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The delay-dependent state, Fault Estimation (FE) and Fault Tolerant Control problems for polynomial fuzzy systems with time delay are investigated in this paper. Firstly, a polynomial adaptive fuzzy observer is used to estimate system states and actuator faults. A polynomial Lyapunov–Krasovskii functional including double integral term is introduced in order to obtain delay-dependent sufficient conditions in terms of Sum Of Squares (SOS) which can be solved via SOSTOOLS and a Semi-Definite Program solver. Then, by exploiting the FE information, a polynomial fuzzy fault tolerant controller is designed to guarantee the stability of the system and to compensate the impact of actuator faults. Finally, several examples are given to illustrate the use of the present delay-dependent result. [ABSTRACT FROM AUTHOR]

In this paper, a robust fault estimation for polynomial systems with time delay via a polynomial adaptive observer is presented and described. In fact, in contrast to previous research works on actuator faults, the learning rate utilized to govern the convergence speed of states and faults errors is not predetermined but is derived using the sum of squares optimization problem. Furthermore, the H ∞ optimization approach was created to reduce the impact of disturbances on state estimation error and fault estimation error. Finally, an illustrative practical example is given to validate the effectiveness of the suggested methodology. [ABSTRACT FROM AUTHOR]

Summary: This paper deals with some synthesis problems for a class of positive polynomial systems with time delay, for which the state vector takes nonnegative values whenever the initial conditions are nonnegative. First, the synthesis of state feedback controllers is solved using a Lyapunov‐Krasovskii approach, including the requirement of positiveness. In a second part, observers are included. In both cases, the design conditions are presented in terms of sum of squares, which can be numerically and symbolically solved via SOSTOOLS and a semidefinite program solver. Finally, four numerical examples are given to illustrate the proposed approach. [ABSTRACT FROM AUTHOR]