Papers by Keyword: Linear Matrix Inequality (LMI)

Abstract: In this paper, we address the mixed H₂/H_∞ control approach for linear time-invariant system based on linear matrix inequality (LMI). First, the problem to be solved is stated, and the satellite attitude dynamics is established and converted into a corresponding state space form. Then, the mixed H₂/H_∞ controller based on LMIs is designed in order to attain the state feedback gain matrix. To validate the efficiency and practicability of the proposed controller, simulation results based on satellite attitude system are presented, from which we can observe that under the condition of external disturbances, the system will be stable within 150s, and the maximum of control torque will be no more than 0.025Nm. Expanding the controller gain will affect the stabilizing process, but not the stabilization time, and it will increase the control input which will bring pressure to the actuator.

Abstract: A type of aircraft that is currently being very reference in the area of ​​control is the quadrotor helicopter, compared to other UAV's (Unmanned Aerial Vehicles UAV's-) has been of great interest for the research groups. Principally were developed for military applications. However, UAVs don’t have only military use, also civilian use and it is in this last field that can have multiple applications. The State variables of the system obtained are, however, in the most general case, internal operation of the system variables whose values ​​can’t be measured directly on physical quantities. An observer is used for to reconstruct partially or completely the state vector of a system from the known inputs, outputs and the dynamic model of this. The reconstruction and calculation of the state variables is performed in a system known as Multiobserver. Applying the fuzzy representation of type Takagi-Sugeno, also known as multi-model [1], in dynamic model of the quadrotor and developing an algorithm based in law control for reconstructed states feedback, the vehicle is stabilized.

Abstract: This paper investigates the exponential stability problem for a class of stochastic neural networks with leakage delay. By employing a suitable Lyapunov functional and stochastic stability theory technic, the sufficient conditions which make the stochastic neural networks system exponential mean square stable are proposed and proved. All results are expressed in terms of linear matrix inequalities (LMIs). Example and simulation are presented to show the effectiveness of the proposed method.

Abstract: In this paper, the problem of delay-dependent asymptotic stability analysis for neural networks with interval time-varying delays is considered. By the use of delay-partitioning method and some novel techniques, some less conservative stability criteria are established in terms of linear matrix inequalities. Moreover, our criteria depend on both the upper and lower bounds of time-varying delay and its derivative, which is different from some existing ones. Finally, an numerical example is given to show the improved stability region of the proposed results.

Abstract: In this paper, the global exponential stability is discussed for static neural networks with time varying delays. On the basis of the linear matrix inequalities (LMIs) technique, and Lyapunov functional method, we have obtained the main condition to ensure the global exponential stability of the equilibrium point for this system, which is dependent on the change rate of time varying delays. The proposed result is less restrictive than those given in the earlier literatures, easier to check in practice. Remarks are made with other previous works to show the superiority of the obtained results, and the simulation examples are used to demonstrate the effectiveness of our results.

Abstract: This paper proposes delay-dependent stability conditions of discrete-time networked control systems (NCSs) with unknown, time-varying and bounded delays using Lyapunov-Krasovskii functional and the improved free-weighting matrix approach. Moreover, the conditions are extended to the NCSs with time-varying structured uncertainties.

Abstract: In this paper the modeling and stability analysis of networked cascade control systems (NCCSs) are discussed. A class of continuous-time NCCSs model with time-varying delays is described, in which the network-induced delays are assumed to be unknown, time-varying, and bounded. Based on the NCCSs model, the stability conditions of the NCCSs are proposed using Lyapunov-Krasovskii functional and the free-weighting matrix approach.

Abstract: The problem studied the robust fault-tolerant controller design for the uncertain networked control system, The considered system has actuator and sensor failures. Under the non-ideal network conditions such as time-delay, data packet dropout and mis-sequence, a model of the networked control systems is provided, The robust stability conditions are obtained in the situation of actuator and sensor failures based on Lyapunov Krsasovkii functional method and static output feedback by introducing some free-weighing matrices, Based on this sufficient condition, the static output feedback controller design method is deduced in terms of linear matrix inequalities. An illustrative example shows the effectiveness and feasibility of proposed method.

Abstract: The monotonic convergence (MC) property of discrete two-dimensional (2-D) systems described by the Roesser model is studied. The MC problem of the 2-D system is firstly converted to two H_∞ disturbance attenuation problems of the traditional one-dimensional system. Then, the sufficient condition is derived for the MC, which is given by two linear matrix inequalities (LMIs). Furthermore, it can be shown that either of the LMIs can also guarantee the Bounded-Input Bounded-Output (BIBO) stability of the 2-D system. Finally, a simulation example is given to show the effectiveness of the LMIs condition.

Abstract: This paper addresses the observer design for simultaneously estimating the state and input of a class of impulsive systems whose nonlinear terms satisfy an incremental quadratic constraint. By employing Lyapunov theory, sufficient conditions for asymptotical and exponential estimation convergence are derived. Gain matrices of the proposed observer can be obtained by solving linear matrix inequalities (LMIs).