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For closed-loop controlled DC-AC inverter system, the performance is highly influenced by load variations and online current measurement. Any variation in the load will introduce unwanted periodic error at the inverter output voltage. In addition, when the current sensor is in faulty condition, the current measurement will be imprecise and the designed feedback control law will be ineffective. In this paper, a sensorless continuous sliding mode control (SMC) scheme has been proposed to address these issues. The chattering effect due to the discontinuous switching nature of SMC has been attenuated by designing a novel boundary-based saturation function where the selection of the thickness of boundary is dependent to the PWM signal generation of the inverter. In order to remove the dependency on the current sensor, a particle swarm optimization(PSO) based modified observer is proposed to estimate the inductor current in which the observer gains are optimized using PSO by reducing the estimation errors cost function. The proposed dynamic smooth SMC algorithm has been simulated in MATLAB Simulink environment for 0.2-kVA DC-AC inverter and the results exhibit rapid dynamic response with a steady-state error of 0.4V peak-to-peak voltage under linear and nonlinear load perturbations. The total harmonic distortion (THD) is also reduced to 0.20% and 1.14% for linear and non-linear loads, respectively.

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This paper proposes an extended model based predictive flux control (MPFC) with modified disturbance observer speed loop for induction motors. The main advantages of the proposed method are the improvement of load estimation, the suppression of current overshoot at step changes in reference speed and the removal of weighting factor in the newly formulated cost function. Weighting factor is removed by using extended reference transformation which translates reference torque, generated by the speed controller, into equivalent stator flux vector eliminating the challenging task of gain tuning at different points of operation. Then, the load torque is considered as an unknown disturbance and the accuracy of load estimation during speed jumps is improved by using a reduced order PI observer (ROPIO) with low-pass filter (LPF) for improved integration. The observer is combined with disturbance rejection based control to design a composite speed controller replacing conventional PI loop. The effectiveness of the proposed method is validated on a two-level three-phase inverter fed induction motor drive using dSpace DS1104 controller board. The dynamic response of the proposed method is compared to previously proposed disturbance observer based controller (DOBC) for predictive torque control method. The load estimation error of the proposed method at speed jumps is reduced by 66% while current surges are also suppressed effectively.