جستجوی مقالات مرتبط با کلیدواژه « Nonlinear system » در نشریات گروه « برق »

This paper proposes robust  output feedback control stabilization for uncertain Takagi–Sugeno (T-S) fuzzy systems via linear matrix inequalities (LMIs). In order to reduce the conservatism associated with T-S fuzzy system, a new form of non-monotonic Lyapunov functions is used. In the non-monotonic approach, the monotonic decrease of the Lyapunov function is relaxed which enables it to increase locally but vanish eventually. Based on the non-monotonic Lyapunov function approach, sufficient conditions for the existence of robust  output feedback control stabilization are derived. The proposed design technique is shown to be less conservative than the existing non-monotonic approach, namely, -samples variations of Lyapunov function. The effectiveness of the proposed approach is further illustrated via numerical example.

In this paper, the continuity of tracking a ground moving target using a Hexarotor is considered in the presence of sudden changes in direction, deceptive movements, temporary departure from the field of view (FOV) and changes in the height of the target. In this regard, a hierarchical guidance and control system for target tracking problem in an unknown environment and disturbances is proposed. In the inner loop, a constrained model predictive controller is designed to eliminate the environmental disturbances and also to ensure the stability against the rapid movement of the target considering the constraints on the dynamic of the Hexarotor. In the outer loop of the controller, the ability of the Hexarotor in changing its height helps the Hexarotor to preserve the ground moving target despite the sudden changes in the target direction and its temporal exitance from the field of view. Also, the controller provides an optimized control effort in a situation where the target attempts to reduce the energy level and endurance of the Hexarotor. In order to ensure the performance of the proposed system, the stability of the closed-loop system is guaranteed by defining a final state penalty function. The simulation results show the effectiveness of the proposed controller in ground moving target tracking in the presence of the environmental disturbances, the variation of the target altitude, and the deceptive movement of the target.

In this study, a novel fault detection scheme is developed for a class of nonlinear system in the presence of sensor noise. A nonlinear Takagi-Sugeno fuzzy model is implemented to create multiple models. While the T-S fuzzy model is used for only the nonlinear distribution matrix of the fault and measurement signals, a larger category of nonlinear systems is considered. Next, a mapping to decouple fault and measurement noise will be used in each fuzzy subsystems. Then, an unknown input observer is implemented to estimate the states of the subsystems subjected to measurement noise. To guarantee asymptotic stability of error dynamic, quadratic Lyapunov function using bilinear matrix inequality is introduced. Finally, the nonlinear parity approach will be used to generate residual to detect and estimate occurred fault(s) in the system. A simulation study on the train system is presented to demonstrate the efficiency of the proposed method.

This paper deals with the issues of sensor fault detection for a class of Lipschitz uncertain nonlinear system. By definition coordinate transformation matrix for system states and output system, at first the original system divided into two subsystems. the first subsystem includes uncertainties but without any sensor faults and the second subsystem has sensor faults but is free of uncertainties. Then sensor faults in second subsystem are formed as actuator faults. For the aim of fault detection (FD) two sliding mode observer is designed for two subsystems. The necessary matrices and parameters to design observers are obtained by solving linear matrix inequality (LMI) problem.  Stability condition of observer’s dynamics are reviewed based on Lyapunov approach. Finally simulation example is given to illustrate the effectiveness proposed approach.

This paper presents a robust model predictive control scheme for a class of discrete-time nonlinear systems subject to state and input constraints. Each subsystem is composed of a nominal LTI part and an additive uncertain non-linear time-varying function which satisfies a quadratic constraint. Using the dual-mode MPC stability theory, a sufficient condition is constructed for synthesizing the MPC’s stabilizing components; i.e. the local terminal cost function and the corresponding terminal set. The proposed control approach is applied to a CSTR. Simulation results show that the proposed robust MPC scheme is quite effective and it has a remarkable performance.