunov functional and using Itôs formula, stochastic sufficient conditions are derived, which ensure that the closed-loop form of the proposed model is asymptotically stable in the mean square with H∞ performance index γ . Finally, three-area IPSs with PMSG-based WTs are validated with derived sufficient conditions. The simulation results confirmed the better-stability performance of frequency response for the proposed stochastic IPSs with PMSG-based WTs.

An improved decentralized control strategy for a PV hybrid energy storage system in an LVDC microgrid

An improved decentralized control strategy for a PV hybrid energy storage system in an LVDC microgrid

A low-cost vision system for online reciprocal collision avoidance with UAVs

In this article, we propose a reciprocal collision avoidance system for autonomous drones, based on computer vision and using relative positioning in an indoor environment. This dynamic environment represents a demanding challenge, but it is crucial for any future existence of multiple drones operating in urban areas. We use commercial AR Drone 2.0 robots, which represent that our proposal is suitable for low-cost equipment. In our case, we attempt to achieve the collision avoidance of two drones that fly one towards the other and react online autonomously to signals received by their computer vision systems with a decentralized control strategy. We test this in four different experiments with demanding conditions. For this purpose, we get the camera signal of the onboard drones and tune their behavior to react smoothly and precisely. We report encouraging positive results and provide the code we use in the experiments for replication.

A multi-point decentralized control for mitigating vibration of flexible space structures using reaction wheel actuators

The vibration with large amplitude and low frequency of the flexible space structures is prone to affect the attitude stability and pointing precision of the spacecraft. To mitigate the vibration of the flexible space structures, a multi-point decentralized control strategy using reaction wheel (RW) actuators is proposed and investigated in this paper. The motion equations of the solar array with multiple RW actuators are derived in modal coordinate representation. To suppress the overall response of the structure, the decentralized control strategy using RW actuators is designed based on the natural frequencies and mode shapes. The stability and the effect of closed-loop dynamic system is theoretically proved. The comparative studies under sun-pointing of the solar array and the rest-to-rest orbital maneuver conditions are presented to show the control performance of the RW actuators. The results indicate that, with 2% increase in total mass from the addition of the actuators, the vibration attenuation time can be decreased by 85.25% and 94.16% for the vibration excited by the sun-pointing and the rest-to-rest orbital maneuver, respectively. The experimental results demonstrate the effectiveness of the proposed decentralized control method. Theoretical analysis, numerical simulation and experimental study are conducted to demonstrate the validity of the proposed vibration mitigation approach and its potential application in the spacecraft design.

Decentralized control strategy of thermostatically controlled loads considering the energy efficiency ratio and measurement error correction

The elimination of traditional thermal generators and the increase of renewable energy source access reduced the inertia of the power system, and thermostatically controlled loads have the potential to provide ancillary services to the power system. This paper introduces a decentralized control strategy for thermostatically controlled loads (TCLs), which focuses on assisting large-scale TCLs in providing frequency support to power systems while considering energy efficiency ratio and measurement error correction. Initially, the nonlinear relationship between heat flow and TCLs’ power is modeled using a polynomial relationship, and the coefficients are determined through a data-driven method to enhance accuracy in TCLs modeling and assess their regulation potential precisely. Subsequently, a decentralized control strategy tailored for power system frequency regulation is developed. To account for measurement errors in TCLs controllers, a measurement error back-correction method is proposed. Simulation examples demonstrate the effectiveness of the proposed control strategy in achieving accurate modeling and control of TCLs and reducing power system frequency fluctuations.

A decentralized control strategy for improved batch tablet coating process operation

This paper proposes a control strategy for batch tablet film-coating processes using readily available process instrumentation. Outlet air conditions (temperature and relative humidity), which impact coating quality, are controlled by the manipulation of inlet air temperature and coating spray rate. Controller design, tuning and validation rely on the use of a dynamic process simulator, calibrated using data collected from a pilot plant coating unit. The final 2 × 2 decentralized PI controller demonstrated good performance for both setpoint tracking and disturbance rejection in simulation. Additionally, controlled variable setpoints were determined to maximize plant profits considering batch duration and energy consumption as optimization criteria. For the case study considered, the total batch processing time can potentially be reduced by 40 % while simultaneously reducing energy usage by 30 %, in comparison with the more conservative fixed recipe approach typically adopted in production.

Delayed non‐fragile robust control of civil structure considering structural uncertainties, actuator faults, and control force time delays

Active control is an effective strategy for suppressing unwanted structural vibrations. The uncertainties in computational models, actuator faults, and time delays in control forces are the potential threats for control performance improvements. These factors are interconnected and may lead to control system instability and poor control effectiveness. The paper presents a delayed non-fragile robust control (DNR) algorithm for uncertain systems with consideration of actuator faults and time delays. To this end, the existence conditions for the DNR multi-objective controller are derived by utilizing the Lyapunov stability proof and introducing a pole constraint inequality. Then, a dynamic output feedback DNR algorithm is further developed. Finally, two numerical simulation examples are discussed for several ground motions. The results show that the control system based on the proposed algorithm exhibits better stability, robustness, and fault tolerance than the linear quadratic Gaussian (LQG) algorithm. Furthermore, there is no need for additional control energy. Significantly, the control performance of the proposed algorithm can be further enhanced with the decentralized control strategy.

Analysis and Development of a Bidirectional Three-Phase Hybrid Rectifier for DC Microgrids With Distributed Energy Resources

This work presents the analysis and development of a Bidirectional Three-phase Hybrid Rectifier (BTHR) for application in Direct Current (DC) Microgrids connected to the utility grid. The voltage regulation technique, called Series DC-bus Voltage Compensation (SDCVC), allows the design of an active front-end converter with high power density. The decentralized control strategy ensures low harmonic distortion of current in the utility grid in both operating modes (rectification and regeneration), in addition to providing DC-bus voltage compensation against power flow dynamics related to Renewable Energy Sources (RES). The operating principle, the control strategy, and the design criteria used for determining the transfer function of the proposed BTHR-SDCVC-DCMG, as well as to the design of the DC-bus voltage controller, are presented. To validate the theoretical analysis, a 1kW prototype was implemented and evaluated at the laboratory. Steady state analysis demonstrate that high efficiency, high power factor, and low harmonic distortion of current are achieved. Finally, transient analysis was performed and demonstrated that the stability of the DC-bus voltage with and without the insertion of RES into the DC microgrid can be assured deploying the proposed solution.

A decentralized approach for the aerial manipulator robust trajectory tracking.

This paper introduces a new decentralized control strategy for an unmanned aerial manipulator (UAM) constrained to the vertical plane. The control strategy comprises two loops: the first compensates for the aerial vehicle's impact on the manipulator; and the second one implements independent controllers for the aerial vehicle and the manipulator. The controller for the aerial vehicle includes an estimator to compensate for the dynamic influence of the manipulator, even if it is affected by external wind-gust disturbances. The manipulator has two revolute joints; however, it is modeled as an dynamically equivalent manipulator, with one revolute and one prismatic joint. The proposed control strategy's performance is evaluated using a simulator that includes the vehicle's aerodynamics and the manipulator's contact force and moment.

Fuzzy adaptive resilient decentralized control of nonlinear interconnected cyber-physical systems under false data injection attacks

In this paper, a new fuzzy adaptive resilient decentralized control method is presented for the nonlinear interconnected cyber-physical systems under false data injection (FDI) attacks. Fuzzy logic systems (FLS) are used to model unknown nonlinear dynamics and the FDI attacks are represented by the sum of the system states and unknown time-varying bounded functions. To deal with the problem of the system states are unavailable under FDI attacks, a new coordinate transformation is proposed for control design. By using the backstepping control design theory and Nussbaum function property, a fuzzy adaptive resilient decentralized control scheme is developed, where the Nussbaum functions are employed to deal with the unknown time-varying weight. Then, the stability of the controlled systems is proved by constructing a appropriate Lyapunov function. Finally, the effectiveness of the proposed fuzzy adaptive resilient decentralized control scheme is verified by the simulation and comparison results.

Decentralized control strategy of air-conditioning loads for primary frequency regulation based on environment information

The existing research on orderly participation of air conditioning load in frequency regulation needs a relatively complete communication architecture, but it cannot be achieved on a large scale in practice. This paper proposes a decentralized control method for the air-conditioning load control to participate in the power system primary frequency regulation, so that the air-conditioning loads can respond to system frequency deviation in an orderly manner without communication. Firstly, the triggering frequency is set to prevent the air-conditioning load from being over- or under-adjusted based on the frequency response interval, which is determined according to the outdoor temperature. Secondly, the response priority is arranged according to the holding time to ensure an orderly response of the air-conditioning load without communication. Finally, a simulation example of a thousand air-conditioning loads under different control strategy proves that the proposed method can achieve better frequency regulation effect.

Operation and control of compact offshore combined cycles for power generation

Gas turbines are the main means for generating power in offshore installations. To increase energy efficiency, and thus reduce CO2 emissions, a steam bottoming cycle can be added to produce additional power by recovering surplus heat from the gas turbine exhaust. Due to space constraints, this solution is not widespread for offshore power generation. To enable deployment, the system must be compact and be able to provide varying power demands. In this paper, we analyze the operation and control problem for such compact combined cycles, consisting of two gas turbines and one steam bottoming cycle. We analyze the steady-state performance of the combined cycle with respect to efficiency and CO2 emissions for two control strategies for coordinating the power setpoint of the two gas turbines. Equal load allocation of the gas turbines showed a higher thermal efficiency and lower emissions compared to keeping one gas turbine close to nominal and letting the second one handle load variations. The main controlled variables for the steam bottoming cycle are the superheated steam pressure and temperature. We implement decentralized control strategies based on standard PID-controllers and nonlinear feedforward. Due to reduced throttle losses, sliding pressure shows higher efficiency and lower CO2 emissions compared to keeping a constant steam pressure, which conversely provides a better temperature dynamic response and may be necessary with highly varying power demand.