Tracking control of nonlinear automobile idle-speed time-delay system via differential geometry approach

This paper is concerned with the problem of global asymptotical tracking of single-input single-output (SISO) nonlinear time-delay control systems. Based on the input-output feedback linearization technique and Lyapunov method for nonlinear state feedback synthesis, a robust globally asymptotical output tracking controller design methodology for a broad class of nonlinear time-delay control systems is developed. The underlying theoretical approaches are the differential geometry approach and the composite Lyapunov approach. One utilizes the parameterized co-ordinate transformation to transform the original nonlinear system into singularly perturbed model and the composite Lyapunov approach is then applied for output tracking. For the view of practical application, the proposed control methodology has been successfully applied to the famous nonlinear automobile idle-speed control system.     

Adaptive output feedback control of large-scale nonlinear time-delay systems with uncertain output equations

For a class of large-scale nonlinear time-delay systems with uncertain output equations, the problem of global state asymptotic regulation is addressed by output feedback. The class of systems under consideration are subject to feedforward growth conditions with unknown growth rate and time delays in inputs and outputs. To deal with the system uncertainties and the unknown delays, a novel low-gain observer with adaptive gain is firstly proposed; next, an adaptive output feedback delay-free controller is constructed by combining Lyapunov-Krasovskii functional with backstepping algorithm. Compared with the existing results, the controllers proposed are capable of handling both the uncertain output functions and the unknown time delays in inputs and outputs. With the help of dynamic scaling technique, it is shown that the closed-loop states converge asymptotically to zero, while the adaptive gain is bounded globally. Finally, the effectiveness of our control schemes are illustrated by three examples.     

Decentralized global stabilization for stochastic high-order feedforward nonlinear systems with time-varying delays

This paper studies the problem of decentralized stabilization for a class of large-scale stochastic high-order time-delay feedforward nonlinear systems. A series of delay-independent state feedback controllers is constructed, which is based on the approach of adding one power integrator. The stochastically global asymptotic stability (GAS) of the closed-loop system under the above-mentioned controllers is proved by Lyapunov–Krasovskii theorem and homogeneous domination approach. A simulation example is given to illustrate the effectiveness of the results of this paper.     

Input–output finite-time stabilization for MJSs with time-varying delay: An observer-based approach

This paper deals with the input–output finite-time stabilization problem for Markovian jump systems (MJSs) with incompletely known transition rates. An observer-based output feedback controller is constructed to study the input–output finite-time stability (IO-FTS) problem. By using the mode-dependent Lyapunov–krasovskii functional method, a sufficient criterion checking the IO-FTS problem is provided. Then, an observer and a corresponding state feedback controller for the individual subsystem are respectively designed to solve the input–output finite-time stabilization problem for the systems. Finally, a numerical example on the mass-spring system model is investigated to bring out the advantages of the control scheme proposed in this paper.     

Output feedback stabilization of high-order nonlinear systems with polynomial nonlinearity

In this paper, the problem of output feedback stabilization for high-order nonlinear systems with more general low-order and high-order nonlinearities multiplied by a polynomial-type output-dependent growth rate is studied. By constructing the novel Lyapunov function and observer, based on the homogeneous domination and adding a power integrator methods, an output feedback controller is developed to guarantee that the equilibrium of the closed-loop system is globally uniformly asymptotically stable.     

New results on linear parameter-varying time-delay systems

A class of linear parameter-varying time-delay systems where the state-space matrices depend on time-varying parameters and the time-delay is unknown but bounded is considered. Both notions of quadratic stability (using a single quadratic Lyapunov-Krasovskii function) and affine quadratic stability (using parameter-dependent Lyapunov-Krasovskii functions) are investigated. LMI-based delay-independent and delay-dependent conditions are derived for stability testing. Then, state-feedback controllers are designed which guarantee quadratic stability and an induced L₂-norm bound. We use a parameter-independent quadratic Lyapunov-Krasovskii function for the case of dynamic output feedback control to develop LMI-based solvability conditions which are evaluated at the extreme points of the admissible parameter set. Numerical examples are presented.     

Delay-dependent non-fragile robust stabilization and H∞ control of uncertain stochastic systems with time-varying delay and nonlinearity

This paper deals with the problems of non-fragile robust stochastic stabilization and robust H_∞ control for uncertain stochastic nonlinear time-delay systems. The parameter uncertainties are assumed to be time-varying norm-bounded appearing in both state and input matrices. The time-delay is unknown and time-varying with known bounds. The non-fragile robust stochastic stabilization problem is to design a memoryless non-fragile state feedback controller such that the closed-loop system is robustly stochastically stable for all admissible parameter uncertainties. The purpose of robust H_∞ control problem, in addition to robust stochastical stability requirement, is to reduce the effect of the disturbance input on the controlled output to a prescribed level. Using the Lyapunov functional method and free-weighting matrices, delay-dependent sufficient conditions for the solvability of these problems are established in terms of linear matrix inequality (LMI). Numerical example is provided to show the effectiveness of the proposed theoretical results.     

Delay-dependent dissipative control for linear time-delay systems

This paper deals with the problem of delay-dependent dissipative control for a class of linear time-delay systems. We develop the design methods of dissipative static state feedback and dynamic output feedback controllers such that the closed-loop system is quadratically stable and strictly (Q,S,R)-dissipative. Sufficient conditions for the existence of the quadratic dissipative controllers are obtained by using linear matrix inequality (LMI) approach. Furthermore, a procedure of constructing such controllers from the solutions of LMIs is given. It is shown that the solvability of a dissipative controller design problem is implied by the feasibility of LMIs. The main results of this paper unify the existing results on H^∞ control and passive control.     

随机时滞非线性系统状态反馈镇定

针对一类严格反馈随机时滞非线性系统，提出了一种状态反馈镇定方案。在系统非线性函数满足线性增长条件的假设下，基于反推技术和占优方法设计了一个无记忆线性状态反馈控制器。通过构建一个四次Lyapunov-Krasoviskii泛函，证明了闭环系统在概率意义下全局渐近稳定，仿真实例说明了方案的可行性。     

Microfluidic on-chip fluorescence-activated interface control system

A microfluidic dynamic fluorescence-activated interface control system was developed for lab-on-a-chip applications. The system consists of a straight rectangular microchannel, a fluorescence excitation source, a detection sensor, a signal conversion circuit, and a high-voltage feedback system. Aqueous NaCl as conducting fluid and aqueous glycerol as nonconducting fluid were introduced to flow side by side into the straight rectangular microchannel. Fluorescent dye was added to the aqueous NaCl to work as a signal representing the interface position. Automatic control of the liquid interface was achieved by controlling the electroosmotic effect that exists only in the conducting fluid using a high-voltage feedback system. A LABVIEW program was developed to control the output of high-voltage power supply according the actual interface position, and then the interface position is modified as the output of high-voltage power supply. At last, the interface can be moved to the desired position automatically using this feedback system. The results show that the system presented in this paper can control an arbitrary interface location in real time. The effects of viscosity ratio, flow rates, and polarity of electric field were discussed. This technique can be extended to switch the sample flow and droplets automatically.     

Moving horizon estimation for multirate systems with time-varying time-delays

This paper presents a moving horizon estimation approach for the multirate sampled-data system with unknown time-delay sequence. To estimate the unknown variables of interest, two main challenging issues need to be addressed: (a) synthesizing the multirate input and output data for state estimation, (b) simultaneously estimating the continuous state and discrete time-delay sequence. In this work a moving horizon estimation based approach is developed to tackle these issues. The proposed approach can simultaneously estimate both the continuous states and discrete time-delay sequence for dynamic systems. The effects of different noise level on the estimation of continuous states and discrete time-delay sequence are analyzed. The effectiveness of this method is illustrated through a simulation study.     

Robust identification of nonlinear time-delay system in state-space form

This paper puts forward a robust identification solution for nonlinear time-delay state-space model (NDSSM) with contaminated measurements. To enhance the robustness of the developed method for outliers, the heavy-tailed Laplace distribution is employed to describe and protect the output measurement process. The undetermined time-delay is considered to be uniformly distributed and the boundary of it is known as a priori. In the developed solution, the uncertain time-delay is treated as a latent process variable and it is iteratively calculated with the expectation–maximization (EM) algorithm. The EM algorithm is actually an iterative optimization algorithm and it is effective for the hidden variable problems. The particle filter is introduced to numerically approximate the cost function (Q-function) in the EM algorithm since it is difficult to calculate directly. The efficacy of the developed solution is evaluated via a numerical test and a two-link robotic manipulator.     

Global sampled-data output feedback stabilization for a class of stochastic nonlinear systems with time-varying delay

This paper studies the global sampled-data output feedback stabilization problem for a class of stochastic nonlinear systems. The considered system is in non-strict feedback form with unknown time-varying delay. A state observer is introduced to estimate the unmeasured states. With the help of the backstepping method, a linear sampled-data output feedback controller is constructed. By choosing an appropriate Lyapunov–Krasoviskii functional and an allowable sampling period, it is shown that the stochastic system can be globally asymptotically stabilized in the mean square sense under the developed control scheme. Finally, two examples are presented to verify the effectiveness of the designed control scheme.     

Decentralized adaptive neural control for interconnected stochastic nonlinear delay-time systems with asymmetric saturation actuators and output constraints

This paper investigates the problem of decentralized adaptive backstepping control for a class of large-scale stochastic nonlinear time-delay systems with asymmetric saturation actuators and output constraints. Firstly, the Gaussian error function is employed to represent a continuous differentiable asymmetric saturation nonlinearity, and barrier Lyapunov functions are designed to ensure that the output parameters are restricted. Secondly, the appropriate 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. At last, based on Lyapunov stability theory, a decentralized adaptive neural control method is proposed, and the designed controller decreases the number of learning parameters. It is shown that the designed controller can ensure that all the closed-loop signals are 4-Moment (or 2 Moment) semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of the origin. Two examples are provided to show the effectiveness of the proposed method.     

Input–output decoupling control design for switched Boolean control networks

We investigate the input–output decoupling problem of switched Boolean control networks (SBCNs) in this paper. Based on the matrix expression of Boolean functions, the dynamics of SBCNs are converted into an algebraic form via semi-tensor product of matrices first. Then, using the redundant variable separation technique, we give the necessary and sufficient conditions for the existence of three kinds of controllers to detect whether an SBCN can be input–output decomposed or not, respectively, including the open-loop controllers, the state feedback controllers, and the output feedback controllers. Meanwhile, a constructive procedure is presented to construct the open-loop controllers, as well as the state feedback controllers and output feedback controllers. Finally, an illustrative example is given to show that the new results obtained are effective.     

Event-based reference tracking control of discrete-time nonlinear systems via delta operator method

This paper investigates the event-based tracking control for delta-sampling systems with a reference model. Takagi–Sugeno (T–S) fuzzy model is used to approximate the nonlinearity. The delta operator is used to implement the discrete-time system. The event trigger is adopted for saving the network resources and the controller forces, and its detection period is designed with the same period of the delta-sampling period. Since the measurement is delayed from the sensor to the event-trigger, the methodology of time-delay systems, called the scaled small gain theorem, is applied for the system stability analysis. The reference output tracking controller is designed to ensure the stability of the resulting system in H_∞ sense. The optimization conditions of the desired H_∞ event-based tracking controller are synthesized, and the simulation example validates its effectiveness finally.     

Observer-based exponential stabilization for time-delay systems via augmented weighted integral inequality

In this paper, we design observer-based feedback control for a class of linear systems. The novelty of the paper comes from the consideration of an augmented weighted based integral inequality involving quadratic functions with an exponential term which is less conservative than the celebrated weighted integral inequality employed in the context of time-delay systems. By using appropriately chosen Lyapunov–Krasovskii functional (LKF), together with the derived integral inequality, a new sufficient condition for exponential stability in terms of linear matrix inequalities (LMIs) is proposed for the delayed linear systems with state feedback control. Finally, the applicability and superiority of the proposed theoretical results over the existing ones are analyzed in virtue of numerical examples.