Sampled-data Control Design Research Articles

Protocol-based secure guaranteed cost control of sampled-data T-S fuzzy system with denial-of-service attack and input saturation

This paper proposes a protocol-based secure guaranteed cost sampled-data controller design problem of Takagi-Sugeno (T-S) fuzzy system under denial-of-service (DoS) attack and input saturation. First, in the absence of an effective description for the characteristics of received signals on controller, a novel scheduling protocol is proposed according to the characteristics of the round-robin protocol and DoS attack, which can guarantee the specific sequence characteristic for control updates. Then, via introducing input delay approach and switched system modeling method, a time-delay switched system with fixed switching sequence is introduced to describe the considered system with DoS phenomenon. Moreover, some novel control criteria are presented to ensure the resulting closed-loop system reaches a required cost level under the obtained control law. And an optimization problem is proposed to compute the optimal upper of the specified cost level. Finally, a simulation example is presented to demonstrate the effectiveness of the algorithm.

Design of sampled-data controller for T–S fuzzy system with the refined fractional delayed-state and its applications

Design of sampled-data controller for T–S fuzzy system with the refined fractional delayed-state and its applications

Enhanced Results on Sampled-Data Synchronization for Chaotic Neural Networks With Actuator Saturation Using Parameterized Control.

This article investigates a novel sampled-data synchronization controller design method for chaotic neural networks (CNNs) with actuator saturation. The proposed method is based on a parameterization approach which reformulates the activation function as the weighted sum of matrices with the weighting functions. Also, controller gain matrices are combined by affinely transformed weighting functions. The enhanced stabilization criterion is formulated in terms of linear matrix inequalities (LMIs) based on the Lyapunov stability theory and weighting function's information. As shown in the comparison results of the bench marking example, the presented method much outperforms previous methods, and thus the enhancement of the proposed parameterized control is verified.

Design of fuzzy dissipative sampled-data control for nonlinear wind turbine systems with random packet losses and communication delays

Design of fuzzy dissipative sampled-data control for nonlinear wind turbine systems with random packet losses and communication delays

Memory sampled-data control design for attitude stabilization of uncertain spacecraft with randomly missing measurements

This paper focuses on stabilizing the attitude of the rigid spacecraft under the sampled-data control design technique with constant communication delay. The system dynamics with model uncertainty (perturbation) and missing measurements are considered. The aim is to design a desirable attitude control that ensures the stabilization of the rigid spacecraft with an optimal H∞ performance level. A novel Lyapunov–Krasovskii functional is developed, incorporating looped characteristics, for the proposed study on the rigid spacecraft model by developing relevant new terms. Making use of the Lyapunov function as well as free-matrix-based integral inequality, sufficient stability criteria are established to assure the stability of the rigid spacecraft model. Furthermore, the desired sampled-data control gain matrices are acquired through the solution of linear matrix inequalities, which guarantees the asymptotic stability of the rigid spacecraft model. Finally, the numerical simulation demonstrates the efficacy of the theoretical study proposed for the rigid spacecraft model.

Sampled-data controller synthesis using dissipative linear periodic jump-flow systems with design applications

In this paper, we will propose linear-matrix-inequality-based techniques for the design of sampled-data controllers that render the closed-loop system dissipative with respect to quadratic supply functions, which includes passivity and an upper-bound on the system’s H∞-norm as a special case. To arrive at these results, we model the sampled-data control system as a linear periodic jump-flow system, study dissipativity in terms of differential linear matrix inequalities (DLMIs) and then convert these DLMIs into a single linear matrix inequality. We will present three applications of these synthesis techniques: (1) passivity-based controller synthesis, as found in teleoperations, (2) input–output-response matching of a continuous-time filter with a discrete-time filter (by minimizing the H∞-norm of a generalized plant) and (3) a sampled-data controller redesign problem, where the objective is to find the best sampled-data controller, in the H∞-norm sense, for a given continuous-time controller. We will show that synthesizing sampled-data controllers leads to better closed-loop system behaviour than using a Tustin discretization of a continuous-time controller.

Sampled-Data Cooperative Adaptive Cruise Control for String-Stable Vehicle Platooning with Communication Delays: A Linear Matrix Inequality Approach

This study aims to propose a sampled-data control technique, utilizing a linear matrix inequality (LMI) approach, to achieve string-stable vehicle platooning in a cooperative adaptive cruise control (CACC) system with communication delays. To do this, a decentralized sampled-data controller design technique that combines one controller using sensor measurements and another one utilizing vehicle-to-vehicle (V2V) communication, ensuring both individual and string stability, is proposed first. Next, a memory sampled-data control (MSC) approach is presented to account for transmission delays in V2V communication. Additionally, an improved Lyapunov–Krasovskii functional (LKF) is presented to improve computational complexity and sampling performance. The design conditions are formulated as linear matrix inequalities (LMIs) in the time domain, facilitating efficient stability analysis and optimization. Finally, vehicle platooning simulations are provided to validate the effectiveness and feasibility of the proposed technique.

Interval Type-2 Fuzzy-Model-Based Sampled-Data Control of an AUV Depth System with Input Saturation

This paper proposes a sampled-data fuzzy controller design technique for an autonomous underwater vehicle (AUV) depth system represented by an interval type-2 (IT-2) fuzzy model, considering input saturation. In the Takagi–Sugeno (T–S) fuzzy model of an AUV depth system, surge velocity is chosen as a premise variable. To address the associated uncertainty with this variable, we employ the IT-2 fuzzy modeling technique. Also, the controller proposed in this paper utilizes time-varying gains, ensuring superior exponential stability compared with traditional fixed gain approaches. Furthermore, a membership function-dependent (MFD) H∞ criterion is employed to enhance robustness for each subsystem individually. Taking into account the mentioned aspects, the controller design condition is derived in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed method is validated through simulation examples.

An improved sampled-data control for a nonlinear dynamic positioning ship with Takagi-Sugeno fuzzy model.

This article considered the sampled-data control issue for a dynamic positioning ship (DPS) with the Takagi-Sugeno (T-S) fuzzy model. By introducing new useful terms such as second-order term of time, an improved Lyapunov-Krasovskii function (LKF) was constructed. Additionally, the reciprocally convex method is introduced to bound the derivative of LKF. According to the constructed LKF, the sampling information during the whole sampling period was fully utilized, and less conservatism was obtained. Then, the stability condition, robust performance, mode uncertainty and sampled-data controller design were analyzed by means of the linear matrix inequality (LMI). Finally, an example was given to demonstrate the effectiveness of the proposed method.

Novel criteria of sampled-data synchronization controller design for gated recurrent unit neural networks under mismatched parameters

Synchronization between neural networks (NNs) has been intensively investigated to analyze stability, convergence properties, neuronal behaviors and response to various inputs. However, synchronization techniques of NNs with gated recurrent units (GRUs) have not been provided until now due to their complicated nonlinearity. In this paper, we address the sampled-data synchronization problems of GRUs for the first time, and propose controller design methods using discretely sampled control inputs to synchronize master and slave GRUs. The master and slave GRUs are mathematically modeled as a linear parameter varying (LPV) system in which the parameter of the slave GRUs is constructed independently of the master GRUs. This distinctive modeling feature provides flexibility to extend the existing master and slave NNs into a more general structure. Indeed, the sampled-data synchronization can be achieved by formulating the design condition in terms of linear matrix inequalities (LMIs). The novel sampled-data synchronization criteria are devised by combining the H∞ controller design with the looped-functional approach. The synthesized synchronization controllers guarantee not only asymptotic stability of the synchronization error system with aperiodic sampling, but also provides a satisfactory H∞ control performance. Moreover, the communication efficiency is improved by using the proposed method in which the sampled-data synchronization controller is combined with the event-triggered mechanism. Finally, the numerical example validates the proposed theoretical contributions via simulation results.

Fuzzy Memory Sampled-Data Controller Design for PMSG-Based WECS With Stochastic Packet Dropouts

The fuzzy memory sampled-data control problem for permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS) with stochastic packet dropouts is discussed in this paper. To do this, the PMSG-based WECS dynamics are firstly modelled by a set of fuzzy IF-THEN rules of the Takagi–Sugeno (T–S) fuzzy model because of high nonlinearity. And then, to minimize design conservatism, a suitable augmented looped-type Lyapunov functional along with a novel integral inequality is established by using the sampling mode information with signal transmission delay. Further, a fuzzy memory-based sampled-data controller is designed to obtain the asymptotic stability condition under the circumstances of packet dropouts, and simultaneously, disturbance reduction is confirmed. Thereafter, the associated fuzzy controller gains can be computed by solving a number of linear matrix inequalities (LMIs). Finally, the application of the suggested method to a real-world system is proved using PMSG-based WECS, and the mathematical Rossler's system demonstrates the effectiveness and superiority of the proposed technique over the existing method.

Sampled-data state feedback control design for evolutionary threshold public goods games on coupled networks

Sampled-data state feedback control design for evolutionary threshold public goods games on coupled networks

Control for Stochastic Singular Systems With Time-Varying Delays via Sampled-Data Controller.

In this article, control for stochastic singular time-varying delay systems under arbitrarily variable samplings is addressed via designing a sampled-data controller. The first and foremost, a novel time-dependent discontinuous Lyapunov-Krasovskii (L-K) functional is built, which takes good advantage of the factual sampling pattern's available properties. Then, based on the refined input delay method by utilizing the constructed time-dependent L-K functional, the free-weighting matrix method, and the auxiliary vector function approach are adopted to develop conditions ensuring the stochastic admissibility for the studied stochastic singular systems with time-varying delays. On the basis of the derived conditions, the sampled-data control issue is tackled, and an unambiguous expression for the sampled-data controller design method is obtained. Finally, simulation examples manifest that our proposed results are correct and effective.

Improved Sampled-Data Controller Design for T–S Fuzzy Systems with an Adaptive Event-Triggered Mechanism

Improved Sampled-Data Controller Design for T–S Fuzzy Systems with an Adaptive Event-Triggered Mechanism

Improved Reachable Set Estimation and Aperiodic Sampled-Data for T–S Fuzzy Markovian Jump Systems

In this article, the problem of reachable set estimation (RSE) and the design of aperiodic sampled-data controller for Takagi–Sugeno fuzzy Markovian jump systems (T–S FMJSs) with unit-energy bounded disturbance (UEBD) and unit-peak bounded disturbance (UPBD) inputs are taken into consideration. First, sufficient conditions that all states of the T–S FMJSs are encompassed by ellipsoids under zero initial conditions are acquired via constructing a mode-dependent two-sided loop-based Lyapunov function and applying a linear matrix inequality approach. Second, the RSE is taken into account in the design of the state feedback aperiodic sampled-data controller with the aim that the resulting ellipsoid encompasses the reachable set of the closed-loop system. Finally, a nonlinear mass-spring model and a tunnel diode circuit model demonstrate the efficiency of the presented approach. In addition, this method is able to obtain a larger sampled-data period than other literature, thus saving bandwidth and reducing communication resources.

Secure P2P Nonfragile Sampled-Data Controller Design for Nonlinear Networked System under Sensor Saturation and DoS Attack

Secure P2P Nonfragile Sampled-Data Controller Design for Nonlinear Networked System under Sensor Saturation and DoS Attack

Stabilization of PMSG-based wind turbine systems with sampling information: Dynamic delay partition method

This paper addresses the novel stabilization criteria for a nonlinear permanent magnet synchronous generator (PMSG)-based wind turbine systems (WTS) with sampled-data information, subject to the uncertainty and controller gain variations. In this regard, the nonlinearity in PMSG-based WTS is conferred by the Takagi–Sugeno (T–S) fuzzy systems. Next, by employing the full advantages of the variable characteristic related to the sampling pattern, a novel looped-type asymmetric augmented Lyapunov-Krasovskii functional (LKF) is developed. Then, the dynamic delay partition method is the first time to be applied for the non-fragile sampled-data control design of proposed T–S fuzzy systems. Also, the less conservativeness stabilization criteria for T–S fuzzy systems are obtained in the form of linear matrix inequality. In the end, the numerical examples confirm the applicability and efficiency of the presented results.

Asynchronous Sampled-Data Controller Design for Switched Markov Jump Systems and Its Applications

This article is dedicated to design asynchronous aperiodic sampled-data controller for a class of Markov jump systems with switching transition rate. The sampling controller corresponding switching transition rate matrix mode is not synchronized with the system corresponding switching transition rate matrix mode due to the possible switching of the transfer rate matrix in the sampling interval. With the help of T–S fuzzy models, the state-space representation of the system is turned into a fuzzy Itô stochastic switched Markov jump systems. By constructing novel Lyapunov functionals, mean square exponential stability criteria, and dissipativity criteria are presented. Furthermore, an asynchronous aperiodic sampled-data controller is designed for fuzzy Itô stochastic Markov jump systems. At last, by fuzzing the nonlinear tunnel diode circuit model and nonlinear mass-spring-damper mechanical model, the effectiveness and lower conservativeness of the proposed method are illustrated.

Design and experimentation of sampled-data controller in T-S fuzzy systems with input saturation through the use of linear switching methods

<abstract><p>In this study, the stability and stabilization analyses are discussed for Takagi-Sugeno (T-S) fuzzy systems with input saturation. A fuzzy-based sampled-data control is designed to stabilize the T-S fuzzy systems. Based on the Lyapunov method and some integral inequality techniques, a set of sufficient conditions is obtained as linear matrix inequality (LMI) constraints to guarantee the asymptotic stability of the considered system. In this process, the linear switching method is utilized to design a controller that is dependent on the membership function, and an integral inequality is utilized. Additionally, determination of the controller parameters is achieved by resolving a series of LMI constraints. The effectiveness of these criteria is demonstrated through a real system that is modeled by the T-S system.</p></abstract>

Reliable Fuzzy Sampled-Data Control for Nonlinear Suspension Systems Against Actuator Faults

This article investigates the reliable fuzzy sampled-data control issue of nonlinear vehicle suspension systems subject to actuator faults. Considering the high nonlinear characteristics in the springs and the shock absorbers, the Takagi–Sugeno fuzzy method is utilized to describe the nonlinear suspension system. To deal with the discrete phenomenon of nonuniform sampling, an input-delay is employed to convert the continuous-discrete suspension system into a continuous-time form. Motivated by the above system model, a Lyapunov functional candidate is employed to obtain sufficient conditions that can meet system stability and performance requirements simultaneously. Furthermore, a novel two-step optimization algorithm is proposed for the sampled-data controller design in the structure of output feedback. Finally, experimental tests are implemented via an active suspension test rig, and the test results illustrate that the proposed method contributes greatly to improve the ride comfort, handling performance, and road holding capability simultaneously.