Binary ABR flow control over ATM networks with uncertainty using discrete-time variable structure controller

A binary available bit rate （ABR） scheme based on discrete-time variable structure control （DVSC） theory is proposed to solve the problem of asynchronous transfer mode （ATM） networks congestion in this paper. A discrete-time system model with uncertainty is introduced to depict the time-varying ATM networks. Based on the system model, an asymptotically stable sliding surface is designed by linear matrix inequality （LMI）. In addition, a novel discrete-time reaching law that can obviously reduce chatter is also put forward. The proposed discrete-time variable structure controller can effectively constrain the oscillation of allowed cell rate （ACR） and the queue length in a router. Moreover, the controller is self-adaptive against the uncertainty in the system. Simulations are done in different scenarios. The results demonstrate that the controller has better stability and robustness than the traditional binary flow controller, so it is good for adequately exerting the simplicity of binary flow control mechanisms.

Approximation law for discrete-time variable structure control systems

Two approximation laws of sliding mode for discrete-time variable structure control systems are proposed to overcome the limitations of the exponential approximation law and the variable rate approximation law. By applying the proposed approximation laws of sliding mode to discrete-time variable structure control systems, the stability of origin can be guaranteed, and the chattering along the switching surface caused by discrete-time variable structure control can be restrained effectively. In designing of approximation laws, the problem that the system control input is restricted is also considered, which is very important in practical systems. Finally a simulation example shows the effectiveness of the two approximation laws proposed.

Variable structure control with sliding mode prediction for discrete-time nonlinear systems

A new variable structure control algorithm based on sliding mode prediction for a class of discrete-time nonlinear systems is presented. By employing a special model to predict future sliding mode value, and combining feedback correction and receding horizon optimization methods which are extensively applied on predictive control strategy, a discrete-time variable structure control law is constructed. The closed-loop systems are proved to have robustness to uncertainties with unspecified boundaries. Numerical simulation and pendulum experiment results illustrate that the closed-loop systems possess desired performance, such as strong robustness, fast convergence and chattering elimination.

APPROXIMATION LAWS OF DISCRETE-TIME VARIABLE STRUCTURE CONTROL SYSTEMS

Two new approximation laws of sliding mode for discrete-time variable structure control systems are proposed in this paper. By applying the proposed approximation laws of sliding mode to discrete-time variable structure control systems,the stability of origin can be guaranteed,and the chattering along the switching surface caused by discrete-time variable structure control can be restrained effectively. In designing of these approximation laws,the problem that the system control input is restricted is also considered,which is very important in practical systems. Finally two simulation examples showing the effectiveness of the approximation laws are proposed.

Adaptive Variable Structure Control of MIMO Nonlinear Systems with Time-varying Delays and Unknown Dead-zones

In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.

Sliding Mode Variable Structure Control for Visual Servoing System

A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.

An Approach to Polynomial NARX/NARMAX Systems Identification in a Closed-loop with Variable Structure Control

Many physical processes have nonlinear behavior which can be well represented by a polynomial NARX or NARMAX model. The identification of such models has been widely explored in literature. The majority of these approaches are for the open-loop identification. However, for reasons such as safety and production restrictions, open-loop identification cannot always be done. In such cases, closed-loop identification is necessary. This paper presents a two-step approach to closed-loop identification of the polynomial NARX/NARMAX systems with variable structure control （VSC）. First, a genetic algorithm （GA） is used to maximize the similarity of VSC signal to white noise by tuning the switching function parameters. Second, the system is simulated again and its parameters are estimated by an algorithm of the least square （LS） family. Finally, simulation examples are given to show the validity of the proposed approach.

ADAPTIVE VARIABLE STRUCTURE CONTROLLERS AND APPLICATION TO ENGINE IDLE SPEED CONTROL SIMULATION

A neural-network-based adaptive variable structure control methodology isproposed for the tracking problem of nonlinear discrete-time input-output systems. The unknowndynamics of the system are approximated via radial basis function neural networks. The control lawis based on sliding modes and simple to implement. The discrete-time adaptive law for tuning theweight of neural networks is presented using the adaptive filtering algorithm with residueupper-bound compensation. The application of the proposed controller to engine idle speed controldesign is discussed. The results indicate the validation and effectiveness of this approach.

Nonlinear and Variable Structure Excitation Controller for Power System Stability

A new nonlinear variable structure excitation controller is proposed. Its design combines the differential geometry theory and the variable structure controlling theory. The mathematical model in the form of ＂an affme nonlinear system＂ is set up for the control of a large-scale power system. The static and dynamic performances of the nonlinear variable structure controller are simulated. The response of system with the controller proposed is compared to that of the nonlinear optimal controller when the system is subjected to a variety of disturbances. Simulation results show that the nonlinear variable structure excitation controller gives more satisfactorily static and dynamic performance and better robustness.

Fault detection and accommodation via neural network and variable structure control

This paper proposes a novel idea that classifies faults into two different kinds： serious faults and small faults, and treats them with different strategies respectively. A kind of artificial neural network （ANN） is proposed for detecting serious faults, and variable structure （VS） model-following control is constructed for accommodating small faults. The proposed framework takes both advantages of qualitative way and quantitative way of fault detection and accommodation. Moreover, the uncertainty case is investigated and the VS controller is modified. Simulation results of a remotely piloted aircraft with control actuator failures illustrate the performance of the developed algorithm.

A Novel Genetic Algorithm and Its Application in Variable Structure Control of Robot

A novel genetic algorithm (NGA) is proposed, which possesses micro-regulation and renascence operation. The optimized variable searching interval is regulated gradually according to the sub-group of excellent individuals. The NGA is used to optimize the parameters of the variable structure control (VSC), which satisfies the new reaching law and sliding mode. It is used in robot control systems. Simulation results are given.

PREDICTIVE VARIABLE STRUCTURE CONTROL FOR A CLASS OF NONLINEAR SYSTEM

Nonlinear sliding m ode predictive controller is designed for a class of nonlinear system w ith unm odeled dynam ic characteristics and nonlinear term . The m ethod is based on nonlinear opti- m alpredictive control. The variable structure controllaw m inim izes the quadratic index ofa predic- tive sliding m ode, w hich contains thecostfunction ofcontrolpreventing the controleffectfrom satu- ration for in m ostpracticalim plem entation the controlinputs are bounded by physicalconstraints and energy constraints. According to the im m easurable states, the variable structure observer for nonlin- ear system sisadapted. The variablestructure system m ethod isaptto therealization ofobserverw ith variable param eters and uncertainty. The proofshow s thatthe states ofthe observer asym ptotically convergence to the realstates ofthe system although itisofuncertainty and nonlinear term s. Final- ly, the digitalsim ulation results prove the effectiveness ofthe proposed m ethod.

VARIABLE STRUCTURE CONTROL APPLIED IN ELECTRO-HYDRAULIC SERVO SYSTEM WITH ANN

The variable structure control （VSC） theory is applied to the electro-hydraulic servo system here. The VSC control law is achieved using Lyapunov method and pole placement. To eliminate the chattering phenomena, a saturation function is adopted. The proposed VSC approach is fairly robust to load disturbance and system parameter variation. Since the distortion. including phase lag and amplitude attenuation occurs in the system sinusoid response, the amplitude and phase control （APC） algorithm, based on Adaline neural network and using LMS algorithm, is developed for distortion cancellation. The APC controller is simple and can on-line adjust, thus it gives accurate tracking.

Adaptive variable structure control for large-scale time-delayed systems with unknown nonlinear dead-zone

The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors axe adopted to minimize the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.

Decentralized Variable Structure Control of Complex Giant Singular Uncertainty Systems

This paper, at the first time, considers the problem of decentralized variable structure control of complex giant singular uncertainty systems by using the property of diagonally dominant matrix and Frobenius-Person theorem. The splendid selection of switching manifold for each subsystem makes the design relatively straightforward and can be easily realized. An illustrate example is given.

Adaptive variable structure control based on backstepping for spacecraft with reaction wheels during attitude maneuver

An adaptive variable structure control method based on backstepping is proposed for the attitude maneuver problem of rigid spacecraft with reaction wheel dynamics in the presence of uncertain inertia matrix and external disturbances. The proposed control approach is a combination of the backstepping and the adaptive variable structure control. The cascaded structure of the attitude maneuver control system with reaction wheel dynamics gives the advantage for applying the backstepping method to construct Lyapunov functions. The robust stability to external disturbances and parametric uncertainty is guaranteed by the adaptive variable structure control. To validate the proposed control algorithm, numerical simulations using the proposed approach are performed for the attitude maneuver mission of rigid spacecraft with a configuration consisting of four reaction wheels for actuator and three magnetorquers for momentum unloading. Simulation results verify the effectiveness of the proposed control algorithm.

Variable Structure Model Reference Adaptive Control with Unknown High Frequency Gain Sign

可变结构模型引用为有比一个和未知高频率获得符号大的相对的度的工厂的适应控制被建议。一个切换的计划基于为靠近的环系统的第一个辅助错误设计的监视功能被介绍。在至多切换和追踪的错误的一个有限数字收敛到能被适当地选择一些设计参数使任意地小的一个剩余集合以后，在监视函数的管理下面，切换停止，这被显示出在至多切换和追踪的错误的一个有限数字收敛到能被适当地选择一些设计参数使任意地小的一个剩余集合以后。

Design of Neural Network Variable Structure Reentry Control System for Reusable Launch Vehicle

A flight control system is designed for a reusable launch vehicle with aerodynamic control surfaces and reaction control system based on a variable-structure control and neural network theory.The control problems of coupling among the channels and the uncertainty of model parameters are solved by using the method.High precise and robust tracking of required attitude angles can be achieved in complicated air space.A mathematical model of reusable launch vehicle is presented first,and then a controller of flight system is presented.Base on the mathematical model,the controller is divided into two parts:variable-structure controller and neural network module which is used to modify the parameters of controller.This control system decouples the lateraldirectional tunnels well with a neural network sliding mode controller and provides a robust and de-coupled tracking for mission angle profiles.After this a control allocation algorithm is employed to allocate the torque moments to aerodynamic control surfaces and thrusters.The final simulation shows that the control system has a good accurate,robust and de-coupled tracking performance.The stable state error is less than 1°,and the overshoot is less than 5%.

Design of variable structure controller for uncertain time-delay singular system

To study the approximation theory of real sliding mode and the design of variable structure controller for time-invariant linear uncertain time-delay singular system,the approximation theory of real sliding mode was developed to provide foundation for obtaining sliding mode by equivalent control,and switching functions with integral dynamic compensators and variable structure controllers were designed respectively under two circumstances that the system without uncertain part was stabilized by delay-dependent and delay-independent linear state feedback. The design guarantees the asymptotical stablity of switching manifolds,and the variable structure controllers can force solution trajectory of the system to arrive at the switching manifolds in limited time. A numerical example is given to demonstrate the feasibility and simplicity of the design method.

Structure identification of an uncertain network coupled with complex-variable chaotic systems via adaptive impulsive control

In this paper, structure identification of an uncertain network coupled with complex-variable chaotic systems is in- vestigated. Both the topological structure and the system parameters can be unknown and need to be identified. Based on impulsive stability theory and the Lyapunov function method, an impulsive control scheme combined with an adaptive strategy is adopted to design effective and universal network estimators. The restriction on the impulsive interval is relaxed by adopting an adaptive strategy. Further, the proposed method can monitor the online switching topology effectively. Several numerical simulations are provided to illustrate the effectiveness of the theoretical results.