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Wireless sensor and actuator networks (WSANs) facilitate close interactions between human and the environment. Efficient coordination among the sensors and actuators plays a vital role in carrying out sensing and acting in WSANs. In this paper, we develop a collaborative estimation and actuation mechanism, which consists of a sensor-actuator coordination phase and an actuator-actuator coordination phase. The first phase is based on distributed Kalman filter in federated configuration, which is able to provide reliable and precise sensing data. On this basis, the second phase allocates proper tasks based on system requirements and coordinates actuators to accomplish the tasks. Particularly, the actuator-actuator coordination is formulated as an optimization problem and an effective method is proposed to search the solution based on sequential unconstrained minimization technique. Simulation results demonstrate the effectiveness of our proposed mechanism.

In present computer networks, cyber attacks, such as compromising and energy depleting attacks, can cause malfunction or even failure of nodes, and can be significantly harmful to the convergence property of the average consensus algorithms. In this paper, we aim to distributively find the most critical nodes in the sense that removing it causes the largest destruction to the converging speed of an average consensus algorithm among all the nodes. The algebraic connectivity is used to assess the destruction and thus the importance of a node. We design two methods to estimate the algebraic connectivity and analyze their bounds for the estimation error. Based on this, we propose a fully distributed algorithm for the nodes to iteratively find the most critical one. Simulation results demonstrate the effectiveness of our algorithm.

The application of OMT, one of the most popular object-oriented development techniques, to the software development of O3CACSD - an open and integrated environment for Computer-Aided Control Systems Design (CACSD). is presented in this paper. How O3CACSD provides support for the entire cycle of control system design is shown by a concrete example - design of control systems for a torsional apparatus.

In this paper, the H∞performance problems of linear systems subject to two types of input saturation are considered respectively. A sufficient condition, which makes the closed-loop systems to be quadratic stable and satisfy the H∞performance prior given, is derived. According to this sufficient condition, a method is presented to design a static feedback controller for the plant in the present of input saturation. All the results are expressed by matrix inequalities

Smith predictor has been proved to be a useful scheme for stable processes with time delay. In this paper an analytical design method of Smith predictor is presented for integrator/time delay processes based on the theory of complex function. The design procedure incorporates a two-stage procedure. In the first stage, the controller that stabilizes the closed loop system is parameterized. In the second stage, high enough order Pade approximation is introduced to approximate the time delay, and convert the design problem of system with time delay to that of system without time delay. The optimal Smith predictor is then derived analytically. Examples are given to illustrate the method.

Robust sampled-data control for a class of nonlinear uncertain systems with prespecified time-domain performances is considered in this paper. Specified time-domain performances are described as the constraints on the states of system. A new notion of L2gain is also proposed for such constrained systems. First the constrained control for general sampled-data systems--impulsive systems or systems with jumps is considered in the paper based on the practical stability theory and the newly proposed notion of L2gain. Then robust sampled-data control for a class of nonlinear systems with constraints on the states is developed. The robust sampled-data controller is composed of the memoryless nonlinear part and the linear part. The linear part of sampled-data controller is solved from certain linear matrix differential inequality subject to the parametric conditions, which can be solved by Matlab LMITool, if the Lyapunov function can be specified as a certain types of piece-wise continuous functions.

In this paper, a multiple-model predictive control strategy is studied, which is based on a new model switching method. It combines multiple-model switching principle and predictive control method, and can be applied to the linear system with large model uncertainty. Simulation results show that the algorithm has good tracking and dynamic performance.

The problem considered here is to find the optimal service control policy for a serial production line with random demand. The workstations are reliable or unreliable. It is shown that the optimal policy is of bang-bang type by minimizing the expected discounted cost. For the two-WS system, the optimal control policy can be described by two switching curves and the asymptote properties of the optimal policy are derived.

A new idea and approach of robust optimal control for shape and gauge on cold strip mill arc proposed in this paper. The paper discusses three major topics: first, we develop a composite regulation model with parameter uncertainties for shape and gauge on cold strip mill, then a robust optimal control system to guarantee the strip quality is proposed, last, we give simulation results of the designed system by the proposed method.

In this paper, a unified framework for the robustness against various kinds of unmodelled uncertainty is presented. It is based on the H∞optimization for a particular nominal feedback matrix. Within such a framework, disturbance attenuation is also considered. Furthermore, the more difficult problem, i.e., when there exists real parameter uncertainty for the plant, is studied.

Refining is an important process in pulping and paper-making industry. With both large uncertainties and rapid response, it is difficult to get accurate models of refining process. Developing efficient and practical control algorithms with robustness and adaptiveness for such a specific process is of essential benefit. In this paper, a hybrid controller is designed and implemented for "refining process optimal control system". It is demonstrated that the hybrid controller gives good performance. Nevertheless, It is very simple and available for practice.