Robust H∞ Control of Hamiltonian System with Uncertainty

This paper investigates the robust H∞ problem for a class of generalized forced Hamiltonian systems with uncertainties. The robust L2-gain was proved for the Hamiltonian with a sufficient condition for stable control of multimachine power systems expressed as a matrix algebraic inequality. A similar sufficient condition was then extended to the robust H∞ control of Hamiltonian systems to construct the state feedback H∞ control law. A numerical example is given to verify the validity of the proposed control scheme, which shows the effectiveness and promising application of the method.     

不确定离散网络控制系统的H∞鲁棒控制

This paper is concerned with an H∞ robust control for a class of Networked Control Systems (NCSs) with uncertain discrete. The NCSs with bounded network-induced and data packet dropout were modeled as closed-loop systems with time-varying input delay. By using a new Lyapunov-Krasovskii function and combining Jessen inequality and reciprocal convex technique, a sufficient condition which asymptotically robust stabilizes closed-loop systems and satisfies H∞ performance index was derived. Compared with the existing literature,This study needs fewer Linear Matrix Inequality(LMI) and matrix variables. Therefore, the result obtained lower conservativeness. Finally, the robust H∞ controller design was obtained with an improved cone complementarity linearization algorithm(ICCL). MATLAB simulation results have shown the effectiveness of the proposed method.     

Adaptive synchronization of neural networks with different attractors

This paper aims to present an adaptive control scheme for the synchronization of two classes of uncertain neural networks with different attractors. A new sufficient condition for the global synchronization of two kinds of neural networks with different attractors is derived. The proposed control method is efficient and easy to be implemented. Numerical simulation is used to show the effectiveness of the obtained result.     

Adaptive synchronization of neural networks with different attractors

This paper aims to present an adaptive control scheme for the synchronization of two classes of uncertain neural networks with different attractors. A new sufficient condition for the global synchronization of two kinds of neural networks with different attractors is derived. The proposed control method is efficient and easy to be implemented. Numerical simulation is used to show the effectiveness of the obtained result.     

Adaptively robust filtering with classified adaptive factors

The key problems in applying the adaptively robust filtering to navigation are to establish an equivalent weight matrix for the measurements and a suitable adaptive factor for balancing the contributions of the measurements and the predicted state information to the state parameter estimates. In this paper, an adaptively robust filtering with classified adaptive factors was proposed, based on the principles of the adaptively robust filtering and bi-factor robust estimation for correlated observations. According to the constant velocity model of Kalman filtering, the state parameter vector was divided into two groups, namely position and velocity. The estimator of the adaptively robust filtering with classified adaptive factors was derived, and the calculation expressions of the classified adaptive factors were presented. Test results show that the adaptively robust filtering with classified adaptive factors is not only robust in controlling the measurement outliers and the kinematic state disturbing but also reasonable in balancing the contributions of the predicted position and velocity, respectively, and its filtering accuracy is superior to the adaptively robust filter with single adaptive factor based on the discrepancy of the predicted position or the predicted velocity.     

H∞ Theory and its Application to the Position of Rolling Mill Control System

The controller designed according to classical or modern control theory will not satisfy the performance requirements when the controlled object in industrial field can not be described by exact mathematical model or the disturbance of the controlled system. In order to make the controlled system stable and having good performance, H∞ control theory was put forward to solve this practical problem. Taking the position of a rolling mill as the controlled object, it was rectified by optimal engineering way. Then, three different plans were put forward according to Bang-Bang control, LQ control and H∞ control, respectively. The result of the simulation shows that the controller designed according to H∞ method whose robust performance and ability to restrain colors disturbance is satisfactory.     

Fault-Tolerant Control for a Class of Uncertain Systems with Actuator Faults

The problem of fault-tolerant controller design for a class of polytopic uncertain systems with actuator faults is studied in this paper. The actuator faults are presented as a more general and practical continuous fault model. Based on the affine quadratic stability (AQS), the stability of the polytopic uncertain system is replaced by the stability at all corners of the polytope. For a wide range of problems including H∞ and mixed H 2 /H∞ controller design, sufficient conditions are derived to guarantee the robust stability and performance of the closed-loop system in both normal and fault cases. In the framework of the linear matrix inequality (LMI) method, an iterative algorithm is developed to reduce conservativeness of the design procedure. The effectiveness of the proposed design is shown through a flight control example.     

Robust H_∞ Control of Uncertain Linear Systems with Multiple State Delays—LMI Approach

This paper deals with the problem of robust H∞ control for uncertain systems with multiple state delays. The parameter uncertainties are unknown but norm - bounded. An LMI based method is developed for robust H∞ stabilization for a class of uncertain systems with multiple state delays via linear memoryless state feedback control. The resuits depend on the size of the delays and are given in terms of linear matrix inequalities, so they are less con. servative than those of delay - independent.     

Robust H∞ Filter Design for a Class of Uncertain Linear Systems with Time—delayed Measurement

A robust H∞ approach to filtering for a class of uncertain linear systems with time-delayed measurement is investigated.The parameter uncertainties are described by real time-varying norm-bounded form.A methodology is developed for designing linear filters such that the filtering process remains robustly stable and the transfer function from the disturbance inputs to error state outputs meets the prescribed H∞-bound constraints.The filter can be obtained and parameterized by solving two Riccati equations based on the lemma of robust stability for control system with delay.Simulation example proves the method to be effective and feasible.     

A New Genetic Algorithm Based on Niche Technique and Local Search Method

The genetic algorithm has been widely used in many fields as an easy robust global search and optimization method. In this paper, a new generic algorithm based on niche technique and local search method is presented under the consideration of inadequacies of the simple genetic algorithm. In order to prove the adaptability and validity of the improved genetic algorithm, optimization problems of multimodal functions with equal peaks, unequal peaks and complicated peak distribution are discussed. The simulation results show that compared to other niching methods, this improved genetic algorithm has obvious potential on many respects, such as convergence speed, solution accuracy, ability of global optimization, etc.     

Construction Process Control of Large Extra Caissons

The complexity of geotechnical engineering and variability in construction circumstances of large extra caissons make the problem of maintaining appropriate sink attitude quite difficult, especially in keeping sink uniformity and achieving the expected final sink depth. A new construction control method is presented using H∞ theory, considering uncertainties in the mechanics model and external noise in the construction site parameters. The design method of an H∞ controller has consequently been obtained for large extra caissons. Control results using only constructor experiences are compared with simulation results using the H∞ controller for a practical engineering situation, which indicates that the H∞ controller is successful in maintaining sink uniformity, avoiding sink as well as in achieving the expected final sink depth.     

Parameter self-adaptive synchronization control for a kind of financial chaotic systems

A parameter adaptive control approach was applied to a kind of financial chaotic systems. According to Lyapunov stability theorem, synchronization of two financial chaotic systems with different certain parameters or the same uncertain parameters were implemented through designing proper control functions and using parameters selfadaptive control principle. The sufficient synchronization conditions of the two financial systems were obtained. Under the situation of the same uncertain parameters, the synchronization system has simpler controller and better performance. Numerical simulations show the effectiveness of the method.     

μ Synthesis Method for Robust Control of Uncertain Nonlinear Systems

μ synthesis method for robust control of uncertain nonlinear systems is propored, which is based on feedback linearization. First, nonlinear systems are linearized as controllable linear systems by I/O linearization,such that uncertain nonlinear systems are expressed as the linear fractional transformations (LFTs) on the generalized linearized plants and uncertainty.Then,linear robust controllers are obtained for the LFTs usingμsynthesis method based on H∞ optimization.Finally,the nonlinear robust controllers are constructed by combining the linear robust controllers and the nonlinear feedback.An example is given to illustrate the design.     

A self-adaptive synchronization controller for Liu chaotic systems

A kind of synchronization controller for Liu chaotic systems whose nonlinear components are subject to Lipschitz condition was proposed. By using Lyapunov function and linear matrix inequality technique, a selfadaptive synchronization controller was constructed for Liu chaotic systems. There are two components of our derived synchronization controller: linear and nonlinear component. Linear component is composed of errors of the state variables between drivingsystems and respondingstems, and nonlinear component is a selfadaptive synchronization controller. a proof was given for proving the feasibility of this method, and numerical simulations of Liu chaotic systems show its effectiveness. Furthermore, this method can be applied to other chaotic systems, such as Chen systems, Lorenz systems, Chua systems and Rssler systems,etc.     

Modified Projective Synchronization of a New Hyperchaotic System with Known or Unknown Parameters

This work presents two different methods-- nonlinear control method and adaptive control approach to achieve the modified projective synchronization of a new hyperchaotic system with known or unknown parameters. Based on Lyapunov stability theory, nonlinear control method is adopted when the parameters of driving and response systems are known beforehand; when the parameters are fully unknown, adaptive controllers and parameters update laws are proposed to synchronize two different hyperchaotic system and identify the unknown parameters. Moreover, the rate of synchronization can be regulated by adjusting the control gains designed in the controllers. The corresponding simulations are exploited to demonstrate the effectiveness of the proposed two methods.     

Detecting the breakup of spiral waves in small-world networks of neurons due to channel block

The breakup of a spiral wave by blockade of sodium and potassium channels in a small-world network of Hodgkin-Huxley neurons is investigated in detail.The influence of ion channel block in poisoned excitable membrane patches of a certain size is measured,by varying channel noise and channel densities resulting from the change in conductance,For example,tetraethylammonium is known to cause a block(poisoning) of potassium channels,while tetrodotoxin blocks sodium channels.We observed the occurrence of spiral waves,which are ordered waves believed to play an important role in facilitating the propagation of electric signals across quiescent regions of the brain.In this paper,the effect of channel block was measured by the factors xK and xNa,which represent the ratios of unblocked,or active,ion channels,to the overall number of potassium or sodium ion channels,respectively.To quantify these observations,we use a simple but robust synchronization measure,which succinctly captures the transition from spiral waves to other collective states,such as broken segments resulting from the breakup of the spiral wave.The critical thresholds of channel block can be inferred from the abrupt changes occurring in plots of the synchronization measure against different values of xK and xNa.Notably,small synchronization factors can be tightly associated with states where the formation of spiral waves is robust to mild channel block.     

An Order-oriented Procedure Model for A Robust and Agile Production System

The manufacturing industry in 1990's is faced with se-vere challenge among the global competition for mar-kets.Production for a small quantity and high varietyeven lot-sizes of one-digit numbers products has be-come a main trend today.Traditional production proce-dure limits the flexibility of the production system.Inthis paper,based on the analysis of the procedure charac-teristics,a design strategy for re-usage of informationand resource is introduced,and an order-oriented pro-cedure model with concurrent,hierarchical and micro-cycle structure for a robust and agile production systemis proposed in order to realize flexible and adaptive pro-duction for dynamically-changing orders.