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RISS 인기검색어
- 검색키워드
- 저자 : Mohammad Danesh (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Active structural acoustic control of a smart cylindrical shell using a virtual microphone
Loghmani, Ali,Danesh, Mohammad,Kwak, Moon K,Keshmiri, Mehdi Institute of Physics Publishing 2016 Smart materials & structures Vol.25 No.4
<P>This paper investigates the active structural acoustic control of sound radiated from a smart cylindrical shell. The cylinder is equipped with piezoelectric sensors and actuators to estimate and control the sound pressure that radiates from the smart shell. This estimated pressure is referred to as a virtual microphone, and it can be used in control systems instead of actual microphones to attenuate noise due to structural vibrations. To this end, the dynamic model for the smart cylinder is derived using the extended Hamilton’s principle, the Sanders shell theory and the assumed mode method. The simplified Kirchhoff–Helmholtz integral estimates the far-field sound pressure radiating from the baffled cylindrical shell. A modified higher harmonic controller that can cope with a harmonic disturbance is designed and experimentally evaluated. The experimental tests were carried out on a baffled cylindrical aluminum shell in an anechoic chamber. The frequency response for the theoretical virtual microphone and the experimental actual microphone are in good agreement with each other, and the results show the effectiveness of the designed virtual microphone and controller in attenuating the radiated sound.</P>
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Fuzzy Greedy RRT Path Planning Algorithm in a Complex Configuration Space
Ehsan Taheri,Mohammad Hossein Ferdowsi,Mohammad Danesh 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.6
A randomized sampling-based path planning algorithm for holonomic mobile robots in complex configuration spaces is proposed in this article. A complex configuration space for path planning algorithms may cause different environmental constraints including the convex/concave obstacles, narrow passages, maze-like spaces andcluttered obstacles. The number of vertices and edges of a search tree for path planning in these configuration spaces would increase through the conventional randomized sampling-based algorithm leading to exacerbation of computational complexity and required runtime. The proposed path planning algorithm is named fuzzy greedy rapidly-exploring random tree (FG-RRT). The FG-RRT is equipped with a fuzzy inference system (FIS) consisting of two inputs, one output and nine rules. The first input is a Euclidean function applied in evaluating the quantityof selected parent vertex. The second input is a metaheuristic function applied in evaluating the quality of selected parent vertex. The output indicates the competency of the selected parent vertex for generating a random offspringvertex. This algorithm controls the tree edges growth direction and density in different places of the configuration space concurrently. The proposed method is implemented on a Single Board Computer (SBC) through the xPC Target to evaluate this algorithm. For this purpose four test-cases are designed with different complexity. The results of the Processor-in-the-Loop (PIL) tests indicate that FG-RRT algorithm reduces the required runtime and computational complexity in comparison with the conventional and greedy RRT through fewer number of vertices in planning an initial path in significant manner.
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Benyamin Anafjeh,Hassan Moosavi,Mohammad Danesh 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.4
Active tilting control is now one of the technologies utilized widely in high-speed railway vehicles. This paper tries to decrease the lateral acceleration on passengers (caused by high-speed motion in a curve) using an electrical anti-roll bar (ARB) that provides a limited amount of carbody tilt. A dynamic model is employed for a modern railway vehicle with its active anti-roll bar (AARB). Moreover, an attempt is made to design three control approaches of Kalman filter-based Model Predictive Control, Linear Quadratic Gaussian servo control, and proportional-integral regulator in such a way to be robust against noise and simultaneously improve ride comfort and vehicle dynamic performance. The active anti-roll bar acts as an actuator with a brushless DC (BLDC) motor, permitting active tilt control. Finally, the performance of the tilting vehicle and electric actuation system employing different control structures is assessed based on numerical simulations. Furthermore, a helpful comparison is drawn between the optimal and other simulated control approaches concerning ride comfort. The simulation results reveal better competency of Kalman filter-based Model Predictive Control in achieving the reference pursuit plus noise canceling and improving ride comfort.
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