Mohammad Tawfik

Publications (27) View all

• Article: Advanced Materials for Applications in Acoustics and Vibration

  Yehia A. Bahei-El-Din, Tawfik Mohammad
  Advances in Acoustics and Vibration. 01/2009;
• Source

  Available from: hydyn.hanyang.ac.kr

  Article: Thermo-acoustic random response of temperature-dependent functionally graded material panels

  Hesham Hamed Ibrahim, Hong Hee Yoo, Mohammad Tawfik, Kwan-Soo Lee
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  ABSTRACT: A nonlinear finite element model is provided for the nonlinear random response of functionally graded material panels subject to combined thermal and random acoustic loads. Material properties are assumed to be temperature-dependent, and graded in the thickness direction according to a simple power law distribution in terms of the volume fractions of the constituents. The governing equations are derived using the first-order shear-deformable plate theory with von Karman geometric nonlinearity and the principle of virtual work. The thermal load is assumed to be steady state constant temperature distribution, and the acoustic excitation is considered to be a stationary white-Gaussian random pressure with zero mean and uniform magnitude over the plate surface. The governing equations are transformed to modal coordinates to reduce the computational efforts. Newton–Raphson iteration method is employed to obtain the dynamic response at each time step of the Newmark implicit scheme for numerical integration. Finally, numerical results are provided to study the effects of volume fraction exponent, temperature rise, and the sound pressure level on the panel response. KeywordsFunctionally graded materials-Thermoacoustic vibration-Nonlinear FEM
  Computational Mechanics 04/2012; 46(3):377-386. · 2.07 Impact Factor
• Article: Enhancing Genetic Algorithms using a Dynamic Mutation Value Approach: An Application to the Control of Flexible Robot Systems

  Sarah Deif, Hanan A. Kamal, Mohammad Tawfik
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  ABSTRACT: This paper presents an investigation into a new optimization technique based on genetic algorithm (GA). A dynamically-changed mutation value approach is introduced to increase the diversity in the search space and avoid premature convergence caused by simple genetic algorithm (SGA). The enhanced genetic algorithm (EGA) is used to tune the feedback gains of a PD controller which controls both the position and vibration of a single-link flexible arm. The dynamic model of the system is derived using Hamilton’s principle and modeled using the finite element method (FEM). A multi-objective function is defined and altered to reach a range of specified system responses and therefore it is shown to be able to satisfy different objectives. Adaptive Genetic Algorithm (AGA) and Cloud Model Based Adaptive Genetic Algorithm (CAGA) techniques are used to challenge the proposed technique. Results obtained show that EGA creates significant improvement in the speed of convergence compared to other techniques. Moreover, the obtained solutions are of higher average fitness values. EGA succeeded to consistently reach a global solution for an objective function that needs rigorous search mechanism which encourages for further application to various control problems, complex mathematical functions and real time applications.
  CiiT International Journal of Artificial Intelligent Systems and Machine Learning (IF 0.763). 01/2012; 4(1):9-16.
• Source

  Available from: Sarah Deif

  Conference Proceeding: Vibration and Position Control of a Flexible Manipulator using a PD- tuned Controller with Modified Genetic Algorithm

  Sarah Deif, Mohammad Tawfik, Hanan A Kamal
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  ABSTRACT: Flexible manipulators have received wide attention being more realistic than their rigid counterparts in many practical conditions. The control of the motion and vibration of an elastic model has inspired many studies in the past decades. A modified genetic algorithm (MGA) is proposed to optimize the feedback gains of a proportional derivative (PD) controller used for the control of the position and vibration of a flexible arm. It has been shown that the new algorithm results in faster convergence and higher accuracy over the simple genetic algorithm (SGA). Also, MGA solves the problem of premature convergence and stagnation that is caused by SGA. Three different objective functions based on minimizing the error function were tested and compared. Multi-objective error fitness function combined with the proposed GA has given the best system response which encourages for further research into various control applications.
  ICCTA 2011, Alexandria, Egypt; 10/2011
• Source

  Available from: Sarah Deif

  Conference Proceeding: Adaptive Genetic Algorithm Application in Controlling a Four DOF Robot Manipulator Based on Inverse Kinematics

  Mohamed Tolba, Sarah Deif, Mohammad Tawfik, Hani M Negm
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  ABSTRACT: In this paper, the controller design of a four degree of freedom (4 DOF) articulated robot manipulator using inverse kinematics and a new adaptive genetic algorithm (AGA) was presented. The Pseudoinverse method was used to solve the Inverse kinematic problem. The gains of the PD controller were tuned using the AGA. The dynamics of the robot manipulator were modeled using Adams simulation package. The controller was modeled in SIMULINK which communicates with Adams using a plant block generated by Adams/Controls plug-in. The proposed genetic algorithm along with the pseudoinverse method were successfully applied to the control of a four DOF articulated robot manipulator giving a satisfactory system response which encourages for further research into various control applications.
  ICCTA 2011, Alexandria, Egypt; 10/2011