Finite-time Stability Research Articles

Continuous-time nonlinear model predictive control based on Pontryagin Minimum Principle and penalty functions

Pontryagin's Minimum Principle (PMP) is a powerful tool for solving Nonlinear Model Predictive Control problems (NMPC), enabling the handling of time-varying input constraints and cost functions. However, applying PMP encounters challenges when state constraints must be satisfied. This arises because the optimal trajectory often requires a blend of unconstrained and constrained arcs with unknown junction points. To address this issue, relaxation methods are frequently explored, where state constraints are replaced with penalty functions. The contributions of this paper are as follows. First, a method of penalty functions allowing for coping with soft state constraints is examined. We prove the recursive feasibility of this method and demonstrate its efficiency in a numerical example. Second, the finite-time practical stability for the optimal reference tracking NMPC problem is addressed. By appropriately choosing the terminal cost, one can guarantee the convergence of the state vector to a predefined neighbourhood of the target state.

Finite-time stability of a class of nonlinear cascaded systems with time-varying output constraints

The finite-time stabilization problem of a class of cascaded systems with time-varying output constraints is investigated in this paper. The system consists of input-to-state stable inverse dynamics and a nonholonomic system. The technology of changing the supply rate eliminates dynamic uncertainty. A new tan-type barrier Lyapunov function is utilized to handle time-varying output constraints. Under the unified framework of constrained and unconstrained systems, combined with the addition of power integrator technology and switch control strategy, a state feedback control strategy is proposed to ensure that the state of the closed-loop system converges to zero in a finite-time and always satisfies time-varying output constraints. Finally, simulation results verify the proposed control scheme’s effectiveness.

A novel finite-time stability criteria and controller design for nonlinear impulsive systems

The issue of a novel finite-time stability and stabilization design for a class of nonlinear impulsive systems is discussed in this paper. In previous finite-time control designs for impulsive systems, the convergence rate of these control strategies is even less rapid than the exponential convergence rate when the initial state is distant from the origin. To overcome this problem, two sufficient conditions for the novel finite-time stability of impulsive systems are presented, in which the stabilizing impulses and the destabilizing impulses are considered, respectively. Meanwhile, the upper bound of the settling-time is evaluated. In addition, combining Lyapunov functions theory with impulsive control, we design a controller for impulsive dynamical systems to satisfy the novel finite-time stability. Finally, two simulation examples are given, in which the first example demonstrates the superiority of the proposed finite-time stability criterion for nonlinear impulsive systems by comparing it with traditional finite-time stability, and the second example verifies the effectiveness of the presented controller.

Adaptive finite-time neural control of nonstrict-feedback nonlinear systems with input dead-zone and output hysteresis

This paper explores the adaptive finite-time neural control issue for nonlinear systems with input dead zone and output hysteresis in nonstrict-feedback form. The unknown functions are estimated by employing the radial basis function neural networks (RBFNN) approach. A systematic adaptive finite-time control method is introduced using the backstepping technique and neural network approximation properties. The stability of the system is also examined by using semi-global practical finite-time stability theory. The established control approach guarantees the boundedness of all signals within the closed-loop system, enabling the system output to accurately follow the desired signal within a finite time framework while maintaining a small and bounded tracking error. Finally, simulation results are shown to demonstrate the efficacy of the suggested strategy.

Finite-time annular domain robust guaranteed cost control of interval positive linear systems

The issue of finite-time annular domain robust guaranteed cost control of positive linear systems with interval uncertainties is investigated in this paper. First, by using the linear copositive Lyapunov function, a sufficient condition for the existence of state feedback controller is given to ensure the positivity and finite-time annular domain robust stability of the closed-loop system, and guarantee the cost function is no more than a given upper bound. The corresponding controller design method is derived based on linear programming technique. Then, an optimisation algorithm is further developed to obtain the optimal guaranteed cost controller, which is convenient to be computed. Finally, a numerical example and an application example are given to demonstrate the effectiveness of theoretical results.

Combining finite-time control and prescribed tracking performance for uncertain PMSM driven steer-by-wire system with unknown disturbance

To solve the uncertainties in permanent magnet synchronous motor (PMSM) driven steer-by-wire (SbW) system, a prescribed-performance-control (PPC) based finite-time fuzzy controller is proposed. Specifically, the dynamics of SbW system driven by PMSM is analyzed, and combine PPC technology to transform the tracking error coordinates. Then, the velocity signal is obtained from the sigmoid function-based tracking differentiator by using the position signal. To solve the problem of mismatched disturbance, fuzzy logic system (FLS) are used as a universal approximator to estimate the lumped nonlinear friction and other unknown functions, the boundary of lumped disturbance is estimated by the designed adaptive updating law. By fusing the designed virtual controller and the intermediate control law, the controller needs no precise parameters of system, under which the effect of uncertainty of control gain can be compensated completely. Finally, rigorous theoretical analysis based on the Lyapunov stability theory is provided to demonstrate the finite-time stability of the closed-loop system under consideration. Simulation and experiment results are presented to show the effectiveness of the developed control approach, and some comparisons are given to show the rapid and accurate position tracking control performance.

Distributed adaptive finite-time output feedback containment control for nonstrict-feedback stochastic multi-agent systems via command filters

In this paper, distributed adaptive finite-time output feedback containment control based on command filters is proposed for nonstrict-feedback stochastic multi-agent systems (SMASs) with unmodeled dynamics, input quantization and prescribed performance. The unknown states are estimated using a high-gain observer, the unmodeled dynamics is handled by introducing a measurable dynamic signal, and the input signal is processed using an integrated quantizer that combines the advantages of uniform quantizer and hysteretic quantizer. The hyperbolic tangent function and time-varying function are applied to construct the performance function, and the constrained containment error is transformed into an unconstrained system through nonlinear mapping (NM). Unknown smooth functions are handled with the superb approximation capability of radial basis function neural networks (RBFNNs). Based on stochastic finite-time theory and dynamic surface control (DSC) method, nonlinear command filters are introduced to reduce the use of black-box functions and simplify the controller design. Finally, the theoretical analysis and two sets of experimental results demonstrate that all signals in the controlled system are semi-global finite-time stability in probability (SGFSP) and the designed controller works well.

Finite-Time Stabilization of Uncertain Markovian Jump Systems: An Adaptive Gain-Scheduling Control Method

Finite-Time Stabilization of Uncertain Markovian Jump Systems: An Adaptive Gain-Scheduling Control Method

Fractional discrete neural networks with variable order: solvability, finite time stability and synchronization

Fractional discrete neural networks with variable order: solvability, finite time stability and synchronization

A novel distributed finite-time economic dispatch for DC microgrids with time delays

This paper delineates an advanced distributed control paradigm for finite-time generation cost optimization in DC Microgrids (MGs), taking into account time delays. Firstly, to enhance system stability with time delays, Artstein's reduction approch is utilized to convert the time-delayed system into an equivalent delay-free model. Subsequently, a finite-time consensus-based distributed algorithm for cost optimization is formulated to equilibrate the incremental costs (ICs) of all distributed generators (DGs) in a predefined convergence time, while adhering to the DGs' capacity limits. Moreover, a distributed control mechanism for finite-time voltage stabilization is developed for sustaining the balance between the generated powers and consumptions across the MG. Rigorous convergence analysis proves that the proposed controller maintains finite-time stability. The efficacy of this innovative control strategy is substantiated through a series of comprehensive case studies.Top of Form

New Adaptive Super-Twisting Extended-State Observer-Based Sliding Mode Scheme with Application to FOWT Pitch Control

This paper details the transformation of the velocity or position-tracking problem of a class of uncertain systems using finite time stability control for first-order uncertain systems. A new composite extended-state observer sliding mode (ESOSM) scheme is proposed, which includes an adaptive super-twisting-like ESO and an adaptive super-twisting controller. The adaptive super-twisting controller is implemented through a barrier function-based second-order sliding mode algorithm. To further reduce control chattering and improve control performance, the adaptive super-twisting-like ESO, which employs high-order terms in the super-twisting algorithm to accelerate convergence, is designed to observe the lumped uncertainty in real time. The advantages of the proposed scheme are verified by a numerical example and application with regard to floating offshore wind turbine (FOWT) pitch control. Compared with proportional integral (PI) and adaptive super-twisting sliding mode (ASTSM) schemes, better results are obtained in velocity tracking and fatigue load suppression. For the FOWT pitch control application, the platform roll, pitch, and yaw are decreased by 3%, 2%, and 4%, respectively, compared to the PI scheme at an average turbulent wind speed of 17 m/s and turbulence intensity of 17.27%.

Distributed finite-time adaptive consensus output-feedback control of multi-agent systems under switching topologies

The paper investigates the finite-time adaptive consensus control of nonlinear multi-agent systems (MASs) by output-feedback. During the process of control design, the fuzzy logic system (FLS) is employed to approximate nonlinear function, as well as constructing a fuzzy state observer to estimate unmeasured states. Combining the dynamic surface control (DSC) with adaptive backstepping method conquers the complexity explosion issue. Then, semi-global practical finite-time stability (SGPFS) for closed-loop system is obtained under arbitrary switching communication topologies. All the signals of the overall system are uniformly ultimately bounded (UUB). Finally, the availability of developed control approach will be demonstrated through a simulation.

Finite-time disturbance observer-based levitation control for vehicle-guideway coupling systems

In this study, a novel composite control scheme for the vehicle-guideway coupling systems is proposed, consisting of FTDOs and a FTC, aiming to address the challenges of unknown disturbances and vibration suppression. Specifically, this method adopts a single magnet-track coupling model and introduces a finite-time disturbance observer (FTDO) that utilizes only measured electromagnet-side signals to estimate unmeasurable states and unknown disturbances. Based on the estimated information provided by the FTDO, a finite-time control (FTC) scheme is developed, which simultaneously handles the problems of disturbance compensation and finite-time tracking control. Additionally, the finite-time stability of the levitation system is analyzed and proven. Finally, simulation and experimental results are given to demonstrate the feasibility and superiority of the proposed control approach.

Existence Results and Finite-Time Stability of a Fractional (p,q)-Integro-Difference System

In this article, we mainly generalize the results in the literature for a fractional q-difference equation. Our study considers a more comprehensive type of fractional p,q-difference system of nonlinear equations. By the Banach contraction mapping principle, we obtain a unique solution. By Krasnoselskii’s fixed-point theorem, we prove the existence of solutions. In addition, finite stability has been established too. The main results in the literature have been proven to be a particular corollary of our work.

Robust Hybrid Visual Servoing of Omnidirectional Mobile Manipulator With Kinematic Uncertainties Using a Single Camera.

A robust hybrid visual servoing (HVS) method for a single camera-mounted omnidirectional mobile manipulator (OMM) with kinematic uncertainties caused by slipping is proposed herein. Most existing studies pertaining to the visual servoing of mobile manipulators do not consider the kinematic uncertainties and the singularity of the manipulator that can occur during actual operations; furthermore, they required external sensors other than a single camera. In this study, the kinematics of an OMM are modeled considering kinematic uncertainties. Accordingly, an integral sliding-mode observer (ISMO) is designed to estimate the kinematic uncertainties. Subsequently, an integral sliding-mode control (ISMC) law is proposed to achieve robust visual servoing using the estimates of the ISMO. Additionally, an ISMO-ISMC-based HVS method is proposed to address the singularity issue of the manipulator; this method guarantees both robustness and finite-time stability in the presence of kinematic uncertainties. Overall, the entire visual servoing task is performed using only a single camera attached to the end effector without any other external sensors, unlike in previous studies. The stability and performance of the proposed method are verified numerically and experimentally in a slippery environment that generates kinematic uncertainties.

Practical Finite-Time Command-Filtered Adaptive Backstepping With Its Applications to Quadrotor Hovers.

In this article, a practical finite-time command-filtered adaptive backstepping (PFTCFAB) control method is presented for a class of uncertain nonlinear systems with nonparametric unknown nonlinearities and external disturbances. Unlike PFTCFAB control techniques that use neural networks (NNs) or fuzzy-logic systems (FLSs) to deal with system uncertainties, the proposed method is capable of handling such uncertainties without the need for NNs or FLSs, thus reducing complexity and increasing reliability. In the proposed approach, novel function adaptive laws are designed to directly estimate unknown nonparametric nonlinearities and external disturbances by means of command filter techniques, and a type of practical finite-time command filters is proposed to obtain such laws. Moreover, the PFTCFAB controllers and finite-time command filters are designed with practical finite-time Lyapunov stability, which ensures finite-time stability of system tracking and filter estimation errors. Experimental results with a quadrotor hover system are presented and discussed to demonstrate the advantages and effectiveness of the proposed control strategy.

Finite-step approximately bi-similar symbolic model for switched systems

Obtaining an approximately bi-similar symbolic model for a continuous-state system is a crucial step in symbolic control. Symbolic control aims to design switching logic to achieve temporal logic specifications. Most existing approaches to approximate bi-simulation are developed over infinite time horizons. However, many control tasks are set within finite periods in practical scenarios. Hence, it makes sense to consider the behavior of trajectories within finite-time horizons. Therefore, this paper introduces two new notions: finite-time uniform incremental stability (FUI-stability) and finite-step approximate bi-simulation. Furthermore, a FUI-stability condition for switched system is derived using the multiple incremental Lyapunov-like functions technique. A symbolic model is constructed for switched system by the state space grid technique. Subsequently, a sufficient condition for finite-step approximate bi-simulation between the finite-time uniformly incrementally stable (FUI-stable) switched system and the constructed symbolic model is derived. Finally, the obtained results are illustrated by two numerical examples.

Adaptive Multi-Input Super Twisting Control for a Quadrotor: Singular Perturbation Approach

Singular perturbations easily result in the problem of high gain. Instead of high gain feedbacks, this work proposes an adaptive two-time-scale (TTS) super twisting control (STWC) algorithm for the attitude tracking of a singularly perturbed quadrotor system (SPQS). The bounds of uncertainties are assumed to be perturbed around their nominal values. First, a nominal STWC with slow and fast control gains is designed to achieve the finite-time attitude tracking for the nominal SPQS. The finite-time stability of the close-loop system is proven by utilizing the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -dependent Lyapunov method. Then, dynamically adapted slow and fast control gains initialized at their nominal values are used for the accurate finite-time convergence of tracking errors to the region around the origin, which avoids overestimating the values of control gains. Experimental results demonstrate the performance of the proposed controller in terms of attitude stabilization and tracking, and robustness to external disturbances.

Finite Time Stabilization in the Production and its Informations Protection

Finite Time Stabilization in the Production and its Informations Protection

Fixed/preassigned-time stabilization of discontinuous switched systems with time-varying delays

The finite-time stabilization of discontinuous switched systems is a highly challenging problem. To address this problem, this article proposes a unified controller that achieves fixed-time and preassigned-time stabilization of discontinuous switched systems with time-varying delays, which is superior to finite-time stabilization. Compared with finite-time stabilization results, the settling time for fixed-time stabilization is independent of the initial state of the system. For preassigned-time stabilization, the settling time can be set in advance regardless of the initial state and controller parameters. Also, the fixed-time and preassigned-time stabilization methods proposed in this article are general and can be extended for applications to other nonlinear discontinuous systems with time delays.