This article presents the development of a low-cost microcontroller-based interface for a microbioreactor operation. An Arduino MEGA 2560 board with 54 digital input/outputs, including 15 pulse-width-modulation outputs, has been chosen to perform the acquisition and control of the microbioreactor. The microbioreactor (volume = 800 µL) was made of poly(dimethylsiloxane) and poly(methylmethacrylate) polymers. The reactor was built to be equipped with sensors and actuators for the control of reactor temperature and the mixing speed. The article discusses the circuit of the microcontroller-based platform, describes the signal conditioning steps, and evaluates the capacity of the proposed low-cost microcontroller-based interface in terms of control accuracy and system responses. It is demonstrated that the proposed microcontroller-based platform is able to operate parallel microbioreactor operation with satisfactory performances. Control accuracy at a deviation less than 5% of the set-point values and responses in the range of few seconds have been recorded.
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.
This paper proposes an average current mode controller (ACMC) for a single-phase bridgeless power factor correction (PFC) circuit using a single ended primary inductor converter (SEPIC) via second-order model reduction. The superiority of the proposed controller is PFC accomplished at power up to 350 W with high efficiency via the second-order model reduction. The design and implementation of ACMC on the converter operated with continuous conduction mode (CCM) is explained in detail. ACMC forces input current to follow sinusoidal current reference at different power levels and sustain high power factor (PF). The proposed controller is designed based on the theoretical analysis operation of the circuit. For verification, MATLAB/Simulink simulations are carried out and validation through an experiment test rig for 110-220 Vrms input, 100 Vdc/ 350 W output prototype at 20 kHz switching frequency. It is proven that the proposed controller strategy accomplishes high PF, high efficiency and conformity with the simulation.