Session Program

Abstract - This paper considers a regulation problem of nonlinear large-scale systems. To do this, a Takagi-Sugen (T-S) fuzzy model is adopted for fuzzy modeling of the nonlinear large-scale systems, which has unknown interconnection terms. An output-feedback decentralized fuzzy controller with integral action is employed to drive the system outputs to reach a reference value and minimize the steady-state error. Sufficient conditions for the output regulation are derived from Lyapunov stability and these are formulated in terms of linear matrix inequalities (LMI). Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed design procedures and regulation conditions.

Abstract - This paper proposes an approach for Fault Detection and Diagnosis (FDD) of an actuation system for passengers seats in commercial aircrafts. The FDD is performed using classification algorithms. The supervised classification algorithms are usually based on data collected from the different sensors installed on a real system. Thus, to reduce the number of embedded sensors and so the costs of seat components in commercial aircrafts, a fuzzy Takagi-Sugeno (T-S) state observer is considered to estimate non-measured state variables in order to enrich the database used for the supervised classification process. From experimental measurements on a prototype of the actuated seat, the benefit of adding T-S observer- based estimations is illustrated through a comparison of the classification results obtained using databases without then with estimated data.

Abstract - This paper deals with the non-quadratic robust D-stabilization of uncertain Takagi-Sugeno (T-S) fuzzy systems. By considering the D-stability concept, Linear Matrix Linearity (LMI) conditions are proposed for the design of non Parallel-Distributed-Compensation (non-PDC) controllers via non-quadratic Fuzzy Lyapunov Functions (FLF). These conditions allow local D-stabilization. Thus, a simple way is considered to estimate the domain of attraction (DA) of the designed closed-loop dynamics. The proposed result is illustrated through a numerical example.

Abstract - This work deals with the problem of stability analysis of time-delay nonlinear systems in a Takagi-Sugeno form. More relaxed delay-dependent conditions in terms of linear matrix inequalities are developed from a novel non-quadratic Lyapunov-Krasovskii functional. The proposed non-quadratic structure is a state-dependent convex one, which includes former approaches as particular cases while avoiding dealing with the time derivatives of the model nonlinearities in the convex sum. Some examples are given to illustrate the effectiveness of the proposed approach when compared with former solutions.

Abstract - In this paper, conditions for local stabilization of Takagi-Sugeno (T-S) fuzzy discrete-time systems with time-varying delay and saturating actuators are developed. These conditions are based on a fuzzy Lyapunov-Krasovskii (L-K) candidate function and on a sector condition. Thus, an estimate of the region of attraction is characterized by two sets: one to deal with the current state vector and the other set to handle the delayed state vectors. The delay is supposed to be time-varying and belongs to the interval [1,dmax]. Only the current state, xk, and the state delayed by dmax samples are fed back through the fuzzy control law. Furthermore, we propose a convex optimization procedure to maximize the estimate of the region of attraction for closed-loop control system. Finally, we give a numerical example to illustrate the obtained results.

Abstract - This paper presents a novel fuzzy based approach to gesture driven human robot interaction. Now a day, gestures are considered to be the most effective communicative medium for remotely controlling a robot. In this work, the gestures are employed to instruct a Khepera II robot to move from a specific starting position to a goal position following a specific path. The main highlight is the determination of exact degree of rotation with proper application of acceleration and brake in order to reach the specified goal position without hitting the obstacles. A Takagi-Sugeno-Kang based fuzzy model with two antecedents (type-2 fuzzy sets) and one consequent (crisp value) has been employed to determine the angle of rotation. The performance of the proposed framework has been tested in terms of a number of parameters like accuracy, precision, error rate etc. And in each case, the formulated strategy has proved its worth.