مجله کنترل
سال چهارم شماره 4 (زمستان 1389)

A class of collective behaviors is considered. Utilizing inverse jacobian method, a well known technique in redundant manipulators context, centralized controllers is synthesized for a multi-agent network to track desired paths in task space. These centralized controllers are dependent on global variables known as coordination variables. These global variables could be estimated by all the agents using some appropriate dynamic consensus protocols based upon local information which is available to each agent. The consensus protocols make the centralized controllers to be distributed over any interaction topology. Some sufficient conditions are identified to guarantee stability of the interconnection between the centralized controllers and the dynamic consensus estimators. An illustrative example is provided for formation control of a group of mobile agents using some inertial moments of the group.

This paper presents a new technique for nonlinear continuous-time observer design based on the differential state-dependent Riccati equation (SDRE) filter, with guaranteed exponential stability. Although impressive results have rapidly emerged from the use of SDRE designs for observers and filters, the underlying theory is yet scant and there remain many unanswered questions such as stability and convergence. In this paper, Lyapunov stability analysis is used to obtain the required conditions for exponential stability of the estimation error dynamics. Furthermore, through a simulation study of a second order nonlinear model, which satisfies the stability conditions, the promising performance of the proposed observer is demonstrated. Finally, in order to examine the effectiveness of the proposed method, it is applied to highly nonlinear flux and angular velocity estimation problem for induction machines. The simulation results verify how effectively the modification proposed in this paper can increase the region of attraction and the observer error decay rate.

In this paper, a new sliding mode observer (SMO) for state estimation of linear systems with unknown time-varying delay, and in the presence of unknown input is presented. This method is an extension on well known unknown input SMO, proposed by Zak. In our approach, the design procedure is very simplified in comparison with the other similar SMO. With an adequate choice of a Lyapunov-Krasovskii functional, sufficient conditions are obtained in LMIs terms to guarantee asymptotic stability of the state estimation errors. In order to reach a guaranteed convergence rate, the dynamic properties of observer are also analyzed. The effectiveness, simplicity, and straight-forwardness of method are shown by simulation of a numerical example.

The conventional feedback controller cannot perform well especially in presence of elastic behavior of flexible systems and variation in the character of disturbances, resulting in the reduction on the stability of the control system. This paper deals with designing a control strategy based on ‘model reference adaptive approach ’applied to appraise a single vibration mode of the system. This approach makes of a model reference adaptive lattice notch filter which has been implemented on the system in the case of recursive form to the elimination of the unsatisfied vibrating frequency. The performances of the proposed control algorithms are evaluated by means of simulation on MATLAB and Simulink.

In each surgical operation, monitoring the depth of anesthesia is vital for anesthesiologists. Several methods have been suggested to determine quantitative indices for depth of anesthesia. In this study, to make the index more robust, a beneficial EEG signal preprocessing method and also two efficient methods have been proposed to estimate the depth index during the surgery. To validate the introduced index, the proposed methods are applied to EEG signals of 22 people (1870 epochs) during the surgery and their determined indices are compared to BIS index which is now a reference in anesthesia monitoring. Experimental results showed that the proposed methods can precisely classify the different anesthesia levels of 1870 epochs. Moreover, the results were compared with BIS which shows highly correlated to the Bispectral index (BIS).

In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. In the proposed strategy, the uncertainty region is divided into smaller regions with a nominal model. It is assumed that a QFT controller prefilter exists for robust stability and performance of the smaller uncertainy subsets. The proposed control architecture is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor compares the candidate local model behaviors with the one of the real plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching for stability reasons. It is shown that this strategy improves closed loop performance, and can also handle the uncertainty sets that cannot be tackled by a single QFT robust controller. The multirealization technique to implement a family of controllers is employed to achieve bumpless transfer. Simulation results show the effectiveness of the proposed methodology.

In this paper, the dynamical model of the Lorenz hyperchaotic system is briefly introduced. An adaptive-sliding mode control scheme is proposed to stabilize the Lorenz hyperchaotic system in the presence of uncertainties, external disturbances, nonlinearity in the control inputs while parameters of the Lorenz system and the bounds of uncertainties and external disturbances are unknown. The mentioned control scheme is composed of two adaptive sliding surfaces and adaptation laws for unknown parameters. The Lyapunov stability theorem is used to prove the stability of sliding mode dynamics and guarantee the reaching condition. High frequency switching of control inputs is removed by substituting the sign function with a continuous sign-like function. Numerical simulations based on MATLAB software are used to verify the feasibility and effectiveness of the proposed controllers.