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.     

H∞ sliding mode control of discrete switched systems with time-varying delays

The finite-time boundedness issue for a class of discrete switched systems with time-varying delays is investigated via sliding mode control (SMC) approach. By employing the Lyapunov functional and average dwell time method, new sufficient conditions are derived to guarantee the finite-time boundedness of the dynamic system in the novel sliding surface. By solving an optimization problem, the sliding mode controller is synthesized such that the discrete reaching condition is satisfied and the chattering is reduced. A simulation example tests the feasibility of the provided SMC scheme.     

Stochastic contraction based online estimation of second order wiener system

Wiener system is a block oriented model, having a linear time-invariant dynamic system followed by a memory-less nonlinearity. To design a stochastic estimator for online estimation of Wiener system of second order, this paper utilizes differential mean value theorem and the results of stochastic contraction theory. The asymptotic convergence of proposed estimator is derived by using contraction theory related to semi-contracting systems. The boundedness and convergence of the parameter and state estimates have been shown analytically. The introduced method has potentials to estimate accurately states and parameters of Wiener model simultaneously from the noisy output of the system and unknown structure of nonlinearity. Numerical simulation of the stochastic estimator is presented to justify the claim by considering the two examples of the real world system with an additive measurement noise.     

Finite-time stabilization for a class of stochastic nonlinear systems via output feedback

This paper investigates the problem of global finite-time stabilization in probability for a class of stochastic nonlinear systems. The drift and diffusion terms satisfy lower-triangular or upper-triangular homogeneous growth conditions. By adding one power integrator technique, an output feedback controller is first designed for the nominal system without perturbing nonlinearities. Based on homogeneous domination approach and stochastic finite-time stability theorem, it is proved that the solution of the closed-loop system will converge to the origin in finite time and stay at the origin thereafter with probability one. Two simulation examples are presented to illustrate the effectiveness of the proposed design procedure.     

Robust finite-time chaos synchronization of uncertain permanent magnet synchronous motors

In this paper, a robust finite-time chaos synchronization scheme is proposed for two uncertain third-order permanent magnet synchronous motors (PMSMs). The whole synchronization error system is divided into two cascaded subsystems: a first-order subsystem and a second-order subsystem. For the first subsystem, we design a finite-time controller based on the finite-time Lyapunov stability theory. Then, according to the backstepping idea and the adding a power integrator technique, a second finite-time controller is constructed recursively for the second subsystem. No exogenous forces are required in the controllers design but only the direct-axis (d-axis) and the quadrature-axis (q-axis) stator voltages are used as manipulated variables. Comparative simulations are provided to show the effectiveness and superior performance 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.     

Fuzzy model predictive control of non-linear processes using convolution models and foraging algorithms

In this paper, a fuzzy model predictive control (FMPC) approach is introduced to design a control system for nonlinear processes. The proposed control strategy has been successfully employed for representative, benchmark chemical processes. Each nonlinear process system is described by fuzzy convolution models, which comprise a number of quasi-linear fuzzy implications (FIs). Each FI is employed to describe a fuzzy-set based relation between control input and model output. A quadratic optimization problem is then formulated, which minimizes the difference between the model predictions and the desired trajectory over a predefined predictive horizon and the requirement of control energy over a shorter control horizon. The present work proposes to solve this optimization problem by employing a contemporary population-based evolutionary optimization strategy, called the Bacterial Foraging Optimization (BFO) algorithm. The solution of this optimization problem is utilized to determine optimal controller parameters. The utility of the proposed controller is demonstrated by applying it to two non-linear chemical processes, where this controller could achieve better performances than those achieved by similar competing controller, under various operating conditions and design considerations. Further comparisons between various stochastic optimization algorithms have been reported and the efficacy of the proposed approach over similar optimization based algorithms has been concluded employing suitable performance indices.     

Sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage

The problem of sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage is investigated in this paper. The objective of designing controllers is to guarantee the stability and anti-disturbance performance of the closed-loop systems while some sensor outages happen. Firstly, based on matrix transformation, the state-space model of structural systems with sensor outages and uncertainties appearing in the mass, damping and stiffness matrices is established. Secondly, by considering most of those earthquakes or strong winds happen in a very short time, and it is often the peak values make the structures damaged, the finite-time stability analysis method is introduced to constrain the state responses in a given time interval, and the H-infinity stability is adopted in the controller design to make sure that the closed-loop system has a prescribed level of disturbance attenuation performance during the whole control process. Furthermore, all stabilization conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using the LMI Toolbox. Finally, numerical examples are given to demonstrate the effectiveness of the proposed theorems.     

Relative position finite-time coordinated tracking control of spacecraft formation without velocity measurements

This paper investigates finite-time relative position coordinated tracking problem by output feedback for spacecraft formation flying without velocity measurement. By employing homogeneous system theory, a finite-time relative position coordinated tracking controller by state feedback is firstly developed, where the desired time-varying trajectory given in advance can be tracked by the formation. Then, to address the problem of lack of velocity measurements, a finite-time output feedback controller is proposed by involving a novel filter to recover unknown velocity information in a finite time. Rigorous proof shows that the proposed control law ensures global stability and guarantees the position of spacecraft formation to track a time-varying reference in finite time. Finally, simulation results are presented to illustrate the performance of the proposed controller.     

Stochastic dynamic output feedback stabilization of uncertain stochastic state-delayed systems

This paper addresses the problem of stochastic dynamic output feedback (SDOF) stabilization for a class of stochastic continuous-time state-delayed systems with norm-bounded nonlinear uncertainties. The aim is to design a linear, delayless, and SDOF control for all admissible uncertainties. The designed control ensures stochastically exponentially stability in the mean square, independent of the deterministic time delay. Using the Finsler's lemma, the necessary and sufficient conditions for the existence of such a control are proposed in terms of certain linear matrix inequalities. These results are illustrated with a simple example to demonstrate the applicability of the proposed design approach.     

Global fast dynamic terminal sliding mode control for a quadrotor UAV

A control method based on global fast dynamic terminal sliding mode control (TSMC) technique is proposed to design the flight controller for performing the finite-time position and attitude tracking control of a small quadrotor UAV. Firstly, the dynamic model of the quadrotor is divided into two subsystems, i.e., a fully actuated subsystem and an underactuated subsystem. Secondly, the dynamic flight controllers of the quadrotor are formulated based on global fast dynamic TSMC, which is able to guarantee that the position and velocity tracking errors of all system state variables converge to zero in finite-time. Moreover, the global fast dynamic TSMC is also able to eliminate the chattering phenomenon caused by the switching control action and realize the high precision performance. In addition, the stabilities of two subsystems are demonstrated by Lyapunov theory, respectively. Lastly, the simulation results are given to illustrate the effectiveness and robustness of the proposed control method in the presence of external disturbances.     

Robust control of post-stall pitching maneuver based on finite-time observer

This article presents a robust finite-time maneuver control scheme for the longitudinal attitude dynamic of the aircraft with unsteady aerodynamic disturbances and input saturation. To efficiently eliminate the influence of unsteady aerodynamic disturbances, nonlinear finite-time observers are developed. Despite the existence of the nonlinearity and the coupling between aircraft states and unsteady aerodynamic disturbances, the proposed observers can still precisely estimate the unmeasurable unsteady aerodynamic disturbances in finite time. To attenuate the effect caused by input saturation, a finite-time auxiliary system is constructed. With the error between the desired control input and saturation input as the input of the auxiliary system, the additional signals are generated to compensate for the effect of input saturation. Combined with the finite-time observers and the finite-time auxiliary system, a robust finite-time backstepping attitude control design is developed. The finite-time convergence of all closed-loop system signals is rigorously proved via Lyapunov analysis method under the developed robust attitude control schemes. Finally, simulation results are presented to illustrate the effectiveness of the proposed attitude control approaches.     

Finite-time extended dissipative control for fuzzy systems with nonlinear perturbations via sampled-data and quantized controller

This paper investigates the problem of finite-time extended dissipative control for T–S fuzzy time-varying delay systems with nonlinear perturbations via sampled-data and quantized controller. The definition of finite-time bounded mixed extended dissipative of fuzzy systems is first proposed. Based on the constructed Lyapunov–Krasovskii functional(LKF) and Peng–Parks integral inequality, some sufficient conditions are obtained in the form of linear matrix inequalities(LMIs), which are less conservative than other papers. By combining the input delay approach and dynamic quantizer, the sampled-data and quantized controller is designed to guarantee that the T–S fuzzy system is finite-time bounded mixed extended dissipative. Finally, some numerical examples and practical examples are presented to verify the feasibility and effectiveness of the proposed methods.     

A novel linear tracking integrator with integral compensation and its application

A novel linear tracking integrator (LTI) with integral compensation is proposed for efficient integral estimation from a contaminated measurement with a constant or time-varying bias. The limitation of finite-time convergent integral observer (FTCIO) in ruling out the integral drift is firstly revealed via describing function method. Subsequently, by the utilization of integral action in the feedback path, a simple but effective linear tracking integrator is established to provide a practical solution in achieving a drift-free integral estimate. The highlight is that the proposed LTI can simultaneously give the accurate integral and tracking estimates from a noisy measurement without relying on the condition of observability. In addition, frequency-domain analysis of LTI is investigated to give a viable guideline of parameter tuning. Illustrative simulations and comparison with Kalman filter are included to demonstrate the superiority of LTI in accomplishing precise integral tracking in the presence of constant or time-varying bias. Finally, the effectiveness of LTI is also confirmed by an application on autopilot design for aircraft.     

MMSE design of nonlinear Volterra equalizers using artificial bee colony algorithm

In this paper a novel approach for channel equalization is presented, where a framework for Volterra system is used to model both the channel and the equalizer. We propose development of first-order and second-order Volterra equalizers using minimum mean square error (MMSE) approach and design these equalizers using swarm intelligence based stochastic optimization algorithm which is applied to adapt the equalizer coefficients to the time varying channel. This work proposes to use the artificial bee colony (ABC) algorithm, recently introduced for global optimization, simulating the intelligent foraging behavior of honey bee swarm in a simple, robust, and flexible manner. For comparative analysis, adaptive equalizers like least mean squares (LMSs) equalizer, recursive least squares (RLSs) equalizer and least mean p-Norm (LMP) equalizer and population based optimum equalizers employing PSO are also applied for identical problems and the superiority of the newly proposed algorithm is aptly demonstrated.     

Finite-time boundedness filtering for discrete-time Markovian jump system subject to partly unknown transition probabilities

This paper investigates the problem of finite-time boundedness filtering for discrete-time Markovian jump system subject partly unknown transition probabilities. By using the multiple Lyapunov function approach, a novel sufficient condition for finite-time bounded of _H∞$H_{\infty }$ filtering is derived and the system trajectory stays within a prescribed bound during a specified time interval. Finally, an example is provided to illustrate the usefulness and effectiveness of the proposed method.