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This paper is concerned with the design of state-feedback switched controllers for a class of uncertain nonlinear plants described by Takagi–Sugeno (T–S) fuzzy models. The proposed methodology eliminates the need to find the membership function expressions to implement the control law, which is relevant in cases where the membership function depends on uncertain parameters. The design of the switched controllers is based on a minimum-type Lyapunov function and the minimization of the time derivative of this Lyapunov function. The conditions of the new stability criterion are represented by a kind of bilinear matrix inequalities (BMIs) that has been solved by the path-following method. A numerical example and the nonlinear control design of a magnetic levitator with uncertainties illustrate the procedure. [ABSTRACT FROM AUTHOR]

The paper proposes a new switched control design method for some classes of uncertain nonlinear plants described by Takagi-Sugeno fuzzy models. This method uses a quadratic Lyapunov function to design the feedback controller gains based on linear matrix inequalities (LMIs). The controller gain is chosen by a switching law that returns the smallest value of the time derivative of the Lyapunov function. The proposed methodology eliminates the need to find the membership function expressions to implement the control laws. The control designs of a ball-and-beam system and of a magnetic levitator illustrate the procedure. [ABSTRACT FROM AUTHOR]

This paper proposes a new switched control design method for some classes of linear time-invariant systems with polytopic uncertainties. This method uses a quadratic Lyapunov function to design the feedback controller gains based on linear matrix inequalities (LMIs). The controller gain is chosen by a switching law that returns the smallest value of the time derivative of the Lyapunov function. The proposed methodology offers less conservative alternative than the well-known controller for uncertain systems with only one state feedback gain. The control design of a magnetic levitator illustrates the procedure. [ABSTRACT FROM AUTHOR]

This manuscript proposes a local H ∞ switched controller design for a class of uncertain nonlinear plants described by Takagi–Sugeno (T–S) fuzzy models with unknown membership functions. The control design requires only the lower and upper bounds of the system nonlinearities and of the system linear parameters, which can depend on uncertain parameters. The switched control law chooses a state-feedback controller gain, which belongs to a given set of gains, that minimizes the time derivative of a quadratic Lyapunov function. This procedure eliminates the necessity of finding the membership function expressions to implement the control law, guarantees an H ∞ performance and ensures that the state trajectory remains within a region in which the T–S fuzzy model is valid. Due to the H ∞ control design, that frequently results in very large control inputs, it is considered that the switched control law is subject to actuator saturation. Finally, two examples are presented. The first example studies the control of a chaotic Lorenz system. It shows that, for disturbances with large magnitude, the proposed procedures provided better results than the obtained with another recent method found in the literature, that considers full access to the membership functions. In the second example, a practical implementation of an active nonlinear suspension control system, considering an uncertain bounded mass and a fault in the actuator, confirms the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]