The suggestion is prepared for Particle Swarm Optimization (PSO) Recurrent Neural Network (RNN) based Z-Source Inverter Fed Induction Motor Drive in this document. The proposed method is employed to develop the presentation of the induction motor while decreasing the Total Harmonic Distortion (THD), eliminating the oscillation period of the stator current, torque and speed. Currently, as the input parameters, the PSO technique uses the induction motor speed and reference speed. It optimizes the raise of the PI controller and produces the reference quadrature axis current from the input parameters. By employing the RNN the reference three phase current for accurate control pulses of the voltage source inverter is predicted. The RNN is trained by the input motor actual quadrature axis current and the reference quadrature axis current with the associated target reference three phase current. The training process used the supervised learning process. Next the proposed technique is implemented in the MATLAB/simulink platform and the competence is scrutinized by comparing with the other techniques such as PSO-Radial Biased Neural Network (RBNN) and PSO-Artificial Neural Network (ANN). The comparison results show the superiority of the proposed approach and confirm its potential to effort out the problem. 8 9 10 11 12 13 14 15 16 17 18 leg is restricted as it short circuits the DC source [3]. In 30 conventional voltage-source inverter, the two switches 31 of the same-phase leg can in no way be gated on at the 32 same time as doing so would cause a short circuit (shoot 33 through) to occur, which would destroy the inverter [2]. 34 Z source inverter increases above the difficulties in the 35 Traditional VSI and CSI [6]. 36 The Z-source inverter is a dc voltage source which 37 prolonged by a relatively large capacitor supplies the 38 most important circuit of the inverter bridge [5]. Z-39 source inverter can improve dc input voltage with no 40 necessity of dc-dc boost converter or step up trans-41 former, hence prevailing over output voltage limitation 42 of traditional voltage source inverter with lower its 43 cost [1]. To take the isolated load, it is applied to 44 change variable magnitude, variable frequency voltage 45 into dependable constant voltage and steady frequency 46 1064-1246/15/$35.00 © 2015 -IOS Press and the authors. All rights reserved U n c o r r e c t e d A u t h o r P r o o f 2 R.S.S. Kumar and S.M. Girirajkumar / Z-Source Inverter Fed Induction Motor Drive control supply [11]. For both voltage-boosting and inversion 47 with an attractive inverter topology it presents a differ-48 ent choice [12]. The Z-source inverters can be planned 49 with their maximum modulation ratio set to the prevail-50 ing nominal case. Any flow in energy demand is next 51 supervised by fluctuating the inverter shoot-through 52 time duration, which in result is a third state introduced 53 for gaining voltage boosting in Z-source inverter [14]. 54 The induction motor drive system fed by z-source 55 inverter may have the benefits ...

ABSTRACT:The proposed work deals with optimal tuning of a Proportional-Integral-Derivative (PID) controller for speed control of a DC shunt motor. PID controllers are widely used in industrial plants because of their simplicity and robustness. Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. So the control engineers are on look for automatic tuning procedures. The performance of Ziegler-Nichols method, one of the widely accepted conventional methods has been compared and analyzed with the intelligent tuning technique called the Simulated Annealing method (SA). The results establishes that tuning the PID controller using SA technique which comes under evolutionary programming has proved its excellence in giving better results by improving the steady state characteristics and performance indices.

Automatic control has played a vital role in the advancement of engineering and science. It is also essential in such industrial operations as controlling pressure, temperature, humidity, viscosity and flow in the process industries. Proportional Integral Differential (PID) controllers marked its place in many of the industrial processes. Tuning a controller is the adjustment of its control parameters. Computational Intelligence (CI) an off shoot of Artificial Intelligence relies on heuristic algorithms mainly evolutionary computation. Swarm intelligence (SI) a derivative of CI, describes the collective behaviour of decentralized, selforganized systems. Ant behaviour was the inspiration for the Meta heuristic optimization technique. This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a (PID) controller for a highly nonlinear conical tank system. The proposed work discusses in detail, the ACO, a CI technique, and its application over the parameter tuning of a PI controller in a real time process. The designed controller"s ability in tracking a given set point is compared with an Internal Model Control (IMC) tuned controller.

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