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    Design of a fuzzy robust-adaptive control law for active suspension systems
    (Springer India, 2020) Ozbek, Cengiz; Ozguney, Omur Can; Burkan, Recep; Yagiz, Nurkan
    This paper outlines a new approach in control of active vibration systems to make the system robust to parametric uncertainties, unmodeled dynamic effects and external disturbances. Namely, it is aimed to ensure robustness of the system towards all kind of disturbances such as road surface inputs and unexpected system parameter changes. So, a new robust-adaptive controller is designed as a vibration isolator and then applied on a full car active suspension system to improve the ride comfort of a vehicle in the presence of structured parameter uncertainties and unstructured unknown parameters or unmodeled dynamics. For this purpose, new parametric uncertainty upper bound adaptation algorithm is developed to isolate any platform from vibrations. Using adaptive laws, the controller can operate properly under changing conditions. The robustness of controller is also ensured by robust control law. This new approach represents a groundbreaking solution to eliminate any disturbance on a vehicle. Stability of the system is guaranteed by using Lyapunov theory, thus uniform boundedness error convergence is achieved. Afterwards, fuzzy logic controller is used to achieve the optimum values of controller gains. Also, comparative numerical solution using a fuzzy logic controlled suspension is performed on the same full-car model, both in time and frequency domain since classical FLC is an effective control method for active suspensions. At the end, it has been verified that the designed fuzzy robust-adaptive controller improves ride comfort more successfully than fuzzy logic one.
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    Ride comfort improvement using robust multi-input multi-output fuzzy logic dynamic compensator
    (Sage Publications Ltd, 2023) Ozbek, Cengiz; Ozguney, Omur Can; Burkan, Recep; Yagiz, Nurkan
    This article aims to improve the ride comfort of a vehicle keeping a satisfactory without road-holding performance by a novel adaptive control method that is insensitive to unknown system dynamics, model parameter changes, external disturbances and without any loss in suspension working space. With this purpose in mind, a new fuzzy integrated model-based adaptive control law for vehicle suspension systems is proposed in this study to improve the ride comfort and to ensure the robustness of system towards unknown model parameters and external disturbances. First, a model-based adaptive control law, which has the robust characteristics is presented. Afterwards, a multi-input multi-output fuzzy logic controller is designed to determine the controller gains dynamically. The stability of controller is ensured by Lyapunov Theory to achieve uniform boundedness error convergence. A 4 degree-of-freedom half-car model with active suspension system is used in this study to assess the performance of the controller. The results are compared among passive, model-based adaptive control law-controlled and novel fuzzy model-based adaptive control law-controlled systems. It has been concluded that fuzzy model-based adaptive control law further attenuates linear and angular motions of the vehicle increasing the ride comfort. The robustness is also verified for vehicle components having different possible parameter values. It is noteworthy that suspension working length returns to its initial position. Thus, the vehicle ride comfort is improved with no suspension working space loss. Finally, the economic feasibility of controllers has been checked in terms of energy consumption.