Rosmazi Bin Rosli @ Pang See Hoon creator author. text my 2025 2025 monographic eng xiii, 135 pages : illustration ; 30 cm. + 1 CD-ROM. In semi-active vibration attenuation systems, the Magnetorheological (MR) damper has emerged as one of the most robust and cost-efficient actuators. The damper provides fail-safe operation, ensuring the safety and reliability of the system while delivering a favorable force-to-power input ratio. However, developing an effective controller for the MR damper remains challenging due to the complexity of its mathematical model and the hysteresis behavior of this highly nonlinear device. To address this, researchers have investigated several parametric models that successfully describe the damper's hysteresis behavior using simpler mathematical formulations. Although these parametric models are effective in capturing the MR damper's hysteresis curve, they present challenges in parameter optimization. This study focuses on optimizing a Bouc-Wen-based phenomenological model to accurately replicate the force-velocity hysteresis curve of a real MR damper. Recent studies shown that the meta-heuristic algorithm has gain popularity among researcher in optimization problems. This research focuses on the Cuckoo Search algorithm for its fast convergence rate and low number of parameters needed to utilize. For optimizing the parameters of the Bouc-Wen model, three new modified versions of the Cuckoo Search Algorithm are used, offering improved exploration and exploitation balances during the optimization process. The Dynamic Cuckoo Search and Inverse Dynamic Cuckoo Search algorithms adjust the exploration-exploitation balance based on the iteration number, while the Adaptive Cuckoo Search algorithm varies the balance based on the fitness evaluation update rate. Experiments were conducted to capture the actual dynamic responses of the MR damper, specifically analyzing its force-displacement and force-velocity characteristics across various current inputs. The optimized parameters of the Bouc-Wen model were then evaluated for tracking performance, demonstrating superior capabilities compared to other optimization methods, such as Particle Swarm Optimization, Genetic Algorithm, and Sine-Cosine Algorithm. The results show that the Bouc-Wen model, optimized using the proposed modified Cuckoo Search algorithm, tracks the MR damper's hysteresis curve more accurately than other algorithms. Finally, the phenomenological model optimized by the modified Cuckoo Search algorithm was tested in a two-degree-of-freedom (2-DOF) semi-active seat suspension system. The results indicate that the model successfully designed a controller scheme for the MR damper, achieving a 35% reduction in body acceleration. This research introduces a new modified Cuckoo Search algorithm and successfully integrates it with the phenomenological Bouc-Wen model for MR damper applications. specialized Rosmazi Bin Rosli @ Pang See Hoon Faculty of Mechanical and Automotive Engineering Technology Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang - 2026 Includes bibliographical references Faculty of Mechanical and Automotive Engineering Technology Dissertations Universities and colleges Dissertations Theses Dissertations THE0010529 (Local) UMPSA 260525 20260525175836.0 eng