Decentralized Output Feedback Control Research Articles

Dynamic Event-Triggered Adaptive Neural Network Decentralized Output-Feedback Control for Nonlinear Interconnected Systems With Hybrid Cyber Attacks and Its Application

Dynamic Event-Triggered Adaptive Neural Network Decentralized Output-Feedback Control for Nonlinear Interconnected Systems With Hybrid Cyber Attacks and Its Application

Predictor-Based Decentralized Event-Triggered Secure Control for Nonlinear Cyber-Physical Systems Under Replay Attacks and Time Delay

This paper investigates the problem of predictor-based decentralized event-triggered secure control for nonlinear cyber-physical systems (CPSs) subject to replay attacks and time delay. To overcome the limitation of the network bandwidth, a periodic decentralized event-triggered scheme (PDETS) is designed for non-strict feedback nonlinear CPSs in the presence of replay attacks. Then, decentralized output feedback controllers are constructed by designing predictor-based observers to attenuate the influences of replay attacks and time delay. Based on the proposed new framework, the global exponential stability (GES) of the resulting nonlinear CPSs can be guaranteed. Finally, two application examples verify the effectiveness of the proposed method.

Decentralized Output-Feedback Control With Asymmetric One-Step Delayed Information

This paper considers the decentralized LQG control problem for discrete-time decentralized system controlled by two players. In this scenario, player 1 shares a unit delayed observations and control inputs with the controller of player 2, whereas due to the limiting capacity, the controller of player 1 cannot obtain the observations and control inputs of player 2 which leads to the asymmetric one-step delay information. It should be emphasized that this structure makes the classical separation principle fail. Under the assumption of linear control strategies, we derive the optimal estimators based on asymmetric information. In virtue of the Pontryagin's maximum principle, the optimal explicit decentralized controllers are obtained by solving the forward and backward stochastic difference equations (FBSDEs). It is noted that the control gains are coupled with the estimation gains. Moreover, the estimation gains satisfy the forward Riccati equations and the control gains follow the backward Riccati equations which cannot be solved simultaneously. To this end, we present iterative solutions to the coupled forward and backward Riccati equations. Finally, a sufficient condition for the stabilization problem is given in terms of the coupled algebraic Riccati equations. Numerical examples are illustrated to show the effectiveness of the proposed algorithm.

Adaptive Fuzzy Decentralized Output-Feedback Control of Large-Scale Systems With Sensor Faults: A Multichannel Asynchronous Triggering Approach

This paper proposes an adaptive fuzzy decentralized output feedback control scheme for large-scale systems with multichannel asynchronous event-triggering. Uncertain system dynamics, unknown interconnections and time-varying sensor faults are handled simultaneously, even though only the corrupted measured local output is available for the design procedure. First, local state estimation filters are designed to estimate the unmeasured states. Then, considering that the resource-limited communication and computation may exist in all three types of channels including state estimation filter-to-controller channel, parameter estimator-to-controller channel and controller-to-actuator channel, an asynchronous event-triggering framework with time-varying triggering threshold is developed for multiple channels to release the communication and computation burden. Compared with the existing synchronous triggering mechanism, the proposed asynchronous one has several advantages: 1) the redundant signal transmission is reduced, 2) the triggering conditions for different channels are uncorrelated, which enables the designer to adjust the signal transmission frequency of each channel independently, and 3) the robustness could be improved in the face of noise as ideal synchronous triggering is not easy to be achieved in practice. In addition, both gain and bias faults, which are allowed to be unknown and time-varying, are covered in a unified sensor fault model. It is proved that, with the proposed control scheme, all the closed-loop signals are semi-globally uniformly ultimately bounded and the output tracking error converges into an adjustable residual set without Zeno behavior. Finally, simulation and comparison results illustrate the effectiveness and advantages of the proposed control scheme.

Distributed optimal coordination of uncertain nonlinear multi‐agent systems over unbalanced directed networks via output feedback

AbstractIn this article, a novel observer‐based output feedback control approach is proposed to address the distributed optimal coordination problem of uncertain nonlinear multi‐agent systems in the normal form over unbalanced directed graphs. The main challenges of the concerned problem lie in unbalanced directed graphs and nonlinearities of multi‐agent systems with their agent states not available for feedback control. Based on a two‐layer controller structure, a distributed optimal coordinator is first designed to convert the considered problem into a reference‐tracking problem. Then a decentralized output feedback controller is developed to stabilize the resulting augmented system. A high‐gain observer is exploited in controller design to estimate the agent states in the presence of uncertainties and disturbances so that the proposed controller relies only on agent outputs. The semi‐global convergence of the agent outputs toward the optimal solution that minimizes the sum of all local cost functions is proved under standard assumptions. A key feature of the obtained results is that the nonlinear agents under consideration are only required to be locally Lipschitz and possess globally asymptotically stable and locally exponentially stable zero dynamics.

Event-triggered adaptive decentralised control of interconnected nonlinear systems with Bouc-Wen hysteresis input

ABSTRACT This article presents an event-based adaptive decentralised output feedback control scheme for interconnected systems with Bouc-Wen hysteresis and unmeasured system states. To reduce some unnecessary data transmissions, a novel dynamic threshold adjustable event-triggering mechanism is proposed. In contrast with the traditional static threshold event-triggering mechanism, communication efficiency is greatly enhanced. Then, a neural networks-based observer is constructed to address the problem of unmeasured states, and the dynamic surface control method is used to address the ‘explosion of complexity’ that comes up when traditional backstepping design processes are used. Meanwhile, the Nussbaum function is introduced to eliminate the effect of unknown hysteresis. By resorting to the Lyapunov stability theory, it can be verified that all signals in the close-loop system are uniformly ultimately bounded. Finally, a simulation example is given to verify the effectiveness of the developed control scheme.

An Event-Triggered Predefined Time Decentralized Output Feedback Fuzzy Adaptive Control Method for Interconnected Systems

This article investigates the event-triggered predefined time output feedback control design problem for nonlinear interconnected systems with nonstrict feedback control structures. Compared with the existing event-triggered output feedback control design schemes, the most significant contribution of this article is that the system stability time can be preset directly. Fuzzy logic systems (FLSs) and FLSs-based state observer deal with unknown nonlinear dynamics and unmeasured states. Combining with dynamic surface control technology and event-triggered mechanism based on switching threshold strategy, an event-triggered predefined time decentralized output feedback control method is proposed, in which a predefined time filter is designed to solve the computational complexity problem. In addition, the algebraic loop problem and control singular problem are also solved, respectively, by applying the property of fuzzy basis function and L’Hospital’s rule. Utilizing the predefined time Lyapunov stability theory, the system stability analysis is given. Finally, the effectiveness and practicability of the proposed control method are verified by practical system simulation cases.

A Characterization of approximate decentralized fixed modes of time‐delay systems

AbstractThe concept of decentralized fixed mode (DFM) is crucial in determining the output feedback stabilizability by linear time‐invariant (LTI) decentralized controllers. However, in some cases, although a system has no DFMs, some of its modes may be very close to being fixed. It is thus important to characterize these modes, which are called approximate DFMs (ADFMs). In this paper, the characterization of ADFMs is discussed for LTI neutral (possibly descriptor‐type) time‐delay systems under static and dynamic decentralized output feedback control laws, and a mode mobility measure is proposed to provide quantitative information about ADFMs. To analytically compare the proposed measure, some of the commonly used quantitative measures for the characterization of ADFMs of finite‐dimensional systems have also been extended to the considered type of systems. The herein proposed approach allows multiple time delays and does not require additional expansions or preliminaries for multi‐input multi‐output systems, like some other commonly used methods. Thus, characterization with this measure, in general, requires less computational load, while it can provide more explicit information about the controller effort than the other considered measures.

Decentralized finite‐time control for a class of large‐scale systems with symmetrically interconnected subsystems

AbstractThe finite‐time stability (FTS) of a symmetrically interconnected system is studied under the consideration of utilizing the system structural properties to reduce the complexity of analysis. The FTS of this kind of large‐scale system can be guaranteed by that of two lower dimensional systems. The concept of mixed stability, taking care of both transient and steady‐state performances of a system, is introduced. Based on the FTS analysis, a decentralized finite‐time controller via state feedback is given to stabilize the large‐scale system. Meanwhile, an observer‐based decentralized output feedback controller is provided to make the closed‐loop system finite‐time stable. The FTS conditions and related decentralized stabilization controller parameters are both derived from solving some differential or algebraic linear matrix inequalities.

Networked scheduling for decentralized load frequency control

This paper investigates the scheduling process for multi-area interconnected power systems under shared but band-limited networks and decentralized load frequency controllers. To cope with sub-area information and avoid node collision of large-scale power systems, round-robin and try-once-discard scheduling are used to schedule sampling data among different sub-grids. Different from existing decentralized load frequency control methods, this paper studies multi-packet transmission scheme and introduces scheduling protocols to deal with multi-node collision. Considering the scheduling process and decentralized load frequency controllers, an impulsive power system closed-loop model is well established. Furthermore, sufficient stabilization criteria are derived to obtain decentralized output feedback controller gains and scheduling protocol parameters. Under the designed decentralized output feedback controllers, the prescribed system performances have been achieved. Finally, a three-area power system example is used to verify the effectiveness of the proposed scheduling method.

Global decentralized control for uncertain large-scale feedforward nonlinear time-delay systems via output feedback

Abstract In this paper, the problem of global decentralized output feedback control is addressed for a class of large-scale nonlinear systems with zero dynamics and unknown time-varying delay. System disturbance nonlinearities are subject to feedforward growth restrictions with unknown growth rate. In the spirit of dynamic scaling change technique, a novel pair of time-varying-gain observer and controller is proposed. Compared with the existing results, the controller proposed is capable of handling the difficulties caused by the zero-dynamics, the uncertainties and the unknown time-varying delay. With the help of the Razumikhin theorem, it is shown that the closed-loop states asymptotically converge to zero. Finally, the effectiveness of the proposed control scheme is illustrated by a numerical example.

Sampled observer-based adaptive decentralized control for strict-feedback interconnected nonlinear systems

This paper investigates the decentralized tracking control problem for a class of strict-feedback interconnected nonlinear systems with unknown parameters, where the system states are unmeasurable and the interconnections are unknown. Different from the existing results, where the output is available all the time, we consider the case that the output is only available at the sampled instants, which means the failure of existing methods. By introducing a kind of sampled observer for each subsystem, the system states and unknown parameters are jointly estimated. Based on which, a totally decentralized output feedback control scheme is developed to achieve the desired tracking performance by applying backstepping technique, where a compensation mechanism is utilized to address the unknown interconnections from other subsystems. Subsequently, by using Lyapunov stability theory, it is proved that all the signals in the closed-loop system are bounded and the tracking errors converge to an adjustable neighbourhood of the origin. Finally, an example is used to illustrate the effectiveness of the proposed method.

Adaptive Fuzzy Decentralized Sampled-Data Control for Large-Scale Nonlinear Systems

This article proposes a sampled-data adaptive fuzzy decentralized output feedback control method for the uncertain nonstrict feedback large-scale interconnected systems whose nonlinear functions are completely unknown and whose states are unavailable for control design. With the help of fuzzy logical systems in identifying the unknown nonlinear functions, and by considering the sampling strategy, a novel sampled-data nonlinear state observer has been designed to approximate the immeasurable state variables, which only contains the output sampling information of the system to be controlled. Furthermore, to avoid the problem of “explosion of complexity” caused by the frequently using the derivative of the virtual controller, the nonlinear filter has been considered under the strategy of the sampled data. Based on Lyapunov theory, a sampled-data adaptive fuzzy decentralized output feedback backstepping control strategy was proposed under the framework of recursive design and sampled-data strategy. The designed sampled-data controller is able to guarantee that all closed-loop signals are semiglobally uniformly ultimately bounded. Two simulation examples are eventually provided to validate the effectiveness of the theoretical findings.

Analysis, planning and control for cooperative transportation of tethered multi-rotor UAVs

The calculation of available wrench set of tethered multi-rotor UAVs is more challenging than that of the traditional cable-driven parallel robots (CDPRs) with fixed anchor points, due to the bounded thrust, motion acceleration and external disturbance acting on multi-rotor unmanned aerial vehicles (UAVs). To our best knowledge, this is the first work to investigate the dynamic available wrench set. We define an index called capacity margin to evaluate the robustness of the quasi-static motion for different system configurations and to represent the available maximum acceleration of the payload. Moreover, the feasible trajectories of multi-rotor UAVs are optimized using a tension distribution algorithm to accomplish the manipulation of the payload. Without the need of centralized ground control station, payload states and UAVs' velocity information, a decentralized output feedback control based on fixed-time extended state observer (ESO) is developed for the group of multi-rotor UAVs. The rigorous proof of stability of the closed-loop system is conducted. Finally, numerical simulations and comparative experiments are demonstrated to validate the proposed tension distribution algorithm and control strategy.

Synchronization via output feedback for multi-agent singularly perturbed systems with guaranteed cost

This paper focuses on the problem of designing a decentralized output feedback control strategy for synchronization of homogeneous multi-agent systems with global performance guarantees. The agents under investigation are described as linear singularly perturbed dynamics representing a wide class of physical systems characterized by processes evolving on two time-scales. The collaborative decentralized control is achieved using only output information from neighboring agents and considering that the only available graph information consists in its connectivity, that is, there is no centralized information related to the interconnection network structure. As methodology, the synchronization problem is rewritten as a dynamic output feedback robust stabilization of a singularly perturbed uncertain linear system with guaranteed cost. We show that these problems can be solved by using convex conditions expressed by LMIs and by decoupling the slow and fast dynamics. As an advantage, the fast dynamic matrix can be singular (nonstandard systems) and unstable. The proposed conditions circumvent some drawbacks of the existing works on this topic by providing a dynamic controller that does not depend on the singular parameter or by allowing the design of slow controllers when the fast system is stable. Numerical examples are presented to demonstrate the effectiveness of the proposed protocol and design method.

Adaptive Decentralized Output-Feedback Control Dealing With Static/Dynamic Interactions and Different-Unknown Subsystem Control Directions

In this article, we present an adaptive decentralized control scheme for a class of interconnected uncertain systems with subsystems having different yet unknown control directions and involving static nonlinear interactions as well as input and output dynamic interactions. A new form of K-filters is designed for each subsystem, and only local information is employed to generate control signals. A new Nussbaum-type function is developed with a key property that allows for the quantification of the interconnections among multiple Nussbaum-type functions for the subsystems with different control directions in a single inequality. By using appropriately chosen Lyapunov functions, global stability of the resulting closed-loop system is rigorously established. Simulation results are included to demonstrate the effectiveness of the proposed methodology.

Adaptive Dynamic Surface Decentralized Output Feedback Control for Switched Nonstrict Feedback Large-Scale Systems with Unknown Dead Zones

This paper investigates a novel adaptive output feedback decentralized control scheme for switched nonstrict feedback large-scale systems with unknown dead zones. A decentralized linear state observer is designed to estimate the unmeasurable states of subsystems. The dead zone inverse technique is used to compensate the effect of the unknown dead zone. A variable separation approach is applied to deal with the nonstrict feedback problem. Moreover, dynamic surface control and minimal parameter learning technology are adopted to reduce the computation burden. The proof of stability and the arbitrary switching are obtained by the common Lyapunov method. Finally, simulation results are given to show the effectiveness of the proposed control scheme.

Decentralized finite-time control for linear interconnected fractional-order systems with input saturation

This paper investigates decentralized finite-time boundedness and control problems for a linear interconnected fractional-order system with input saturation. By Lyapunov function, generalized Gronwall inequality, and fractional-order Caputo derivative inequality, sufficient conditions for finite-time boundedness of the linear interconnected fractional-order system are established. Both the decentralized state feedback controller and the decentralized output feedback controller are designed to guarantee the finite-time boundedness of the closed-loop system, and the seeking methods of controller gains are given by solving linear matrix inequalities. Finally, two simulation examples are employed to illustrate the effectiveness of the obtained results.

Global decentralized output feedback control for interconnected time delay systems with saturated PI hysteresis

In this paper, a global decentralized adaptive output feedback control is proposed for a class of nonlinear interconnected time delay systems, in which each subsystem covers unknown parameters, the unmeasured states dependent nonlinearities, and unknown saturated PI hysteresis. By constructing modified dynamic high-gain observers, together with backstepping technique, the unmeasured states dependent nonlinearities that fail to match global Lipschitz condition can be well disposed and global stability of the overall closed-loop system is obtained. With the aid of a new adaptive law, the restrictive assumption requiring known bounds of the time-varying delays in the existing literature is removed. Furthermore, based on the prescribed performance technique, it can be proved that both steady state and prespecified transient tracking performance are able to be guaranteed.

Event-Triggered Security Output Feedback Control for Networked Interconnected Systems Subject to Cyber-Attacks

This article studies the security of networked interconnected systems (NISs) subject to cyber-attacks based on a new event-triggered mechanism (ETM). NISs with spatially distributed subsystems are vulnerable to cyber-attacks. With a new concept of security control, attention is focused on designing a novel ETM together with a decentralized output feedback control (DOFC) scheme such that the NIS subject to cyber-attacks is stable in secure sense. Under the proposed ETM, the average data-releasing rate over the whole operating period can be extremely decreased, thereby reducing the burden of network bandwidth, computation, and battery-supply. Moreover, during the system with external disturbance or attack on the communication network, more transmission-events can be generated than other periods. As a result, the desired control performance can be achieved. By using stochastic analysis techniques and Lyapunov stability theory, sufficient conditions are derived to obtain both the controller gains and the parameters of the ETM. Numerical simulation of chemical reactor systems is given to illustrate the advantages and effectiveness of the proposed theories and design techniques.