Robust stability analysis for a cruise missile

A global controller design methodology for a flight stage of the cruise missile is proposed. This methodology is based on the method of least squares, To prove robust stability in the full airspace with parameter disturbances, the concepts of convex polytopic models and quadratic stability are introduced, The effect of aerodynamic parameters on system performance is analyzed. The designed controller is applied to track the overloading signal of the cruise segment of the cruise missile, avoiding system disturbance owing to controller switching, Simulation results demonstrate the validity of the proposed method.     

Best weight pattern evaluation based security constrained power dispatch algorithm

This paper presents a methodology which determines the allocation of power demand among the committed generating units while minimizes number of objectives as well as meets physical and technological system constraints. The procedure considers two decoupled problems based upon the dependency of their goals on either active power or reactive power generation. Both the problems have been solved sequentially to achieve optimal allocation of active and reactive power generation while minimizes operating cost, gaseous pollutants emission objectives and active power transmission loss with consideration of system operating constraints along with generators prohibited operating zones and transmission line flow limits. The active and reactive power line flows are obtained with the help of generalized generation shift distribution factors （GGDF） and generalized Z-bus distribution factors （GZBDF）, respectively. First problem is solved in multi-objective framework in which the best weights assigned to objectives are determined while employing weighting method and in second problem, active power loss of the system is minimized subject to system constraints. The validity of the proposed method is demonstrated on 30-bus IEEE power system.     

A New Discipline of Science-The Study of Open Complex Giant System and Its Methodology

This paper introduces the conception of open complex giant system and the methodology for dealing with the system, with stress on its profound significance in development of science and technology. The authors conclude that the reductionism underlying the exact science is not suitable to open complex giant system, and the only feasible alternative is the meta-synthetic engineering from the qualitative to the quantitative.     

Convergence of Self-Tuning Regulators Under Conditional Heteroscedastic Noises with Unknown High-Frequency Gain

In the classical theory of self-tuning regulators, it always requires that the conditional variances of the systems noises are bounded. However, such a requirement may not be satisfied when modeling many practical systems, and one significant example is the well-known ARCH(autoregressive conditional heteroscedasticity) model in econometrics. The aim of this paper is to consider self-tuning regulators of linear stochastic systems with both unknown parameters and conditional heteroscedastic noises, where the adaptive controller will be designed based on both the weighted least-squares algorithm and the certainty equivalence principle. The authors will show that under some natural conditions on the system structure and the noises with unbounded conditional variances, the closed-loop adaptive control system will be globally stable and the tracking error will be asymptotically optimal.Thus, this paper provides a significant extension of the classical theory on self-tuning regulators with expanded applicability.     

Research on improved integrated FDD/FTC with effectiveness factors

This paper investigates the integrated fault detection and diagnosis(FDD) with fault tolerant control(FTC) method of the control system with recoverable faults.Firstly,a quasi-linear parameter-varying(QLPV) model is set up,in which effectiveness factors are modeled as time-varying parameters to quantify actuators and sensors faults.Based on the certainty equivalency principle,replacing the real time states in the nonlinear term of the QLPV model with the estimated states,the parameters and states can be estimated by a two-stage Kalman filtering algorithm.Then,a polynomial eigenstructure assignment(PEA) controller with time-varying parameters and states is designed to guarantee the performance of the system with recoverable faults.Finally,mathematical simulation is performed to validate the solution in a satellite closed-loop attitude control system,and simulation results show that the solution is fast and effective for on-orbit real-time computation.     

Research for the orientation detection system using L-shape reticle

The basic scheme of the orientation detection system using L-shape reticle is introduced. The dimension of the patterns on the reticle of the system in practical applications is designed and an analysis of the principle of abstracting the orientation information of the target and the effects and formation method of self-adapting tracking gate is presented. The research result shows that the orientation detection system using L-shape reticle has a good effect on space-filtering, the signals that the orientation detection system sends out are easy to be processed by computer, its self-adapting tracking gate has a strong anti-interference ability, and the whole system＇s searching and tracking performances are quite high.     

PREDECESSOR-SET TECHNIQUE FOR RELIABILITY EVALUATION OF A STOCHASTIC MANUFACTURING SYSTEM

This paper studies the reliability evaluation of a stochastic manufacturing system with multiple production lines in parallel.Multiple repairs and different failure rates,never simultaneously addressed in earlier works,are taken into account.First,a revised graphical methodology integrating transformation and decomposition is utilized to construct the stochastic manufacturing system as a multi-state manufacturing network(MSMN).In particular,a "predecessor-set" technique is proposed to deal with multiple repairs.An algorithm is proposed to generate the lowest capacity vectors(LCVs)that stations should provide to satisfy the workloads.Subsequently,the system reliability of the MSMN,which is defined as the probability of demand satisfaction,is calculated in terms of the LCVs.A real case of a printed circuit board manufacturing system is utilized to demonstrate how the system reliability can be evaluated.A further decision making issue is addressed based on the derived system reliability.     

On Robust Stability of a Class of Uncertain Nonlinear Systems with Time—Varying Delay

The problem of robust stability of a class of uncertain nonlinear dynamical systems with time-delay is considered. Based on the assumption that the nominal system is stable, some sufficient conditions on robust stability of uncertain nonlinear dynamical systems with time-delay are derived. Some analytical methods and a type of Lyapunov functional are used to investigate such sufficient conditions. The results obtained in this paper are applicable to perturbed time-delay systems with unbounded time-varying delay. Some previous results are improved and a numerical example is given to demonstrate the validity of our results.     

Adaptive monopulse beamforming with partial parallel structure

A new recursive algorithm with the partial parallel structure based on the linearly constrained minimum variance (LCMV) criterion for adaptive monopulse systems is proposed. The weight vector associated with the original whole antenna array is decomposed into several adaptive weight sub-vectors firstly. An adaptive algorithm based on the conventional LCMV principle is then deduced to update the weight sub-vectors for sum and difference beam, respectively. The optimal weight vector can be obtained after convergence. The required computational complexity is evaluated for the proposed technique, which is on the order of O(N) and less than that of the conventional LCMV method. The flow chart scheme with the partial parallel structure of the proposed algorithm is introduced. This scheme is easy to be implemented on a distributed computer/digital signal processor (DSP) system to solve the problems of the heavy computational burden and vast data transmission of the large-scale adaptive monopulse array. Then, the monopulse ratio and convergence rate of the proposed algorithm are evaluated by numerical simulations. Compared with some recent adaptive monopulse estimation methods, a better performance on computational complexity and monopulse ratio can be achieved with the proposed adaptive method.     

Research of robust adaptive trajectory linearization control based on T-S fuzzy system

A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.     

CONSTRUCTING AN ACCESS SYSTEM FOR UNBANKED IN MYANMAR TO A MICROFINANCE INSTITUTION

In Myanmar,the formal financial institution does not provide uncollateralized credits.The rural unbanked under the poverty line is depending on the informal money-lenders with high interest rate.Private Agency Collaboration Together is only one microfinance institution providing the credits without collateral and with low interest rate to the unbanked in Myanmar.Half of the unbanked are unable to borrow the loans from the microfinance institution because of the weakness of the information contribution and the strict legal policies of the microfinance institution.Therefore,the objective of this study is to construct a system to improve the relationship between the microfinance institution and the unbanked by reducing the obstacles in the current system of microfinance institution.The legal policy is studied from the vision of the local unbanked as the originality of this research and the /-System methodology is applied to accomplish the research.The current system comprises the information contribution,loans and legal policies.The current system is only one relationship between the microfinance institution and unbanked.When the ten obstacles occurred in the current system,the unbanked cannot approach to the microfinance institution.An access system including four sub-systems is developed depending on the collected ideas to solve these obstacles and intend to improve the relationship between microfinance institution and the unbanked.     

Dynamic Characteristics of Inter-Satellite Links in LEO Networks

To establish an efficient inter-satellite link (ISL) in an LEO network, the effect of geometric characteristics of ISL on the ISLs and the devices on the LEO satellite should be examined. Because of the continuous movement of the LEO satellite, the time-varying behaviours of the ISL's geometric charactersistics continuously change with the changes of the satellite's position on the orbit. These dynamic geometric characteristics of the ISLs are important for ISL's performance analyzing and the design of the devices on the LEO satellite. This paper describes dynamic geometric characteristics of ISL, analyzes the impact of these regulations on the tracking system of the satellite's antenna and the power adjusting system of the satellite's transmitter, with the Iridium system as an example.     

Study on the Generation of Ultra-Wideband (UWB) High Power Microwave

The experimental study of ultra-wideband (UWB) technology, its generation and on-line measurement are presented. An experimental repetitive UWB system is designed, manufactured, and tested. High-pressure spark gap switch and its components, as well as oil spark gap switch are studied experimentally on the system. Experimental results indicate that the system operates at a 200 pps repetitive rate with a stable performance. 100 MW peak power UWB pulses are obtained on the system. Fast-time response capacitive divider is designed and fabricated, allowing for an accurate measurement of the high power UWB signal. The main issues related to the design of the switch and the UWB signal online measurement are discussed.     

Research on robust fault-tolerant control for networked control system with packet dropout

A kind of networked control system with network-induced delay and packet dropout, modeled on asynchronous dynamical systems was tested, and the integrity design of the networked control system with sensors failures and actuators failures was analyzed using hybrid systems technique based on the robust fault-tolerant control theory. The parametric expression of controller is given based on the feasible solution of linear matrix inequality. The simulation results are provided on the basis of detailed theoretical analysis, which further demonstrate the validity of the proposed schema.     

Finite-time tracking control for motor servo systems with unknown dead-zones

A finite-time tracking control scheme is proposed in this paper based on the terminal slid- ing mode principle for motor servo systems with unknown nonlinear dead-zone inputs. By using the differential mean value theorem, the dead-zone is represented as a time-varying system and thus the inverse compensation approach is avoided. Then, an indirect terminal sliding mode control （ITSMC） is developed to guarantee the finite-time convergence of the tracking error and to overcome the singu- larity problem in the traditional terminal sliding mode control. In the proposed controller design, the unknown nonlinearity of the system is approximated by a simple sigmoid neural network, and the ap- proximation error is diminished by employing a robust term. Comparative experiments on a turntable servo system are conducted to show the superior performance of the proposed method.     

CRUDE OIL PRICE FORECASTING WITH TEI@I METHODOLOGY

The difficulty in crude oil price forecasting, due to inherent complexity, has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forecasting crude oil prices. However, all of the existing models of prediction can not meet practical needs. Very recently, Wang and Yu proposed a new methodology for handling complex systems-TEI@I methodology by means of a systematic integration of text mining, econometrics and intelligent techniques.Within the framework of TEI@I methodology, econometrical models are used to model the linear components of crude oil price time series (i.e., main trends) while nonlinear components of crude oil price time series (i.e., error terms) are modelled by using artificial neural network (ANN) models. In addition, the impact of irregular and infrequent future events on crude oil price is explored using web-based text mining (WTM) and rule-based expert systems (RES) techniques. Thus, a fully novel nonlinear integrated forecasting approach with error correction and judgmental adjustment is formulated to improve prediction performance within the framework of the TEI@I methodology. The proposed methodology and the novel forecasting approach are illustrated via an example.     

On Stabilization of It Stochastic Time-Varying Systems

The stabilization with receding horizon control(RHC) of It stochastic time-varying systems is studied in this paper. Based on monotonically non-increasing of optimal cost and stochastic Lyapunov stability theory, a necessary and sufficient stabilization condition on the terminal weighting matrix is proposed, which guarantees the mean-square stability of the closed-loop system. The explicit receding horizon controller is obtained by employing stochastic maximum principle. Simulations demonstrate the effectiveness of the proposed method.     

Class of modified parallel combined methods of real-time numerical simulation for a stiff system

A class of modified parallel combined methods of real-time numerical simulation are presented for a stiff dynamic system. By combining the parallelism across the system with the parallelism across the method, and relaxing the dependence of stage value computation on sampling time of input function, a class of modified real-time parallel combined methods are constructed. Stiff and nonstiff subsystems are solved in parallel on a parallel computer by a parallel Rosen-brock method and a parallel RK method, respectively. Their order conditions and convergences are discussed. The numerical simulation experiments show that this class of modified algorithms can get high speed and efficiency.     

Neural network-based H∞ filtering for nonlinear systems with time-delays

A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed. Firstly, neural networks are employed to approximate the nonlinearities. Next, the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion （LDI）. Finally, based on the LDI model, a neural network-based nonlinear filter （NNBNF） is developed to minimize the upper bound of H∞ gain index of the estimation error under some linear matrix inequality （LMI） constraints. Compared with the existing nonlinear filters, NNBNF is time-invariant and numerically tractable. The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example.