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.     

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.     

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.     

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.     

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.     

Robust Watermarking Scheme with Side Information and Template Matching Mechanism

Digital watermarking has been proposed for the copyright protections of multimedia products. In this paper, a robust and blind watermarking scheme is presented. The concept of communication with side in-formation is applied at the encoder to improve the probability of detection within acceptable fidelity, while the template matching technique is employed to estimate the undergone attacks in attacking channel. This scheme is optimized by the optimal design of the encoder to match with the media content and the decoder to adapt to the attack channel state. Experiments show that our method is robust against some common at-tacks such as filtering, compression, rotation, scaling, cropping and translation. It can be applied to both color and gray images.     

Reliable grading robust stabilization for uncertain time-varying systems via dynamic compensator

A new general model for uncertain time-varying parameters and a new measure sensor failure model are presented, and the problems of both grading robust stabilization and reliable grading robust stabilization for such systems are studied. By the Lyapunov stability theory and matrix algebra method, some sufficient criteria for the above two control problems are established in quasi-linear matrix inequalities (Q-LMIS) forms. In view of linear matrix inequality (LMI) approach, a solving procedure for the Q-LMIS problem is proposed. The solvability of the Q-LMIS problem can be improved obviously by adding some LMI constraints to the Q-LMIS. Based on the two Q-LMIS criteria, a grading robust stable control strategy, namely, the controller with different energy is acted on the system with different uncertain parameter range, is presented. The numerical simulating results show that the grading robust stable control strategy for the robust stabilization of uncertain systems has important theoretical and practical significance.     

Study on Bending of Woven Fabrics Using Linear Viscoelasticity Theory

The bending behavior of woven fabrics under low curva-ture conditions has been analyzed by linear viscoelastictheory.The fabric is assumed to behave viscoelasticallyand to be subjected to frictional restraints in bending de-formation.The frictional restraint is considered to beproportional to the curvature and can be described by africtional moment.A model has been constructed by astandard three-element solid model and a paralleledfrictional sliding element.The equations of the model fora cyclic curvature variation are derived.A set of param-eters of the equations for each fabric has been obtainedexperimentally.Predictions of the bending rigidity andhysteresis for wool,cashmere,wool/polyester blended,polyester and cotton fabrics are made,displaying verygood agreement with the experimental observations.     

Decentralized Stabilization of Large-scale Uncertain Systems with State-Delays——LMIs Approach

This paper deals with the problem of decentralized robustcontrol for a class of interconnected uncertain systemswith state delays.The parameter uncertainties are un-known but norm-bounded.A new sufficient condition isobtained for each subsystem and overall system to be sta-bilizable via linear memoryless state feedback robust de-centralized controllers.The results depend on the size of the delays and are given in terms of linear matrix ine-qualities,so they are less conservative than those of delay-independent.Moreover,matching condition is not a necessary condition.Finally,an example is presented to illustrative the effectiveness of the proposed method.     

Predictive PI control and its robust stability analysis

It is difficult to analyze robust BIBO stability of predictive PI (PPI) control system due to the time delay of process. A novel technique for stability analysis of this kind of system is proposed in this paper. The state space form of PPI control system is given, and its characteristic polynomial is derived by a simple method, so the robust BIBO stability analysis of this kind of system is also the analysis of corresponding characteristic polynomial. Applying Kharitonov theorem and edge theorem, the BIBO stability can be judged for arbitrarily given process parameter intervals. The system robust stability with variable process parameters is described respectively, and some beneficial conclusions for the design of PPI controller are obtained.     

Robust control for uncertain singular systems with time-varying delay

We study the problem of L2-L∞, control for a class of uncertain singular systems with time-delay and norm-bounded parameter uncer- tainties in this paper. A new delay-dependent robust stability criterion is obtained in terms of linear matrix inequalities （LMIs）. Based on this criterion, a state feedback controller is designed to guarantee that the closed-loop system is regular, impulse free and stable with a prescribed L2-L∞ performance satisfied for all admissible parameter uncertainties. A simulation example is included to illustrate the effectiveness of the proposed method.     

H∞ Filter Design for Linear Systems with Delays

This paper focuses on the problem of H∞ filter design for linear delayed systems.A new approach of filter design is proposed by using Lyapunov stability theory together with linear matrix inequality(LMI) approach.Some sufficient conditions for the existence of H∞ filter are established based on the solutions of a set of LMIs.Finally,two examples are given to demonstrate the effectiveness of the proposed method.     

Application of adaptive filtering by selecting the parameter weight factor in precise kinematic GPS positioning

A new method of adaptive filtering by selecting the parameter weight factor is introduced in this paper. Based on the theoretical analysis and research, this method is firstly used for precise kinematic GPS positioning with single frequency double-differenced (DD) carrier phase observations. Two numerical examples are given to illustrate the feasibility and validity of the method. The preliminary results show that precise positioning results can be obtained by using only the GPS single frequency DD carrier phase measurements for short baselines with the new method.     

Improved Square-Root UKF Algorithm for State Estimation of Nonlinear Systems

The square-root unscented Kalman filter (SR-UKF) for state estimation probably encounters the problem that Cholesky factor update of the covariance matrices can't be implemented when the zero'th weight of sigma points is negative or the numerical computation error becomes large during the filtering procedure.Consequently the filter becomes invalid.An improved SR-UKF algorithm (ISR-UKF) is presented for state estimation of arbitrary nonlinear systems with linear measurements.It adopts a modified form of predicted covariance matrices,and modifies the Cholesky factor calculation of the updated covariance matrix originating from the square-root covariance filtering method.Discussions have been given on how to avoid the filter invalidation and further error accumulation.The comparison between the ISR-UKF and the SR-UKF by simulation also shows both have the same accuracy for state estimation.Finally the performance of the improved filter is evaluated under the impact of model mismatch.The error behavior shows that the ISR-UKF can overcome the impact of model mismatch to a certain extent and has excellent trace capability.     

Delay-Dependent Exponential Stability of Stochastic Delayed Recurrent Neural Networks with Markovian Switching

The exponential stability problem is investigated for a class of stochastic recurrent neural networks with time delay and Markovian switching. By using Ito＇s differential formula and the Lyapunov stability theory, sufficient condition for the solvability of this problem is derived in term of linear matrix inequalities, which can be easily checked by resorting to available software packages. A numerical example and the simulation are exploited to demonstrate the effectiveness of the proposed results.     

Modeling and Control of Active Suspensions for MDOF Vehicle

The conventional method for analyzing active suspension control for a vehicle is only to analyze a quarter or half car with a lower order degree-of-freedom (DOF) model, but such models do not actually model practical applications. Accurate models of a suspension control system require a multi-degree-of-freedom (MDOF) vehicle model with a detailed model of the controller. An MDOF model was developed including the influence of factors such as the engine, the seats, and the passengers to describe vehicle motion using a reduced order model of the controller designed by using the H∞ control method. The control system performance has been investigated by comparing the H∞controller with a linear quadratic (LQ) controller.     

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.