Finite-time resilient decentralized control for interconnected impulsive switched systems with neutral delay

This paper is concerned with the problem of finite-time control for a class of interconnected impulsive switched systems with neutral delay in which the time-varying delay appears in both the state and the state derivative. The concepts of finite-time boundedness and finite-time stability are respectively extended to interconnected impulsive switched systems with neutral delay for the first time. By applying the average dwell time method, sufficient conditions are first derived to cope with the problem of finite-time boundedness and finite-time stability for interconnected impulsive switched systems with neutral delay. In addition, the purpose of finite-time resilient decentralized control is to construct a resilient decentralized state-feedback controller such that the closed-loop system is finite-time bounded and finite-time stable. All the conditions are formulated in terms of linear matrix inequalities to ensure finite-time boundedness and finite-time stability of the given system. Finally, an example is presented to illustrate the effectiveness of the proposed approach.     

Takagi–Sugeno fuzzy model based robust dissipative control for uncertain flexible spacecraft with saturated time-delay input

In this paper, the problem of robust dissipative control is investigated for uncertain flexible spacecraft based on Takagi–Sugeno (T–S) fuzzy model with saturated time-delay input. Different from most existing strategies, T–S fuzzy approximation approach is used to model the nonlinear dynamics of flexible spacecraft. Simultaneously, the physical constraints of system, like input delay, input saturation, and parameter uncertainties, are also taken care of in the fuzzy model. By employing Lyapunov–Krasovskii method and convex optimization technique, a novel robust controller is proposed to implement rest-to-rest attitude maneuver for flexible spacecraft, and the guaranteed dissipative performance enables the uncertain closed-loop system to reject the influence of elastic vibrations and external disturbances. Finally, an illustrative design example integrated with simulation results are provided to confirm the applicability and merits of the developed control strategy.     

Indirect predictive type-2 fuzzy neural network controller for a class of nonlinear input - delay systems

In this paper a new indirect type-2 fuzzy neural network predictive (T2FNNP) controller has been proposed for a class of nonlinear systems with input-delay in presence of unknown disturbance and uncertainties. In this method, the predictor has been utilized to estimate the future state variables of the controlled system to compensate for the time-varying delay. The T2FNN is used to estimate some unknown nonlinear functions to construct the controller. By introducing a new adaptive compensator for the predictor and controller, the effects of the external disturbance, estimation errors of the unknown nonlinear functions, and future sate estimation errors have been eliminated. In the proposed method, using an appropriate Lyapunov function, the stability analysis as well as the adaptation laws is carried out for the T2FNN parameters in a way that all the signals in the closed-loop system remain bounded and the tracking error converges to zero asymptotically. Moreover, compared to the related existence predictive controllers, as the number of T2FNN estimators are reduced, the computation time in the online applications decreases. In the proposed method, T2FNN is used due to its ability to effectively model uncertainties, which may exist in the rules and data measured by the sensors. The proposed T2FNNP controller is applied to a nonlinear inverted pendulum and single link robot manipulator systems with input time-varying delay and compared with a type-1 fuzzy sliding predictive (T1FSP) controller. Simulation results indicate the efficiency of the proposed T2FNNP controller.     

Finite time stability and controller design for nonlinear impulsive sampled-data systems with applications

This paper investigates the finite time stability (FTS) for nonlinear impulsive sampled-data systems. By constructing an appropriated Lyapunov function and employing average impulsive interval (AII) method, some FTS criteria for the nonlinear impulsive sampled-data systems are derived in terms of linear matrix inequalities (LMIs), which can be easily verified via the LMI toolbox. The hybrid controller including sampled-data controller and impulsive controller is designed via the established LMIs. Moreover, the impulse effect considered in this paper including stabilizing impulse and destabilizing impulse. Our developed results are less conservative than the recent work in the literature. Finally, two numerical examples are provided to show the applications of the proposed criteria.     

H∞ output-feedback fuzzy proportional-integral control of fully delayed input/output systems

This paper presents the output-feedback fuzzy proportional-integral (PI) controller design for uncertain nonlinear systems with both fully delayed input and output. Based on the Takagi–Sugeno (T–S) fuzzy model representation, the output-feedback PI control is realized via parallel distributed PI compensation and novel LMI gain design. Although the T–S fuzzy PI controller is simple, asymptotic output regulation is assured to overcome the effect of uncertainty, state delay, and full input/output delays. When considering disturbance and measurement noise, the control performance is achieved by robust gain design. Furthermore, state observers and bilinear matrix inequality conditions are removed in this paper. Finally, time-delay Chua׳s circuit system and a continuous-time stirred tank reactor are taken as applications to show the expected performance.     

A new robust control for minirotorcraft unmanned aerial vehicles

This paper presents a new robust control based on finite-time Lyapunov stability controller and proved with backstepping method for the position and the attitude of a small rotorcraft unmanned aerial vehicle subjected to bounded uncertainties and disturbances. The dynamical motion equations are obtained by the Newton–Euler formalism. The proposed controller combines the advantage of the backstepping approach with finite-time convergence techniques to generate a control laws to guarantee the faster convergence of the state variables to their desired values in short time and compensate for the bounded disturbances. A formal proof of the closed-loop stability and finite-time convergence of tracking errors is derived using the Lyapunov function technique. Simulation results are presented to corroborate the effectiveness and the robustness of the proposed control method.     

Resilient guaranteed cost control for uncertain T–S fuzzy systems with time-varying delays and Markov jump parameters

This paper aims to investigate the problem of resilient guaranteed cost control for uncertain Takagi–Sugeno fuzzy systems with Markov jump parameters and time-varying delay. A resilient mode-dependent fuzzy controller is designed and a weak sufficient condition is developed to ensure that the resulting closed-loop system is robust almost surely asymptotically stable with guaranteed cost index not exceeding the specified upper bound. Subsequently, the controller gain and upper bound of the guaranteed cost index can be obtained by solving a set of linear matrix inequalities. Finally, numerical and practical examples of the single-link robot arm system are provided to demonstrate the performance of the proposed approach.     

Time-discretization of nonlinear systems with delayed multi-input using Taylor series

This study proposes a new scheme for the sampled-data representation of nonlinear systems with time-delayed multi-input. The proposed scheme is based on the Taylor-series expansion and zero-order hold assumption. The mathematical structure of a new discretization scheme is explored. On the basis of this structure, the sampled-data representation of nonlinear systems including time-delay is derived. The new scheme is applied to nonlinear systems with two inputs and then the delayed multi-input general equation is derived. The resulting time-discretization provides a finite-dimensional representation of nonlinear control systems with time-delay enabling existing controller design techniques to be applied to them. In order to evaluate the tracking performance of the proposed scheme, an algorithm is tested for some of the examples including maneuvering of an automobile and a 2-DOF mechanical system.     

Finite-time decentralized adaptive neural constrained control for interconnected nonlinear time-delay systems with dynamics couplings among subsystems

The problem of finite-time decentralized neural adaptive constrained control is studied for large-scale nonlinear time-delay systems in the non-affine form. The main features of the considered system are that 1) unknown unmatched time-delay interactions are considered, 2) the couplings among the nested subsystems are involved in uncertain nonlinear systems, 3) based on finite-time stability approach, asymmetric saturation actuators and output constraints are studied in large-scale systems. First, the smooth asymmetric saturation nonlinearity and barrier Lyapunov functions are used to achieve the input and output constraints. Second, the appropriately designed Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. Note that, due to unknown time-delay interactions and the couplings among subsystems, the controller design is more meaningful and challenging. At last, based on finite-time stability theory and Lyapunov stability theory, a decentralized adaptive controller is proposed, which decreases the number of learning parameters. It is shown that the designed controller can ensure that all closed-loop signals are bounded and the tracking error converges to a small neighborhood of the origin. The simulation studies are presented to show the effectiveness of the proposed method.     

Finite-time stability for discrete-time system with time-varying delay and nonlinear perturbations

In this paper, the problem of finite-time stability for discrete-time system with time-varying delay and nonlinear perturbations is investigated. By constructing a novel Lyapunov–Krasovskii functional and employing a new summation inequality named discrete Wirtinger-based inequality, reciprocally convex approach and zero equality, the improved finite-time stability criteria are derived to guarantee that the state of the system with time-varying delay does not exceed a given threshold when fixed time interval. Furthermore, the obtained conditions are formulated in forms of linear matrix inequalities which can be solved by using some standard numerical packages. Finally, three numerical examples are given to show the effectiveness and less conservatism of the proposed method.     

Time-discretization of non-affine nonlinear system with delayed input using taylor-series

In this paper, we propose a new scheme for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption. This scheme is applied to the sampled-data representation of a non-affine nonlinear system with constant input time-delay. The mathematical expressions of the discretization scheme are presented and the ability of the algorithm is tested for some of the examples. The proposed scheme provides a finite-dimensional representation for nonlinear systems with time-delay enabling existing controller design techniques to be applied to them. For all the case studies, various sampling rates and time-delay values are considered.     

基于T-S模型的自适应模糊PID控制器的设计

基于T-S模型设计模糊PID控制器,在分析量化因子和比例因子对系统性能的影响基础上,基于T-S模型制定了在线校正量化因子和比例因子模糊规则,实现了模糊PID控制器在线自校正.对大纯滞后对象的仿真表明,该控制器明显改善系统的动态性能.     

Model algorithm control for path tracking of wheeled mobile robots

This paper proposes a model algorithm control (MAC) method for the path tracking control of differentially steered wheeled mobile robots (WMRs) subject to nonholonomic constraints. The continuous dynamic model of the wheeled mobile robot is presented and used as the model to be controlled. The MAC controller is designed based on the sampled-data representation of the system. In this paper the case that there exists time delay in the control input is also considered. A time discretization method using the Taylor series and the zero-order-hold (ZOH) assumption is proposed to discretize the continuous dynamic model of the WMR. This time discretization method is especially useful in the case of the time delayed system. It can provide finite dimensional and more accurate discretized form model of the mobile robot with input time delay and convert it into a general nonlinear time discretized form to which the MAC controller can be applied. Simulations are conducted to show the performance and feasibility of the proposed control strategy. In these simulations the WMR is controlled to track two difference reference paths such as the “8” shape path and the circular path. The bounded inertial parameters uncertainties and some disturbance are also considered in the model of the control system.     

Further improved stability criteria for uncertain T–S fuzzy systems with interval time-varying delay by delay-partitioning approach

This paper focuses on further improved stability criteria for uncertain T–S fuzzy systems with interval time-varying delay by a delay-partitioning approach. A modified augmented Lyapunov–Krasovskii functional (LKF) is established by partitioning the delay in all integral terms. Then some tighter bounding inequalities, i.e., Peng–Park׳s integral inequality (reciprocally convex approach) and the Free-Matrix-Based integral inequality (which yields less conservative stability criteria than the use of Wirtinger-based inequality does) are introduced to reduce the enlargement in bounding the derivative of LKF as much as possible, therefore, less conservative results can be expected in terms of e_s and LMIs. Finally, a numerical example is included to show that the proposed methods are less conservative than existing ones.     

New stability and stabilization conditions for nonlinear systems with time-varying delay based on delay-partitioning approach

This paper focuses on stability analysis and stabilization of nonlinear systems with interval time-varying delay, modeled by Takagi-Sugeno (T-S) fuzzy approach. To achieve more relaxation in the feasibility region, delay-partitioning approach is used for all integral terms in the Lyapunov-Krasovskii functional (LKF). A fuzzy Lyapunov function is proposed instead of non-integral term in LKF, and moreover, some slack matrices variables are offered to enlarge the design space. By doing this, new delay-dependent stability criteria are obtained. During the derivation of stability conditions, Jensen’s integral inequality is applied to deal with integral terms. Furthermore, in this paper the problem of controller design via the parallel distributed compensation (PDC) scheme is studied. Stability and stabilization conditions with less conservative are achieved in terms of linear matrix inequality (LMI). Finally, two numerical examples are presented to show the effectiveness of the proposed results.     

Finite-time Extended State Observer based fault tolerant output feedback control for attitude stabilization

This work addresses the challenging problem of finite-time fault tolerant attitude stabilization control for the rigid spacecraft attitude control system without the angular velocity measurements, in the presence of external disturbances and actuator failures. Consider the severe circumstances with above failures and uncertainties, a novel continuous finite-time Extended State Observer is first established to observe the attitude angular velocity and the synthetic failure simultaneously. Unlike the existing observers, the finite-time methodology and Extended State Observer are utilized, to achieve the finite-time uniformly ultimately bounded stability of the attitude angular velocity and extended state observation errors. Furthermore, a novel continuous finite-time attitude controller is developed by using the nonsingular terminal sliding mode control and super-twisting method. The main feature of this work stems from our use of multiply advanced techniques or methodologies that enables the finite-time stability of the closed-loop attitude control system and the designed control scheme is continuous with the property of chattering restraining. Finally, numerical simulation results are presented to illustrate the effectiveness and fine performances of the finite-time observer and controller for the attitude control system.     

Time discretization of nonlinear systems with variable time-delayed inputs using a Taylor series expansion

This paper proposes a new method of discretization for nonlinear systems using a Taylor series expansion and the zero-order hold assumption. The method is applied to sampled-data representations of nonlinear systems with input time delays. The delayed input varies in time and its amplitude is bounded. The maximum time-delayed input is assumed to be two sampling periods. The mathematical expressions of the discretization method are presented and the ability of the algorithm is tested using several examples. A computer simulation is used to demonstrate that the proposed algorithm accurately discretizes nonlinear systems with variable time-delayed inputs.     

Non-fragile sampled-data robust synchronization of uncertain delayed chaotic Lurie systems with randomly occurring controller gain fluctuation

This paper proposes a new non-fragile stochastic control method to investigate the robust sampled-data synchronization problem for uncertain chaotic Lurie systems (CLSs) with time-varying delays. The controller gain fluctuation and time-varying uncertain parameters are supposed to be random and satisfy certain Bernoulli distributed white noise sequences. Moreover, by choosing an appropriate Lyapunov-Krasovskii functional (LKF), which takes full advantage of the available information about the actual sampling pattern and the nonlinear condition, a novel synchronization criterion is developed for analyzing the corresponding synchronization error system. Furthermore, based on the most powerful free-matrix-based integral inequality (FMBII), the desired non-fragile sampled-data estimator controller is obtained in terms of the solution of linear matrix inequalities. Finally, three numerical simulation examples of Chua's circuit and neural network are provided to show the effectiveness and superiorities of the proposed theoretical results.     

Finite-time master–slave synchronization and parameter identification for uncertain Lurie systems

This paper investigates the finite-time master–slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master–slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method.