Large-scale Interconnected Systems Research Articles

Predefined-time adaptive neural network decentralized control for large-scale interconnected systems with input hysteresis

Predefined-time adaptive neural network decentralized control for large-scale interconnected systems with input hysteresis

Event-triggered explorized IRL-based decentralized fault-tolerant guaranteed cost control for interconnected systems against actuator failures

This paper presents a novel data-based decentralized guaranteed cost (DGC) fault tolerant control (FTC) scheme for the large-scale systems subject to actuator faults and mismatched interconnection. First, the FTC issues of interconnected systems are converted into a series of near optimal event-triggered control (ETC) methods for isolated subsystems via constructing a modified performance index function of each subsystem. By means of adaptive dynamic programming (ADP) algorithm, the upper bound of performance index function of large-scale systems can be obtained by solving the Hamilton-Jacobi-Bellman (HJB) equation of each auxiliary subsystem. Second, according to the proposed ADP-based decentralized approach and utilizing the event-based synchronous integral reinforcement learning (IRL) algorithm, a model-free guaranteed cost (GC) FTC approach is developed for interconnected large-scale system which can relax the restriction on the condition that system functions must be known. Further, the ultimate uniformly bounded (UUB) stability of auxiliary subsystems can be proved according to the Lyapunov principle. Finally, the effectiveness of the proposed control method is verified by presenting the simulation results.

Decentralized Event-Triggered Tracking Control for Unmatched Interconnected Systems via Particle Swarm Optimization-Based Adaptive Dynamic Programming.

The problem of the large-scale interconnected system (LSIS) control is prevalent in practical engineering and is becoming increasingly complex. In this article, we propose a novel decentralized event-triggered tracking control (ETTC) strategy for a class of continuous-time nonlinear LSIS with unmatched interconnected terms and asymmetric input constraints. First, auxiliary subsystems are established to address the unmatched cross-linking terms. Next, the dynamics states of the tracking error and the exosystem are combined to construct a nominal augmented subsystem. By employing a nonquadratic performance function, the input-constrained decentralized tracking control problem is transformed into an optimal control problem for the nominal augmented subsystem. A group of independent parameters and event-triggered conditions are designed to save communication bandwidth and computational resources. Subsequently, the critic-only adaptive dynamic programming (ADP) method is used to solve the Hamilton-Jacobi-Bellman equation (HJBE) associated with the optimal control problem. To improve training success rate, the weights of the critic neural network (NN) are updated by introducing a particle swarm optimization algorithm (PSOA). The tracking error and the NN weights are proved to be uniformly ultimately bounded (UUB) under the proposed ETTC by using the Lyapunov extension theorem. Finally, the simulation example of an unmatched interconnected system is provided to verify the validity of the proposed decentralized method.

Non-Fragile Sampled Control Design for an Interconnected Large-Scale System via Wirtinger Inequality

A control design for a linear large-scale interconnected system composed of identical subsystems is presented in this paper. The control signal of all subsystems is sampled. For different subsystems, the sampling times are not identical. Nonetheless, it is assumed that a bound exists for the maximal sampling time. The control algorithm is designed using the Wirtinger inequality, and the non-fragile control law is proposed. The size of the linear matrix inequalities to be solved by the proposed control algorithm is independent of the number of subsystems composing the overall system. Hence, the algorithm is computationally effective. The results are illustrated by two examples. The first example graphically illustrates the function of the proposed algorithm while the second one compares with a method for stabilizing a large-scale system obtained earlier, thus illustrating the improved capabilities of the presented algorithm.

A new distributed robust H∞ control strategy for a class of uncertain interconnected large-scale time-delay systems subject to actuator saturation and disturbance

In the realm of large-scale systems, the complexity of controller design has long been exacerbated by the proliferation of decision variables and inherent conservatism. This study introduces a novel approach to address these challenges, presenting a new distributed robust controller design methodology tailored for large-scale systems grappling with disturbances, uncertainties, and actuator saturations. The primary objectives include reducing conservatism, minimizing decision variables, and significantly curtailing computation time. To surmount these hurdles, the research leverages descriptive and reciprocally convex methods, formulating the design procedure using linear matrix inequalities. This enables the adjustment of uncertain parameters and robust disturbance rejection, thereby ensuring stability in large-scale systems. Additionally, a feedback control law is proposed to accommodate saturation constraints and ensure the closed-loop system’s stability. Notably, the effectiveness of the proposed control scheme is demonstrated through the evaluation of a full-car active suspension system, which is partitioned into interconnected subsystems to a large-scale system. Comparative analyses underscore the superior performance and technical advancements offered by the proposed methodology over existing approaches.

Decentralized fuzzy DSC for uncertain large-scale interconnected switched systems in non-strict feedback form with input saturation

This paper demonstrates a fuzzy decentralized dynamic surface control (DSC) scheme for switched large-scale interconnected nonlinear systems under arbitrary switching, which contains non-strict feedback form and unknown input saturation uncertainties. An auxiliary design system is established to handled input saturation. Uncertainties of non-strict feedback form are learned by fuzzy logic systems (FLSs) approximators, DSC method is designed to conquer “explosion of complexity” inherented by repeated differential of virtute controller in backstepping approach. Ii is shown that based on common Lyapunov function (CLF) design and analysis scheme, all the closed-loop systems signals are uniformly ultimately bounded (UUB), simulation results are provided to demonstrate the effectiveness of this proposed strategy.

Observer-based control for large-scale interconnected systems with parameter uncertainty and application to wireless power transfer systems

In the work, the observer-based control is designed and analyzed for a class of large-scale interconnected systems subject to parameter uncertainty. In the beginning, we build a large-scale interconnected system with parameter uncertainty and apply this model to a multi-level wireless power transfer system. By using this modeling method, the order of multi-level wireless power transfer system is greatly deduced. In addition, the multi-level wireless power transfer system include coupling terms and uncertain parameters considered in the observer-based control law design. We earn sufficient conditions of this model stability for multi-level wireless power transfer systems under this control law through the Lyapunov stability theorem and Young’s inequality. The stability analysis method suggested in the work could also be adopted in other practical plants. At last, the correctness and availability of this suggested approach are verified through simulation results.

Event-based adaptive active disturbance rejection control for nonlinear large-scale systems with input delay

This paper explores the active disturbance rejection control (ADRC) issue for interconnected large-scale systems with unmeasured states, input delay and a total disturbance composed of unknown constrained external disturbances. An enhanced extended state observer is built via fuzzy logic systems to identify system uncertainties and states and keep restraining the total disturbance of uncertain systems. When the triggering condition is met, the tracking differentiator component of the ADRC is able to reduce the communication overhead by successfully applying the backstepping control approach and the dynamic event-triggered mechanism. Meanwhile, the integral compensation method eliminates the negative effect cased by the input delay. Furthermore, the developed decentralised fuzzy control scheme can ensure that all signals in the closed-loop systems are semiglobally uniformly ultimately bounded and Zeno behaviour does not occurs. Finally, an example is used to depict the validity of the control approach.

Distributed cyber attack detection and physical fault diagnosis for a class of interconnected large-scale systems

In this paper we focus on the distributed cyber attack detection and physical fault diagnosis problem for a class of interconnected large-scale systems (ILSSs). In the proposed scheme, apart from node measurement, edge measurement is also used to construct distributed Kalman filter to estimate the state of each subsystem. The gain matrices of Kalman filter are determined by minimizing the covariance of estimation error in the attack-free and fault-free case, which reduces the false alarm rate of cyber attack detection and physical fault diagnosis. Based on this filter, a bank of adjacent residual generators is constructed to characterize the influence of cyber attack on the edge measurement, and the Chi-square test is used to detect whether the received edge measurements are attacked. At the same time, a local residual generator is constructed for each subsystem to characterize the influence of physical faults on it, and the residual signal is evaluated by variance and directional residual, so as to make distributed fault detection and isolation of each subsystem. It is worth noting that at each step, each subsystem first performs attack detection on the received edge measurements, and then estimates its own state using the attack-free edge measurements and node measurement, which further improves the accuracy of fault detection and isolation. In addition, a sufficient condition that ensuring the mean square exponential boundedness of the estimation error is given. Finally, the proposed scheme is verified by an illustrative example.

Actuator fault detection and isolation in a class of nonlinear interconnected systems

In this paper, the problem of actuator fault detection and isolation is investigated for a class of nonlinear interconnected large-scale systems with modelling uncertainty and measurement noise, where each subsystem can have multiple inputs and multiple outputs (MIMO). The main contribution of this work is the derivation of a scheme that is able to diagnose single or multiple actuator faults in one or multiple subsystems. Each subsystem is monitored by a local diagnosis agent which contains the actuator fault detection module and the isolation module. The detection threshold in the fault detection module is generated through the use of a novel filtering technique, while the fault isolation module is realised by applying a reasoning-based decision logic based on a fault signature matrix. Fault propagation among subsystems is investigated and the results obtained allow for the identification of the subsystems that contain the faulty actuators. Finally, the effectiveness of the proposed actuator fault diagnosis method is demonstrated through a simulation example.

Data-Driven Optimal Distributed Fault Detection Based on Subspace Identification for Large-Scale Interconnected Systems

Data-Driven Optimal Distributed Fault Detection Based on Subspace Identification for Large-Scale Interconnected Systems

Sliding Mode-Based Distributed Trajectory Tracking Control of Four-body Train Systems

This paper considers the speed tracking of a four-body train system modelled mathematically based on Newton’s second law, which is described by a large-scale interconnected system with four subsystems. Uncertainties are included in the systems to represent the potential impacts on system performance caused by mechanical wear and external environmental changes. An adaptive sliding mode technique is employed to design a distributed control scheme to guarantee tracking accuracy. Coordinate transformations are introduced to transfer the model of train systems to a system in regular form to facilitate the design of the hyperplane and controllers. The Barbashin-Krasovskii theorem is employed to show the reachability of the hyperplane. In simulations, the Gaussian function is chosen as the desired signal, representing time-varying characteristics relevant to real-world situations, and the result demonstrates the feasibility of the proposed control strategy.

Decentralized and Distributed Control of Large-scale Interconnected Multi-Agent Systems in Prescribed Time

Decentralized and Distributed Control of Large-scale Interconnected Multi-Agent Systems in Prescribed Time

Fault detection and diagnosis using the dynamic network framework

A local model-based method for fault detection and diagnosis (FDD) in large-scale interconnected network systems is introduced, using models in a dynamic network framework. To this end, model validation methods are developed for validating single modules in a dynamic network, which are generalized from the classical auto- and cross-correlation tests for open- and closed-loop systems. Invalidation of the model can indicate the detection of a fault in the system. A fault diagnosis algorithm is developed that includes fault isolation and optimal placement of external excitation signals. Numerical illustrations demonstrate the method’s capability to detect a fault in a local module and isolate it within the entire network system.

Optimal Fault-Tolerant Control for Large-Scale Interconnected Systems With State Constraints

Optimal Fault-Tolerant Control for Large-Scale Interconnected Systems With State Constraints

$H_{2}$ Performance Analysis and Distributed $H_{2}$ Control of Interconnected Large-Scale Systems

This paper considers the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{2}$</tex-math></inline-formula> performance analysis and distributed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{2}$</tex-math></inline-formula> control problems of interconnected large-scale systems (LSSs). According to the developed space construction approach, both novel necessary and sufficient conditions are established to ensure the asymptotic stability and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{2}$</tex-math></inline-formula> performance of the studied LSSs. Next, these investigated results are utilized to derive some sufficient conditions for the existence of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{2}$</tex-math></inline-formula> distributed controllers. The desired distributed controller gains are constructed via the solutions of some developed linear matrix inequality conditions, which guarantee the stability and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{2}$</tex-math></inline-formula> performance of the closed-loop LSSs. Finally, three examples are introduced to show the superiority and validness of the proposed theoretical method.

Decentralized optimal control of large-scale partially unknown nonlinear mismatched interconnected systems based on dynamic event-triggered control

In this paper, a novel decentralized control method is proposed for nonlinear mismatched large-scale interconnected systems subjected to partially unknown dynamics by designing auxiliary control for each subsystem. It is demonstrated that the control sequence consisting of the optimal control policies of auxiliary control can stabilize the system asymptotically, leading to decentralized control of the large-scale system. An integral reinforcement learning (IRL) method is firstly proposed, replacing the traditional policy iterative algorithm to analyze the optimal control problem of each edge subsystem with partially unknown dynamics. After that, the edge-based dynamic event-triggered control algorithm is proposed based on the static event-triggered control method, and an internal dynamic variable characterized by a first-order filter is defined. A single critic neural network (NN) is then designed to learn the approximate optimal control strategy under the dynamic event-triggered mechanism adaptively. The stability analysis is proposed to demonstrate that the state of the event-based pulse system is ultimately uniformly bounded (UUB) and the Zeno behavior is eliminated successfully. Finally, the effectiveness of the proposed algorithm is verified by two simulation examples to realize decentralized control of mismatched large-scale systems.

Adaptive fuzzy output-Feedback control of switched large-Scale systems with fast time-Varying delay

In this paper, an adaptive fuzzy decentralized output-feedback control is developed for the uncertain switched large-scale interconnected nonlinear system, which contains fast time-varying delays and unknown nonconstant control coefficients. By introducing and proving a new lemma, an improved analysis method is given based on the Lyapunov-Krasovskii (LK) functional, and it gets rid of the dependence of LK functional design on the bound of the derivative of the delay. Immeasurable states are estimated by co-designing the decentralized state observer and the innovative compensation system, which eliminates a widely adopted but strict assumption that the unknown control coefficient must be constant. By comprehensively designing the state observer, the compensation system and LK functionals, a novel adaptive fuzzy decentralized output-feedback control law is proposed, and stability of the closed-loop system is guaranteed theoretically based on an improved average dwell time. Finally, the effectiveness is further verified by complete simulation experiments.

An improved robust distributed [formula omitted] control method for uncertain interconnected large-scale time-delayed systems

In modern industries, systems have become increasingly large-scale and complex, comprising multiple interconnected subsystems where the performance of each subsystem impacts the others. Ensuring stability and performance under uncertainties, external disturbances, and time delays is crucial for such systems. This paper proposes a new distributed control method that stabilizes a specific type of time-varying input-delayed large-scale system in the presence of uncertainties and external disturbances. The proposed method employs Jensen’s inequality to reduce the number of decision variables and uses reciprocally convex and descriptive methods to minimize conservatism and decrease computation time. The performance of the proposed method is evaluated on a full-car model with an active suspension system as a novel approach to controlling large-scale systems. This paper describes how to divide a large-scale full-car system into several interconnected subsystems, for the first time. The results indicate the potential of the proposed controller in enhancing the performance of the system in comparison with other previous control methods.

Decentralized $H_{\infty }$ Control for Switched Interconnected Large-Scale Systems: A Computationally Attractive Method

This article investigates the decentralized <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> controller design problems for switched interconnected large-scale systems (ILSSs). The designed decentralized controllers are dependent on the switching modes which can reduce the conservatism. Sufficient conditions are established for ensuring the asymptotic stability and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance of the studied switched ILSSs. Novel computationally attractive mode-dependent controller deign method is derived. The established controller design conditions eliminate the computationally expensive matrix inversion terms and are given in terms of linear matrix inequalities. Finally, the validness of the proposed decentralized controller design method is verified by the interconnected continuous stirred-tank reactor systems. Other three numerical examples are also performed to show the advantages and superiorities of the derived theoretical results.