Unscented Kalman filter for continuous‐time nonlinear fractional‐order systems with process and measurement noises

This study proposes the design of unscented Kalman filter for a continuous‐time nonlinear fractional‐order system involving the process noise and the measurement noise. The nonlinear fractional‐order system is discretized to get the difference equation. According to the unscented transformation, the design method of unscented Kalman filter for a continuous‐time nonlinear fractional‐order system is provided. Compared with the extended Kalman filter, the proposed method can obtain a more accurate estimation effect. For fractional‐order systems containing non‐differentiable nonlinear functions, the method proposed in this paper is still effective. The unknown parameters are also discussed by the augmented vector method to achieve the state estimation and parameter identification. Finally, two examples are offered to verify the effectiveness of the proposed unscented Kalman filter for nonlinear fractional‐order systems.     

Finite‐time stabilization of stochastic low‐order nonlinear systems with FT‐SISS inverse dynamics

This paper studies finite‐time stabilization problem for stochastic low‐order nonlinear systems with stochastic inverse dynamics. By characterizing unmeasured stochastic inverse dynamics with finite‐time stochastic input‐to‐state stability, combining the Lyapunov function and adding a power integrator technique, and using the stochastic finite‐time stability theory, a state feedback controller is designed to guarantee global finite‐time stability in probability of stochastic low‐order nonlinear systems with finite‐time stochastic input‐to‐state stability inverse dynamics.     

Finite‐time output feedback stabilization of nonlinear high‐order feedforward systems

This paper considers the global finite‐time output feedback stabilization of a class of nonlinear high‐order feedforward systems. By using the homogeneous domination method together with adding a power integrator method and overcoming several troublesome obstacles in the design and analysis, a global finite‐time output feedback controller with reduced‐order observer is recursively designed to globally finite‐time stabilize nonlinear high‐order feedforward systems. Copyright © 2015 John Wiley & Sons, Ltd.     

Extended Kalman filters for fractional‐order nonlinear continuous‐time systems containing unknown parameters with correlated colored noises

By using the Grünwald‐Letnikov (G‐L) difference method and the Tustin generating function method, this study presents extended Kalman filters to achieve satisfactory state estimation for fractional‐order nonlinear continuous‐time systems that containing some unknown parameters with the correlated fractional‐order colored noises. Based on the G‐L difference method and the Tustin generating function method, the difference equations corresponding to fractional‐order nonlinear continuous‐time systems are constructed respectively. The first‐order Taylor expansion is used to linearize the nonlinear functions in the estimated system, which provides the system model for extended Kalman filters. Using the augmented vector method, the unknown parameters are regarded as new state vectors, and the augmented difference equation is constructed. Based on the augmented difference equation, extended Kalman filters are designed to estimate the state of fractional‐order nonlinear systems with process noise as fractional‐order colored noise or measurement noise as fractional‐order colored noise. Meanwhile, the extended Kalman filters proposed in this paper can also estimate the unknown parameters effectively. Finally, the effectiveness of the proposed extended Kalman filters is validated in simulation with two examples.     

Active disturbance rejection control for nonlinear fractional‐order systems

This paper investigates active disturbance rejection control involving the fractional‐order tracking differentiator, the fractional‐order PID controller with compensation and the fractional‐order extended state observer for nonlinear fractional‐order systems. Firstly, the fractional‐order optimal‐time control scheme is studied to propose the fractional‐order tracking differentiator by the Hamilton function and fractional‐order optimal conditions. Secondly, the linear fractional‐order extend state observer is offered to acquire the estimated value of the sum of nonlinear functions and disturbances existing in the investigated nonlinear fractional‐order plant. For the disturbance existing in the feedback output, the effect of the disturbance is discussed to choose a reasonable parameter in fractional‐order extended state observer. Thirdly, by this observed value, the nonlinear fractional‐order plant is converted into a linear fractional‐order plant by adding the compensation in the controller. With the aid of real root boundary, complex root boundary, and imaginary boot boundary, the approximate stabilizing boundary with respect to the integral and differential coefficients is determined for the given proportional coefficient, integral order and differential order. By choosing the suitable parameters, the fractional‐order active disturbance rejection control scheme can deal with the unknown nonlinear functions and disturbances. Finally, the illustrative examples are given to verify the effectiveness of fractional‐order active disturbance rejection control scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

Generalized Nonlinear Stiffness Identification on Controlled Mechanical Vibrating Systems

A new algebraic parametric identification method in time domain for multiple degrees‐of‐freedom mechanical vibrating systems with high‐order nonlinear stiffness is proposed. Parameters of mass, damping and linear and nonlinear stiffness are estimated on‐line and, simultaneously, using transient real‐time position measurements and active control force signals. Parametric identification can be applied for real‐time estimation of both symmetrical and non‐symmetrical stiffness. Parametric identification is combined with adaptive planned motion control on Multiple‐Input‐Multiple‐Output nonlinear mechanical vibrating systems. Analytical and numerical results prove the effectiveness and efficiency of the proposed on‐line algebraic parametric identification approach.     

Distributed consensus and tracking control of second‐order time‐varying nonlinear multi‐agent systems

In this paper, the distributed consensus and tracking protocols are developed for the second‐order time‐varying nonlinear multi‐agent systems under general directed graph. Firstly, the consensus and tracking problems can be converted into a conventional stabilization control problem. Then a state transformation is employed to deal with the time‐varying nonlinearities. By choosing an appropriate time‐varying parameter and coupling strengths, exponential consensus and tracking of second‐order nonlinear multi‐agent systems can be achieved. Finally, a simulation is given to illustrate the effectiveness of the proposed consensus and tracking protocols. Copyright © 2017 John Wiley & Sons, Ltd.     

Robust Finite‐Time Stability Control of a Class of High‐Order Uncertain Nonlinear Systems

In this study, a novel robust finite‐time stability controller is proposed for a class of high‐order uncertain nonlinear systems. It uses the dynamic surface control (DSC) approach to simplify the traditional backstepping design for high‐order nonlinear systems, thus avoiding the “explosion of terms”. The finite‐time stability of the closed‐loop system is guaranteed to have high performance, such as fast transient and strong robustness to dynamic uncertainties, and the tracking error is made arbitrarily small. Simulation results of two examples indicate that the proposed controller is effective.     

A method to construct reduced‐order parameter‐varying models

This paper describes a method to construct reduced‐order models for high‐dimensional nonlinear systems. It is assumed that the nonlinear system has a collection of equilibrium operating points parameterized by a scheduling variable. First, a reduced‐order linear system is constructed at each equilibrium point using state, input, and output data. This step combines techniques from proper orthogonal decomposition, dynamic mode decomposition, and direct subspace identification. This yields discrete‐time models that are linear from input to output but whose state matrices are functions of the scheduling parameter. Second, a parameter‐varying linearization is used to connect these linear models across the various operating points. The key technical issue in this second step is to ensure the reduced‐order linear parameter‐varying system approximates the nonlinear system even when the operating point changes in time. Copyright © 2016 John Wiley & Sons, Ltd.     

Nonlinear adaptive learning control for unknown time‐varying parameters and unknown time‐varying delays

A new adaptive learning control approach is proposed for a class of first‐order nonlinear systems with two unknown time‐varying parameters and an unknown time‐varying delay. By reconstructing the system equation, all unknown time‐varying terms, including the time‐varying delay, are combined into an unknown periodic time‐varying vector, which is estimated by a periodic adaptive mechanism. By constructing a Lyapunov–Krasovskii‐like composite energy function (CEF), we prove the boundedness of all signals and the convergence of the tracking error. The results are extended to two classes of high‐order nonlinear systems with mixed parameters. Three simulation examples are provided to illustrate the effectiveness of the control algorithms proposed in this paper. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Continuous‐ and discrete‐time fixed‐gain controller designs for the control of vehicle lateral dynamics

In this paper, fixed‐gain feedback linearization controls are presented to stabilize the vehicle lateral dynamics at bifurcation points for both continuous‐time and discrete‐time cases. Based on the assumption of constant driving speed, a second‐order nonlinear lateral dynamics model is adopted for controller design. Via the feedback linearization scheme and the first‐order Taylor series expansion, a time‐invariant feedback linearization control is proposed as a fixed‐gain linear version of the previously proposed nonlinear one. Furthermore, the conventional linear quadratic regulator (LQR) design is applied to facilitate the choice of the fixed‐gain matrix. Refined controls to compensate the model uncertainty and their local stability analysis are provided. Extension of the continuous‐time design results to discrete‐time cases is also addressed. Numerical simulations for an example model demonstrate the effectiveness of the proposed continuous‐time and discrete‐time design results. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Fractional‐Order Dynamic Output Feedback Sliding Mode Control Design for Robust Stabilization of Uncertain Fractional‐Order Nonlinear Systems

A robust fractional‐order dynamic output feedback sliding mode control (DOF‐SMC) technique is introduced in this paper for uncertain fractional‐order nonlinear systems. The control law consists of two parts: a linear part and a nonlinear part. The former is generated by the fractional‐order dynamics of the controller and the latter is related to the switching control component. The proposed DOF‐SMC ensures the asymptotical stability of the fractional‐order closed‐loop system whilst it is guaranteed that the system states hit the switching manifold in finite time. Finally, numerical simulation results are presented to illustrate the effectiveness of the proposed method.     

Robust Exponential Stability and Stabilization of a Class of Nonlinear Stochastic Time‐Delay Systems

This paper presents new exponential stability and delayed‐state‐feedback stabilization criteria for a class of nonlinear uncertain stochastic time‐delay systems. By choosing the delay fraction number as two, applying the Jensen inequality to every sub‐interval of the time delay interval and avoiding using any free weighting matrix, the method proposed can reduce the computational complexity and conservativeness of results. Based on Lyapunov stability theory, exponential stability and delayed‐state‐feedback stabilization conditions of nonlinear uncertain stochastic systems with the state delay are obtained. In the sequence, the delayed‐state‐feedback stabilization problem for a nonlinear uncertain stochastic time‐delay system is investigated and some sufficient conditions are given in the form of nonlinear inequalities. In order to solve the nonlinear problem, a cone complementarity linearization algorithm is offered. Mathematical and/or numerical comparisons between the proposed method and existing ones are demonstrated, which show the effectiveness and less conservativeness of the proposed method.     

Razumikhin‐type approach on state feedback of stochastic high‐order nonlinear systems with time‐varying delay

The Razumikhin‐type approach is introduced to solve the state feedback stabilization problem for a class of stochastic high‐order nonlinear systems with time‐varying delay. Based on the general Razumikhin‐type theorem on stochastic systems established in our paper and backstepping design method, a state feedback controller is constructed to ensure the origin of closed‐loop system is globally asymptotically stable in probability. Our methodology enables us to completely remove the limitations on the derivative of delay, which is the common assumption of stochastic high‐order nonlinear systems with time‐varying delay. The efficiency of the state feedback controller is demonstrated by simulation examples. Copyright © 2017 John Wiley & Sons, Ltd.     

Adaptive practical preassigned finite‐time stability for a class of pure‐feedback systems with full state constraints

This paper focuses on an adaptive practical preassigned finite‐time control problem for a class of unknown pure‐feedback nonlinear systems with full state constraints. Two new concepts, called preassigned finite‐time function and practical preassigned finite‐time stability, are defined. In order to achieve the main result, the pure‐feedback system is first transformed into an affine strict‐feedback nonlinear system based on the mean value theorem. Then, an adaptive preassigned finite‐time controller is obtained based on a modified barrier Lyapunov function and backstepping technique. Finally, simulation examples are exhibited to demonstrate the effectiveness of the proposed scheme.     

Data‐driven high‐order terminal iterative learning control with a faster convergence speed

In this paper, a novel high‐order optimal terminal iterative learning control (high‐order OTILC) is proposed via a data‐driven approach for nonlinear discrete‐time systems with unknown orders in the input and output. The objective is to track the desired values at the endpoint of the operation cycle. The terminal tracking errors over more than one previous iterations are used to enhance the high‐order OTILC's performance with faster convergence. From rigor of the analysis, the monotonic convergence of the terminal tracking error is proved along the iteration direction. More importantly, the condition for a high‐order OTILC to outperform the low‐order ones is first established by this work. The learning gain is not fixed but iteratively updated by using the input and output (I/O) data, which enhances the flexibility of the proposed controller for modifications and expansions. The proposed method is data‐driven in which no explicit models are used except for the input and output data. The applications to a highly nonlinear continuous stirred tank reactor and a highly nonlinear fed‐batch fermentater demonstrate the effectiveness of the proposed high‐order OTILC design.     

A unified approach to finite‐time stabilization of high‐order nonlinear systems with and without an output constraint

This paper considers the problem of state feedback finite‐time stabilization for a class of high‐order nonlinear systems with an output constraint. By proposing a novel tan‐type barrier Lyapunov function combined with manipulating sign functions, the technique of adding a power integrator is skillfully revamped to develop a systematic approach that guides us to construct a state feedback finite‐time stabilizer for high‐order nonlinear systems while preventing the violation of a prespecified output constraint during operation. The proposed approach is a unified tool in the sense that it can provide a finite‐time stabilizer design even when the constraint is infinite, or equivalently, there is no need for a constraint. A simple example is presented to demonstrate the effectiveness of the proposed strategy.     

Finite‐time stability of fractional order impulsive switched systems

This paper considers the finite‐time stability of fractional order impulsive switched systems. First, by using the fractional order Lyapunov function, Mittag–Leffler function, and Gronwall–Bellman lemma, two sufficient conditions are given to verify the finite‐time stability of fractional order nonlinear systems. Then, the concept of finite‐time stability is extended to fractional order impulsive switched systems. A sufficient condition is given to verify the finite‐time stability of fractional order impulsive switched systems by combining the method of average dwell time with fractional order Lyapunov function. Finally, two numerical examples are provided to illustrate the theoretical results. Copyright © 2014 John Wiley & Sons, Ltd.