Finite control set predictive torque control for induction motor drive with simplified weighting factor selection using TOPSIS method

Abstract

Finite control set predictive torque control (FCS-PTC) becomes popular for induction motor drives due to its simple structure and flexibility of including additional control parameters into the control law. However, primary concern of this control technique is the selection of suitable weighting factors in the cost-function. Usually, empirical method is used to select the weighting factors, which is time-consuming and heuristic process. In this study, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is introduced in the cost-function optimization to simplify the difficulties involved in the weighting factor selection. This method selects an optimal control action, which is closer to positive ideal control action and far away from negative ideal control action. This e n s u r e st h es e l e c t i o no fo p t i m a lc o n t r o la c t i o ni ne a c hs a m p l i n gp e r i o db a s e do nt h ep r i o r i t i e sg i v e nt oc o n t r o l parameters in the cost-function. Further, to reduce the computational burden of proposed technique, a predefined set of switching states are used for the cost-function optimization based on previous optimal control action. Both simulation and experimental studies are carried out for a two-level voltage source inverter fed induction motor drive. These results are compared with conventional FCS-PTC technique to highlight the merits of proposed technique.

Modified predictive torque and flux control for open end winding induction motor drive based on ranking method

“…This has a direct influence on voltage vector selection. In [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41], analytical and empirical methods are employed for proper tuning of weight factor which results in complex control.…”

“…It necessitates a lot of search process prior to control. For IM drive control in [36,37], multi-decision criteria-based VIKOR and TOPSIS methods are introduced. In this process, weighting factor coefficients are not altogether removed and analysed with only torque and flux control terms.…”

Simulation of electric heating prediction model by internet of things technology and room thermal performance analysis

“…Because of its excellent comprehensive quality of model control, it is suitable for the control of complex industrial processes with high real-time calculation requirements and large changes in environmental parameters. For complex control problems, predictive control technology can provide better control performance than proportional integral differential (PID) control technology, which has been applied in large-scale process control systems [3].…”

Simplified Predictive Torque Control for Surface-Mounted PMSM Based on Equivalent Transformation and Partition Method

“…Based on the approaches above, some simplified algorithms for PTC have been proposed. In [13], the number of candidate voltage vectors is reduced by introducing a direct torque control (DTC) switching table in the induction motor drive system; In [14], the complex weighting factor selection process in the cost function is simplified by using the TOPSIS algorithm. In [15], a cost function with the consideration of the voltage vector error is constructed based on duty cycle calculation for PTC, and the candidate voltage vectors and duty cycles are determined according to the geometric position of the reference voltage vector in the inverse triangular matrix.…”