Passification-based direct adaptive control is considered for polytopic uncertain linear time-invariant multi-input multi-output systems. Linear Matrix Inequality based results are provided to guarantee that the adaptive algorithm passifies the system whatever the uncertain parameters in some given set. The contributions are based on the introduction of a parallel feed-forward shunt that libera...

A stochastic minimax optimal control strategy for uncertain quasi-Hamiltonian systems is proposed based on the stochastic averaging method, stochastic maximum principle and stochastic differential game theory. First, the partially completed averaged Itô stochastic differential equations are derived from a given system by using the stochastic averaging method for quasi-Hamiltonian systems with u...

This paper proposes a novel method for identification of a class of the uncertain active suspension systems by using on-line adaptive T-S fuzzy-neural controller. In reality, vehicles may encounter unpredictable road conditions, e.g., rocks and potholes influencing the dynamic behavior of active suspension systems. These road conditions are not only cause parts of the active suspension system t...

We study the problem of estimating the states of an unstable dynamical system subject to nonstochastic disturbances. The estimator obtains all its information through an uncertain channel which is subject to nonstochastic disturbances as well and an eavesdropper obtains a disturbed version of the channel inputs through a second uncertain channel. An encoder observes and block-encodes the states...

We develop an adaptive control architecture to achieve stabilization and command following of uncertain dynamical systems with improved transient performance. Our framework consists of a new reference system and an adaptive controller. The proposed reference system captures a desired closed-loop dynamical system behavior modified by a mismatch term representing the high-frequency content betwee...

Inspired from the robust control principle, a robust scheduling method is proposed to solve uncertain scheduling problems. The uncertain scheduling problem is modeled by a set of workflow simulation models, and then a scheduling scheme (solution) is evaluated by the results of workflow simulations that are executed by using the workflow models in the set. A variable neighborhood immune algorith...

Uncertainty theory is a mathematical methodology for dealing withnon-determinate phenomena in nature. As we all know, uncertainprocess and uncertain integral are important contents of uncertaintytheory, so it is necessary to have deep research. This paperpresents the definition and discusses some properties of strongcomonotonic uncertain process. Besides, some useful formulas ofuncertain integr...

multiple sclerosis is a chronic inflammatory disease of central nervous system.women are more susceptible to this disease. one of the obvious clinical complaints in women with multiple sclerosis specially treated with beta interferones is menstrual cycle irregularity. the aim of this study was to determine the prevalence of menstrual irregularities and probable changes in blood levels of relate...

This paper presents a model reference attitude tracking controller design for quadrotor unmanned aerial vehicle subject to saturated actuators and external disturbances. The dynamical nonlinear of the quadrotor's is represented by an uncertain-like Takagi-Sugeno model, with exact matching on compact subset state space. generalized sector condition employed deal inputs quadrotor. LMI conditions ...