LINEAR QUADRATIC REGULATOR DESIGN FOR VEHICLE SUSPENSION SYSTEM BASED ON BACTERIAL MEMETIC ALGORITHM

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dc.contributor.advisorDávid Péter, Nusser
dc.contributor.authorABDULLAHI MAGAJI, BALA
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2025-12-12T17:17:46Z
dc.date.available2025-12-12T17:17:46Z
dc.date.created2025
dc.description.abstractThe thesis work entails the design of a Bacterial Memetic Algorithm (BMA)-optimized Linear Quadratic Regulator (LQR) controller for a vehicle suspension system. The BMA combines and integrates two optimization methods – the Bacterial Foraging Optimization Algorithm (BFOA) and the Memetic Algorithm (MA), thereby enhancing its search efficiency and reducing the risk of getting stuck in local minima. Through this synergistic integration, an optimal feedback gain for the LQR controller is determined, which in turn controls the random vibration and oscillation of the suspension system, thereby enhancing comfort, safety, and road handling. The MATLAB 2024b environment was utilized for the simulation. The Fast Fourier Transform (FFT) was used to calculate the Power Spectral Density (PSD) of the randomly generated road profile applied in the study. The results of the proposed model were compared with two other models – the Genetic Algorithm (GA)-LQR and the Virus Evolutionary Genetic Algorithm (VEGA)-LQR optimized models – to demonstrate the efficiency and efficacy of the proposed model.
dc.description.courseMechatronical Engineeringen
dc.description.degreeBSc/BA
dc.format.extent47
dc.identifier.urihttps://hdl.handle.net/2437/399855
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectBacterial Memetic Algorithm (BMA)
dc.subjectLinear Quadratic Regulator (LQR) Controller
dc.subjectVehicle Suspension System
dc.subject.dspaceEngineering Sciences
dc.titleLINEAR QUADRATIC REGULATOR DESIGN FOR VEHICLE SUSPENSION SYSTEM BASED ON BACTERIAL MEMETIC ALGORITHM
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