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This study studies the problem of synchronisation control for spacecraft formation via extended state observer approach over directed communication topology. The attitude kinematics and dynamics of spacecraft are described by Lagrangian formulations, and the decentralised controller is designed with time-varying external disturbances and unmeasurable velocity information. In particular, the estimation of disturbances obtained via extended state observer is used for the decentralised controller design. A novel Lyapunov function is proposed to show that both static regulation and dynamic synchronisation are realised. Finally, simulation results are given to demonstrate the effectiveness of the controllers proposed in this study.

This research paper addresses the challenge of designing a decentralized controller for a discrete-time uncertain polytopic system with a linear large-scale (LSS) structure. Specifically, we investigate this problem in cases where the subsystem’s output matrix lacks a decentralized structure. Firstly, the proposed novel procedure of a decentralized controller design transforms the LSS model to have a fully decentralized structure (both input and output matrices are block-diagonal). Then, the robust stability boundary parameter is calculated for the open-loop system. This stability boundary parameter is considered in robust decentralized controller design where an appropriate controller design method is used. The entire process of designing a robust decentralized controller takes place at the subsystem level, and the influence of interaction is considered through the robust stability boundary parameter. Lastly, we present an example of a five-order system comprising two subsystems to show the effectiveness of the new method.

This paper contains methodology research for forming the control algorithm for a distillation column, modeled as TITO (two-input two-output) process. Its modified form was obtained by connecting the two parts, and this combination hasn't been applied for such a industrial plant, until now. These parts include: a simplified decoupler which was first designed and decentralized PID controller obtained using D-decomposition method for such decoupled process. The decoupler was designed in order to make process become diagonal, and parameters of PID controllers are defined for the two SISO (single-input single-output) processes starting from relation between IE (integral error) criterion and integrator gain, taking into account desired response characteristics deriving from technological requirements of controlled plant. Their connecting provides centralized control. Analysis of the processes responses, obtained by the proposed algorithm and their comparison with the results from the literature, were performed after the completion of the simulations. The proposed approach to the centralized controller design, beside its simplicity of usage and flexibility in achieving diversity of process dynamic behavior, gives better response characteristics, in comparison with existing control algorithms for distillation column in the literature. nema

This chapter contains sections titled: Introduction Relative Gain Array and Variants ì‐Interaction Measure Pairing Analysis Based on the Controllability and Observability Input‐Output Pairing for Uncertain Multivariable Plants Input‐Output Pairing for Non‐linear Multivariable Plants Conclusions References

This study presents a solution to the problem of cooperative path following of multiple underactuated marine surface vehicles subject to dynamical uncertainties and ocean disturbances. The dedicated control designs are categorised into two envelopes. One is to steer individual underactuated marine surface vehicle to track a given spatial path; and the other is to synchronise the along-path speeds and path variables under the constraints of an underlying communication network in order to hold a desired formation pattern. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicle based on neural networks and a dynamic surface control (DSC) technique. Then, the along-path speeds and path variables are synchronised to each vehicle owing to the proposed decentralised synchronisation control law building on graph theory and Lyapunov theory. The key features of the developed controllers are that, first, the DSC technique simplifies the controller design by introducing first-order filters and avoids the calculation of derivatives of virtual control signals. Second, the developed controllers with filtering adaptive laws allow for fast learning without generating high-frequency oscillations in control signals. Rigorous theoretical analysis demonstrates that all signals in the closed-loop system are uniformly ultimately bounded. Simulation results are provided to show the efficacy of the proposed method.

This survey provides an overview of combining federated learning (FL) and control to enhance adaptability, scalability, generalization, and privacy in (nonlinear) control applications. Traditional control methods rely on controller design models, but real‐world scenarios often require online model retuning or learning. FL offers a distributed approach to model training, enabling collaborative learning across distributed devices while preserving data privacy. By keeping data localized, FL mitigates concerns regarding privacy and security while reducing network bandwidth requirements for communication. This survey summarizes the state‐of‐the‐art concepts and ideas of combining FL and control. The methodical benefits are further discussed, culminating in a detailed overview of expected applications, from dynamical system modelling over controller design, focusing on adaptive control, to knowledge transfer in multi‐agent decision‐making systems. This survey explores the integration of federated learning with control systems to improve adaptability, scalability, generalization, and privacy in nonlinear control applications. Federated learning enables distributed model training while maintaining data privacy, making it useful for real‐world scenarios that require secure adaptive and collaborative learning. The manuscript provides a comprehensive overview of the state‐of‐the‐art in this domain, highlighting potential applications such as dynamic system modelling, adaptive control design, and knowledge transfer in multi‐agent decision‐making systems.

In this study, the authors present decentralised adaptive controllers for two cooperating robotic manipulators moving an object with constrained trajectory/force in the presence of dynamics uncertainties and external disturbances. The cooperating manipulators are described as an aggregation of subsystems. For control design, first a decentralised local dynamics coupled with physical interactions between subsystems is developed, and then a decentralised adaptive control merging parameter adaptation and disturbance observer is constructed, such that motion and force trajectories converge to the desired manifolds and the effect of non-parametrisable uncertainties is compensated by the disturbance observer. Experiment studies are carried out to show the efficiency of the control design.

This paper presents a novel decentralized controller design approach for synchronous generators’ voltage and power control in complex power systems. Unlike traditional methods that require detailed modeling of interconnection dynamics, our method exploits the relationship between the stability of isolated subsystems and that of the overall system by transforming the plant model into a descriptor form with a block-diagonal (decentralized) structure. This transformation enables independent controller synthesis at the subsystem level through a method consisting of three key steps. First, the overall stability of the complex power system is evaluated using a Lyapunov function approach. Second, stability conditions at the subsystem level are derived such that ensuring each subsystem’s closed-loop stability guarantees the stability of the entire system. Third, a decentralized controller is designed using any suitable method (e.g., via extended LMI/BMI conditions), with the guarantee that the closed-loop subsystem stability measure is enhanced relative to the open-loop. The robust controller design is carried out via extended LMI/BMI conditions, ensuring improved dynamic performance and robust performance under bounded disturbances by incorporating variations in subsystem parameters. Simulation results on a multi-generator power system demonstrate improved transient response, robust disturbance rejection, and scalability, making the proposed method an attractive solution for large-scale power system control.

Distributed Energies Resources (DERs) can be controlled for supporting the voltage regulation at nodes of an Active Distribution Network (ADN) where they are connected. However, since the ADN is a Multi-Input Multi-Output (MIMO) system with coupled dynamics, the controller of a DER mutually interacts with all other controllers through the distribution lines. These interactions lead to operating conflicts which may drive the ADN to work close to its voltage stability boundaries. To achieve a stable voltage regulation without new investment in the existing ADNs, the present paper proposes a straightforward decentralized design of the multi-loop controllers based on the property of integral controllability. The main feature of the method is that the design problem can be expressed by a single parameter designed both for reducing the effects of the undesired coupling and for increasing the degree of robust stability in the presence of parameter uncertainty in the matrix plant. Simulation studies are developed to illustrate the design result and the performance achieved under different operating conditions. The performance is also compared with the one obtained by another method in terms of the integral absolute error.

Dynamometers are used to evaluate the real-world performances of drivetrains in various loading conditions. Due to its superior power density, high bandwidth, and design flexibility, a hydrostatic power-regenerative dynamometer is an ideal candidate for hydrostatic wind turbine transmission testing. A dynamometer can emulate the wind turbine rotor dynamics and allow the investigation of the performance of a unique hydrostatic drivetrain without actually building the physical system. The proposed dynamometer is an energy-efficient system with counter-intuitive control challenges. This paper presents the dynamics, control synthesis, and experimental validation of a power-regenerative hydrostatic dynamometer. A fourth-order non-linear model with three inputs was formulated for the dynamometer. The strength of input–output couplings was identified, and two different decoupling controllers were designed and implemented. During wind turbine testing, the synchronous generator turns at a constant speed and the system model is linear. A steady-state decoupling controller was developed for independent control of the drive and transmission. The implemented decoupling controller demonstrated a negligible change in rotor speed for a 40 bar step increase in pressure, but a 20 bar pressure spike for a 4 rpm step change in rotor speed. However, during starting and stopping, the synchronous generator speed is not constant, and the system model is nonlinear. Therefore, a steady-state decoupling controller will not work. Thus, a decentralized controller with feed-forward control and gain scheduling was designed and implemented. A reference command was designed to avoid cavitation, pressure spikes, and power flow reversal during start-up. The experimental results show precise tracking in steady-state and transient operations. The decentralized controller demonstrated a negligible change in rotor speed for a 40 bar step increase in pressure but a 100 bar pressure spike for a 4 rpm step increase in rotor speed. The pressure spike was reduced by 80 bar with the implementation of feed-forward gain. The proposed electro-hydro-mechanical system requires less power and has the potential to reduce energy expenditure by 50%.