H ∞ filtering for continuous-time systems with pointwise time-varying delay

The problem of H_∞filtering for continuous-time systems with pointwise time-varying delay is investigated in this paper.By applying an innovation analysis in Krein space,a necessary and sufficient condition for the existence of an H_∞filter is derived in two methods:One is the partial differential equation approach,the other is the reorganized innovation analysis approach.The former gives a solution to the proposed H_∞filtering problem in terms of the solution of a partial differential equation with boundary conditions.The later gives an analytical solution to the proposed H_∞filtering problem in terms of the solutions of Riccati and matrix differential equations.     

Robust fault diagnosis with disturbance rejection and attenuation for systems with multiple disturbances

The fault diagnosis problem is investigated for a class of nonlinear neutral systems with multiple disturbances.Time-varying faults are considered and multiple disturbances are supposed to include the unknown disturbance modeled by an exo-system and norm bounded uncertain disturbance.A nonlinear disturbance observer is designed to estimate the modeled disturbance.Then,the fault diagnosis observer is constructed by integrating disturbance observer with disturbance attenuation and rejection performances.The augmented Lyapunov functional approach,which involves the tuning parameter and slack variable,is applied to make the solution of inequality more flexible.Finally,applications for a two-link robotic manipulator system are given to show the efficiency of the proposed approach.     

H_∞ Control for Nonlinear Stochastic Markov Systems with Time-Delay and Multiplicative Noise

This paper is concerned with the H_∞ control problem for a class of nonlinear stochastic Markov jump systems with time-delay and system state-, control input-and external disturbancedependent noise. Firstly, by solving a set of Hamilton-Jacobi inequalities(HJIs), the exponential mean square H_∞ controller design of delayed nonlinear stochastic Markov systems is presented. Secondly,by using fuzzy T-S model approach, the H_∞ controller can be designed via solving a set of linear matrix inequalities(LMIs) instead of HJIs. Finally, two numerical examples are provided to show the effectiveness of the proposed design methods.     

New approach to eliminate structural redundancy in case resource pools using α mutual information

Structural redundancy elimination in case resource pools (CRP) is critical for avoiding performance bottlenecks and maintaining robust decision capabilities in cloud computing services. For these purposes, this paper proposes a novel approach to ensure redundancy elimination of a reasoning system in CRP. By using α entropy and mutual information, functional measures to eliminate redundancy of a system are developed with respect to a set of outputs. These measures help to distinguish both the optimal feature and the relations among the nodes in reasoning networks from the redundant ones with the elimination criterion. Based on the optimal feature and its harmonic weight, a model for knowledge reasoning in CRP (CRPKR) is built to complete the task of query matching, and the missing values are estimated with Bayesian networks. Moreover, the robustness of decisions is verified through parameter analyses. This approach is validated by the simulation with benchmark data sets using cloud SQL. Compared with several state-of-the-art techniques, the results show that the proposed approach has a good performance and boosts the robustness of decisions.     

Stackelberg Game Approach to Mixed H_2/H_∞ Problem for Continuous-Time System

This paper studies the mixed H_2/H_∞ control for continuous-time linear dynamic systems.By applying Stackelberg game approach, the control input is treated as the leader and the disturbance is treated as the follower, respectively. Under standard assumptions and maximum principle, a necessary and sufficient existence condition which is based on three decoupled Riccati equations is obtained.Explicit expression of controllers and solutions to forward backward differential equations(FBDES)are obtained by homogeneous analysis of variables. A numerical example is finally given to verify the efficiency of the proposed approach.     

New approach to multiple attribute decision making with interval numbers

In an ambiguous decision domain, the evaluation values of alternatives against attributes would be interval numbers because of the inherent, uncertain property of the problems. By using a number of linear programming models, Bryson and Mobolurin propose an approach to compute attribute weights and overall values of the alternatives in the form of interval numbers. The intervals of the overall values of alternatives are then transformed into points or crisp values for comparisons among the alternatives. However, the attribute weights are different because of the use of linear programming models in Bryson and Mobolurin＇s approach. Thus, the alternatives are not comparable because different attribute weights are employed to calculate the overall values of the alternatives. A new approach is proposed to overcome the drawbacks of Bryson and Mobolurin＇s approach. By transforming the decision matrix with intervals into the one with crisp values, a new linear programming model is proposed, to calculate the attribute weights for conducting alternative ranking.     

H_2/H_∞ Control for Stochastic Jump-Diffusion Systems with Markovian Switching

In this paper, a stochastic H_2/H_∞ control problem is investigated for Poisson jumpdiffusion systems with Markovian switching, which are driven by a Brownian motion and a Poisson random measure with the system parameters modulated by a continuous-time finite-state Markov chain.A stochastic jump bounded real lemma is proved, which reveals that the norm of the perturbation operator below a given threshold is equivalent to the existence of a global solution to a parameterized system of Riccati type differential equations. This result enables the authors to obtain sufficient and necessary conditions for the existence of H_2/H_∞ control in terms of two sets of interconnected systems of Riccati type differential equations.     

Fully Distributed Cooperative Motion of Group Robots

This paper is focused on the fully distributed cooperative motion of group robots and proposes a new approach. Each robot has a local sensing ability and a simple action selection strategy. Computational complexity is decreased by the fully distributed architecture and the information insufficiency is solved by the interaction between the robots and the environment. Variable loop and random method are used to deal with the fluctuation and equity selection problem and the rapidity and reasonabiliiy are guaranteed. Some simulations have proved the effectiveness of the proposed approach.     

Learning-based force servoing control of a robot with vision in an unknown environment

A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of the robot are derived and learned by a neural network. Secondly, a learning controller based on the neural network is designed for the robot to trace the object. Thirdly, a discrete time impedance control law is obtained for the force servoing of the robot, the on-line learning algorithms for three neural networks are developed to adjust the impedance parameters of the robot in the unknown environment. Lastly, wiping experiments are carried out by using a 6 DOF industrial robot with a CCD camera and a force/torque sensor in its end effector, and the experimental results confirm the effecti veness of the approach.     

High-resolution swath bathymetry using MIMO sonar system

For increasing the cross-track resolution, the multiple input multiple output （MIMO） technique is introduced into the swath bathymetry system and a new swath bathymetry approach using MIMO sonar is proposed. The MIMO sonar is composed of two parallel transmitting uniform linear arrays （ULAs） and a receiving ULA which is perpendicular to the former. The spacing between the two transmitting ULAs is equal to the product of the receiving sensor number and the receiving inter-sensor spacing. Furthermore, two narrowband linear frequency modulation （LFM） pulses, sharing the same frequency band but with opposite modulation slopes, are used as transmitting waveforms of the two transmitting ULAs. With such an array layout and transmitting signals, the MIMO sonar can sound a swath with the cross-track resolution doubling that of the traditional multibeam sonar using a Mills cross array. Numerical examples are provided to verify the effectiveness of the proposed approach.     

Multiobjective Decision Making: the Combined Approach

: In this paper, a new approach for generating all or partly efficient solutions called the Combined Approach is developed. The property of efficient solutions generated by the combined approach and its relationships with other four approaches: weighting approach, sequential approach, ε-constraint approach and hybrid approach, are discussed. Based on this combined approach, a decision-making support method called the Combined Decision-Making Method (CDMM) for multiobjective problems is developed, which is an interactive process with the decision maker. Only the aspiration levels, which reflect the decision maker's satisfying degrees for corresponding objectives, are needed to be supplied by the decision maker step by step as he will. This interactive way for objectives can easily be accepted. Finally, the application of the proposed decision making method in the resource allocation problem is discussed, and an example for the production decision analysis of the solar energy cells given.     

Adaptive fuzzy controller for a class of strict-feedback nonaffine nonlinear systems

A robust adaptive fuzzy control scheme is presented for a class of strict-feedback nonaffine nonlinear systems with modeling uncertainties and external disturbances by using a backstepping approach.Fuzzy logic systems are employed to approximate the unknown parts of the desired virtual controls,and the approximation errors of fuzzy systems are only required to be norm-bounded.The function tanh(·) is introduced to avoid problems associated with sgn(·).The tracking error is guaranteed to be uniformly ultimately bounded with the aid of an additional adaptive compensation term.Chua’s circuit system and R o¨ssler system are presented to illustrate the feasibility and effectiveness of the proposed control technique.     

EOQ Models for Deteriorating Items with Time-varying Demand and Partial Backorder under Inflation

This paper, through the discounted cash flow (DCF) approach, considers inventory replenishment problems for deteriorating items with general time-varying demand over a finite planning horizon under inflation. The optimal replenishment policies for the total profit of system to be maximum are presented with partial backlogging. Moreover, the fraction of demand backlogged is assumed to be a non-increasing function of waiting time. Firstly, the models with a fixed fraction backorder and complete backorder are provided. Then the model is presented with assuming that the fraction of demand backlogged is an exponentially decreasing function of waiting time. The solution procedures of models are proposed. The effect of inflation on the optimal policies is shown. The models are illustrated through numerical examples and sensitivity analysis of parameters is given.     

A GMRP Approach for Reliability Analysis of Repairable Systems

We propose here a mathematical approach for the study of repairable systems with arbitrary distributions. The idea is to define a new type of stochastic process, called a generalized Markov renewal process (GMRP). which may describe the transition behavior of the stochastic process at non-regenerative points. In the paper an analytical method for the GMRP is put forward and the formulas are then presented for reliability analysis of repairable systems which can be described by a GMRP with finite states. A signal flow graph technique for system modeling is also summarized here. Finally- an analytical model to evaluate the reliability of a m-out-of- n.G system with general repair-time distribution is developed by means of the GMRP approach.     

Stochastic maximum principle for mixed regular-singular control problems of forward-backward systems

This paper considers a stochastic optimal control problem of a forward-backward system with regular-singular controls where the set of regular controls is not necessarily convex and the regular control enters the diffusion coefficient. This control problem is difficult to solve with the classical method of spike variation. The authors use the approach of relaxed controls to establish maximum principle for this stochastic optimal control problem. Sufficient optimality conditions are also investigated.     

Exponential distribution-based genetic algorithm for solving mixed-integer bilevel programming problems

Two classes of mixed-integer nonlinear bilevel programming problems are discussed. One is that the follower＇s functions are separable with respect to the follower＇s variables, and the other is that the follower＇s functions are convex if the follower＇s variables are not restricted to integers. A genetic algorithm based on an exponential distribution is proposed for the aforementioned problems. First, for each fixed leader＇s variable x, it is proved that the optimal solution y of the follower＇s mixed-integer programming can be obtained by solving associated relaxed problems, and according to the convexity of the functions involved, a simplified branch and bound approach is given to solve the follower＇s programming for the second class of problems. Furthermore, based on an exponential distribution with a parameter λ, a new crossover operator is designed in which the best individuals are used to generate better offspring of crossover. The simulation results illustrate that the proposed algorithm is efficient and robust.     

Value of Commonality in Multiple Stage Assembly Products

This paper presents a systematic approach to estimate the value of commonality in products that involve multiple stage assemblies. In particular, the inventory savings are quantified with a mathematical model. The purpose is to assist product deisgn teams to make rational decisions in assigning unique parts or pursuing component standardization. In order to enhance the usability of the model, approximations are made to simplify the model and calculations.     

Decentralized adaptive fuzzy control of time-delayed interconnected systems with unknown backlash-like hysteresis

The problem of decentralized adaptive fuzzy control for a class of time-delayed interconnected nonlinear systems with unknown backlash-like hystersis is discussed. On the basis of the principle of variable structure control （VSC） and by using the fuzzy systems with linear adjustable parameters that are used to approximate plant unknown functions, a novel decentralized adaptive fuzzy control strategy with a supervisory controller is developed. A general method, which is modeled the backlash-like hysteresis, is proposed and removes the assumption that the boundedness of disturbance, and the slope of the backlash-like hystersis are known constants. Furthermore, the interconnection term is supposed to be pth-order polynomial in time-delayed states. In addition, the plant dynamic uncertainty and modeling errors are adaptively compensated by adjusting the parameters and gains on-line for each subsystems. By theoretical analysis, it is shown that the closed-loop fuzzy control systems are globally stable, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.     

Resilient predictive control for a class of uncertain time-delay systems

In practice, gain perturbations of controllers which are caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.