Abstract This paper deals with the robust fault detection (FD) identification of discrete-time periodic systems using modelmatching problem. Discrete-time periodic system is first converted into linear time invariant (LTI) system using lifting technique and then conventional fault detection filter (FDF) problem is applied on such discrete LTI system. This problem is multi-objective or optimization problem in which effect of disturbance on residual is minimized and at the same time effect of fault on residual is maximized by solving some linear matrix inequalities (LMI). In the end, a design example is solved and simulation results are provided. This paper deals with the robust fault detection (FD) identification of discrete-time periodic systems using modelmatching problem. Discrete-time periodic system is first converted into linear time invariant (LTI) system using lifting technique and then conventional fault detection filter (FDF) problem is applied on such discrete LTI system. This problem is multi-objective or optimization problem in which effect of disturbance on residual is minimized and at the same time effect of fault on residual is maximized by solving some linear matrix inequalities (LMI). In the end, a design example is solved and simulation results are provided. Read More Read Less

Abstract This paper presents a new way of modeling the OCC model of emotions. A Bayesian network is employed to represent the structure and the relationship among emotions of the OCC model. In this manner the stochastic behavior, a new characteristic, is inserted in the simulations using the OCC model. Emotions a ect directly the human behavior ff influencing many aspects e.g. decisionmaking, actions and memory. Specially because emotions are not a deterministic variable we propose the use of the Bayesian networks to model them. Bayesian networks are an excellent tool for modeling real problems because they use probabilistic reasoning which differs from the logical reasoning used by the majority of the computational tools. In order to evaluate the proposed model we applied it in a BDI Multi - Agent system. In this system we tested the introduction of emotions in three hypothetical situations and compared how these emotions influence the behavior of the agents. This paper deals with the robust fault detection (FD) identification of discrete-time periodic systems using modelmatching problem. Discrete-time periodic system is first converted into linear time invariant (LTI) system using lifting technique and then conventional fault detection filter (FDF) problem is applied on such discrete LTI system. This problem is multi-objective or optimization problem in which effect of disturbance on residual is minimized and at the same time effect of fault on residual is maximized by solving some linear matrix inequalities (LMI). In the end, a design example is solved and simulation results are provided. Read More Read Less