Speed Performance Improvement Of Three-Phase Induction Motor Drives Using Adaptive Sliding Mode Controller

Mohd Aziri, Muhammad Hasif (2020) Speed Performance Improvement Of Three-Phase Induction Motor Drives Using Adaptive Sliding Mode Controller. Masters thesis, Universiti Teknikal Malaysia Melaka.

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Abstract

The induction motor is widely used in industrial applications. The most type of induction motor used in the industrial applications is three-phase squirrel cage AC induction motor. Several industrial applications use the induction motor because of its ruggedness, reliability and relatively low cost. However, more complexity control scheme is required for the induction motor because it is highly non-linear in a dynamic structure. In addition, the rotor currents and flux-linkage of induction motor also cannot be directly measured. The modified classical sliding mode control (SMC) algorithm is developed based on the conventional robust controller with the adaption of switching gain and discontinuous sigmoid functions to eliminate the undesirable chattering phenomenon. The main focus of this research is to design a sliding mode control strategy that provides speed performance improvement of delay time (td), rise time (tr), peak time (tp), maximum % overshoot (Mp), settling time (ts) and steady-state error (ess) for the three-phase induction motor drives. More specifically, research objectives are to design a sliding mode controller by using an adaptive control strategy and compare with conventional SMC and PI speed controller. Then, the developed speed controller is implemented in an experimental rig based on indirect field-oriented control (IFOC) by using the digital signal processor (DSP) to achieve high performance control characteristics in controlling torque and rotor flux effectively. The PI or PID controllers are tuned to improve speed control issues of AC induction motor due to load variations and changes in parameters. However, the conventional strategy of the PI controller is realized cannot achieve better performance when the input of load variations are applied. Specifically, the algorithm to overcome these issues is proposed by using an ASMC and the speed control performances are tested in simulation by using PSIM software. Practically, the experimental works on hardware rigs are based on high voltage digital motor control (HVDMC) with power factor correction (PFC) from Texas Instruments (TI) that attached with the floating-point of TMS320F28335 DSP to analyze and validate the performance of an ASMC control algorithm. Moreover, the features of an ASMC are compared with conventional SMC and PI controller to improve the performance of an ASMC control algorithm. As a result, highperformance control of AC induction motor is achieved for different speed commands and loaded conditions as compared to conventional controllers. Technically, simulated results at 1400rpm with no-load conditions of maximum % overshoot (ASMC, Mp=14.4%), (SMC, Mp=24.42%), (PI, Mp=30.41%) and steady-state error (ASMC, ess=1.76rpm), (SMC, ess=6.02rpm), (SMC, ess=2.23rpm) are clearly summarized the ASMC is more superior performances compared with differences speed controllers of SMC and PI respectively. Supremely, experimental results for the ASMC at 1400rpm with no-load conditions of maximum % overshoot (Mp=0.28%) and steady-state error (ess=3.21rpm) are achieved comprehensive performances. Apart from this, the benefit of this research work is importantly desired for the non-linear of the AC motor to achieved dynamic performances such as fast response and also practically used at variable speed conditions.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Sliding mode control, Control theory, Electric motors, induction, Automatic control, Induction Motor Drives
Subjects:	T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery
Divisions:	Library > Tesis > FKE
Depositing User:	F Haslinda Harun
Date Deposited:	27 Oct 2021 16:10
Last Modified:	27 Oct 2021 16:11
URI:	http://eprints.utem.edu.my/id/eprint/25378
Statistic Details:	View Download Statistic

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