Applied Mathematics and Humanities

In this paper using the system identification method a PMDC motor transfer function is derived. The transfer function is derived in digital as in continuous domain and it is verified with the parameter of PMDC motor. The model predictive control method is applied for the control of PMDC motor. The model of the system used here is the practical or the actual model of the system that is derived from the practical setup.

Inverse kinematics is difficult in computation and can result in significant delays in real time. For a redundant robot, additional computations are required for the inverse kinematic solution through optimization schemes. Getting inverse kinematics result using equation would be considered under expensive efforts. So this optimization can be done efficiently by fuzzy logic. Based on the fact that exact inverse kinematics cannot be calculated by human, but can do defined positioning from trial and error. The implementation of the projected scheme has established that it is practical for both redundant and non redundant cases, and that it is very computationally efficient. The result provides sufficient precision. This paper discusses (1) the automatic generation of the Fuzzy Inverse Kinematic Mapping (FIKM) from specification of the Denavit-Hartenberg parameters (2)Programming that in microcontroller and implementation on hardware.

In this paper, different fractional order transfer functions are taken first and discretized them using available methods and filters (i.e. Oustaloup or modified Oustaloup). Coefficients of discretized transfer function are calculated and scaled using Q15 number system to get the coefficients in the range between-1 to 1, and converted into equivalent hexadecimal number. These coefficients are entered into the Micro C code that is generated using filter design tool of Micro C for dsPIC microcontroller. Also the simulation results are validated using EasydsPIC4 development board.

This paper presents a case study of utilizing waste streams from diverse fiber/yarn products to create engineered automotive acoustic components. Cost, weight, acoustic performance and recyclabiHty are important attributes in the automotive industry. Creating engineered products from waste streams requires a systematic approach, which takes into account factors such as material properties, material handling, process and logistics.