Earticle

The objective of this paper is to Develop and Test a model of optimizing the early design phase of shell and Tube Heat Exchangers via the application of modified Genetic Algorithm (MGA).The Modified Genetic Algorithm is based on the integration of classical genetic algorithm structure and a systematic neighborhood structure .The MGA model can help the designers to make decisions at the early phases of the design process. With a MGA model, it is possible to obtain an approximately better prediction, even when required information is not available in the design process. This model proved that MGA is capable of providing better solutions with higher quality even with inadequate data.

This paper describes the automatic control of disc type rheometer. This developed device will able to provide flexibility to operator for testing of rubber. The operator has to just enter the duration of test and parameters through man machine interface. All the operations will occur automatically without any intervention in a prescribed sequence stored in programmable logic controller (PLC). This developed apparatus is useful not only for testing purpose, but it can be used for research for other types of materials also. With this state of art apparatus one can control the quality of rubber for various applications such as tyre industry. Also this would help to increase the production of rubber as automatic control comes which reduces the test duration to few minutes only.

This article contributes a torque control based on hysteresis for Brushless Doubly Fed Induction Machine (BDFM) through machine analysis and extracting the d-q parameters that influence on the machine behavior. In this research, a Direct Torque Control (DTC) based on stator flux-oriented vectors and machine's relation and equations with voltage and current of both stators have been introduced. The control for the BDFM is implemented by a voltage source inverter connected to the second stator as a torque controller that uses the classical field-oriented control method widely used in voltage sector selection. Finally BDFM as a closed loop model with DTC is simulated and evaluated.

An optimal Fractional Order PIλDμ (FOPID) controller is designed for a full vehicle nonlinear active suspension system. The optimal values of FOPID controller parameters for minimizing the cost function are tuned using an Evolutionary Algorithm (EA), which offers an optimal solution to a multidimensional rough objective function. The fitness parameters of FOPID controller (proportional constant P, integral constant I, derivative constant D, integral order λ and derivative order μ) are selected from ranges of reliable values, depending on survival-to-the-fitness principle used in the biology science. A full vehicle nonlinear active suspension model including hydraulic actuators, nonlinear dampers and nonlinear springs has been proposed with structural and analytical details. The nonlinear frictional forces due to rubbing of piston seals with the cylinders wall inside the actuators are taken into account to find the real supply forces generated by the hydraulic actuator. The results of the full vehicle nonlinear suspension system using the FOPID controller are compared with the corresponding passive suspension system (system without controller). The controlled suspension system has been investigated under typical vehicle maneuvers: cruising on rough road surface, sharp braking and cornering. The results have clearly shown the effectiveness and robustness of the proposed controller.

Model predictive control is the family of controllers, makes the explicit use of model to obtain control signal. The reason for its popularity in industry and academia is its capability of operating without expert intervention for long periods. There are various control design methods based on model predictive control concepts. This paper provides review of the most commonly used methods that have been embedded in an industrial model predictive control. The most widely used strategies as Dynamic matrix control (DMC), Model algorithmic control (MAC), Predictive functional control (PFC), Extended prediction self-adaptive control (EPSAC), Extended horizon adaptive control(EHAC) and Generalized predictive control(GPC) have been described with history, basic idea, properties, and their controller formulation.