Permanent Magnet Synchronous Motor (PMSM) is an AC motor in which the rotor must operate at synchronous speed in all load conditions. If the motor mechanical load increases, the motor can lose synchronization, stopping the motor. In sensorless control systems, i.e., those without speed sensors, the speed is estimated from the stator current using the Model Reference Adaptive System (MRAS) algorithm. Because such systems therefore cannot detect the loss of synchronization, it is necessary to design a synchronization loss detection system. Here, another speed estimation calculated from the stator currents and voltages is introduced. The speed is called a calculated speed. In the normal condition (synchronous condition), estimated speed and calculated speed will be approximately equal. However, when synchronization loss occurs, these two speed values diverge. On the basis of this phenomenon, a synchronization loss detection algorithm and method are developed. The algorithm’s speed-delta boundary values and detection period must be determined. The greater the setpoint speed, the higher the speed-delta boundary values but the smaller the detection period. The experiments confirm that the proposed algorithm is able to effectively detect the occurrence of synchronization loss.
A dynamic mathematical model for a new structure of precision air conditioning (PAC) has been developed. The proposed PAC uses an additional secondary condenser for relative humidity regulation compared to a basic refrigeration system. The work mechanism for this system and a vapour-compression cycle process of the system are illustrated using psychrometric chart and pressure-enthalpy diagram. A non-linear system model is derived based on the conservation of mass and energy balance principles and then linearized at steady state operating point for developing a 8 th -order state space model suited for multivariable controller design. The quality of linearized model is analyzed in terms of transient response, controllability, observability, and interaction between input-output variables. The developed model is verified through simulation showing its ability for imitating the nonlinear behavior and the interaction of input-output variables. AbstrakPemodelan Sistem Tata Udara Presisi Berstruktur Baru Menggunakan Kondenser Sekunder untuk Pengaturan RH. Tulisan ini membahas penurunan model matematis dinamis untuk sistem tata udara presisi (PAC) dengan struktur baru. Berbeda dengan sistem refrigerasi umumnya, sistem PAC yang diusulkan menggunakan kondenser sekunder tambahan untuk pengaturan kelembaban relatif. Mekanisme kerja dan proses siklus kompresi uap sistem ini diilustrasikan menggunakan psychrometric chart dan diagram tekanan-entalpi. Model nonlinier sistem diturunkan berbasis konservasi massa dan prinsip kesetimbangan energi dan kemudian dilinierisasi pada titik kerja untuk mengembangkan model ruang keadaan orde-8 yang cocok untuk disain pengendali multivariabel. Kualitas model linier dianalisa dari aspek respons transien, kontrolabilitas, observabilitas, dan interaksi antar variabel masukan-keluaran. Model yang dikembangkan diverifikasi secara simulasi menunjukkan kemampuan model untuk meniru karakteristik nonlinier dan interaksi variabel masukan-keluaran.
As one part of the advanced driver assistance systems (ADAS), adaptive cruise control (ACC) is introduced to reduce the possibility of traffic accidents by controlling the throttle and the pressure on the brakes to maintain a safe distance from the vehicle in front. Generally, linearized model-based controllers are used in the ACC. In this paper, a new approach to ACC's inner loop is developed by designing the controller using neural network predictive control (NNPC) which integrates the capability of artificial neural networks (ANN) to imitate vehicle characteristics and model predictive control (MPC) to obtain the minimized quadratic error between future reference trajectories and predicted outputs. Two separate control loops will be used: an outer loop based on a decision algorithm, and the PI controller, which will give the inner loop a speed reference to maintain the safe distance from the vehicle in front. NNPC is used in the inner loop to manipulate throttle and brake pressure on the brakes in order to control the speed of the following vehicle. Simulations will be carried out using software-in-the-loop (SIL) between CarSim and Simulink. The ANN model is identified and verified to mimic the nonlinearity behavior of the vehicle model using the mean square error (MSE) parameter. The results of this study are that the ANN model is able to imitate the vehicle dynamic with MSE equal to 0.0095, and the controller can maintain a safe distance while having a smooth response.
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