This paper proposes a fuzzy logic control algorithm (FLCA) to stabilize the Rössler chaotic dynamical system. The fuzzy logic control system is based on a Takagi-Sugeno-Kang inference engine and the stability analysis in the sense of Lyapunov is carried out using Lyapunov's direct method. The new FLCA is formulated to offer sufficient inequality stability conditions. The asymptotic complexity of our algorithm is analyzed and proved to be lower in comparison with that of linear matrix inequality-based FLCAs. A set of simulation results illustrates the effectiveness of the proposed FLCA.
This paper discusses novel tensor product (TP) models for the control of two complex components of the vehicle automatic transmission systems, namely the drive line without clutch and, the valve-clutch. The TP models are obtained by a transformation of the linear parameter-varying models derived from the first principle nonlinear mathematical models of the controlled processes. Experimental results validate the performance of the proposed TP models.
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