Position Control of 1-DOF High-Precision Rotary Table using Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller

Research of position control of 1-DOF high-precision rotary table using adaptive Neuro-Fuzzy inference system (ANFIS) controller has been done. In the closed-loop system without a controller, the response was oscillating and pounding caused by inertial torque. It because a rotary table receives a considerable load. Based on this, the ANFIS controller is needed to eliminate oscillations and compensate for the inertia. The result shows that there was no oscillation or overshoot with the steady-state error value of 2.27% for the reference angle of 45°, valued at 0.10% reference angle of 180°, and valued at 0% reference angle of 360°. The result proves that ANFIS controllers can eliminate oscillations with and compensate for inertia

Lepironia articulata as a sustainable acoustic absorber

Lepironia articulata is found abundant in a swamp and along streams in West Malaysia and it is commonly used for grey water treatment, numerous traditional craft and now commercialise as an organic straw. However, there is a scarcity of knowledge on the physical and acoustical properties of this natural fibre. Therefore, this study was to determine the potential of Lepironia articulata as acoustic absorber. The absorption coefficient was tested using the impedance tube method (ASTM E1050-98) for four different structure arrangements, namely “axial”, “horizontal”, “crossed” and “combination” made up of Lepironia articulata with the diameter ranging from 2 to 4 mm and 4 to 7 mm respectively and the thickness remains at 50 mm. The influence of air gap of 0 to 25 mm, in 5 mm increment was introduced in each sample and other physical properties such as density, porosity and tortuosity were investigated. The results revealed that the Lepironia articulata in horizontal, crossed and combination arrangements showed greatest absorption performance especially in the low frequency range compared to the axial arrangement. If compared between samples with the range diameter of 4 to 7 mm and 2 to 4 mm, bigger stalks diameter in axial arrangement exhibits the least NRC value. Next, air gaps have great influence at low frequency range whereby it shifted the peaks and sound absorption coefficient curve toward lower frequency. Sound absorption coefficient increases as porosity increase and decrease as density�tortuosity increase. Overall, Lepironia articulata has the potential to be used as a sustainable acoustic absorber as all the samples has the NRC value more than or equal to 0.20

A Trip Planning-Assisted Energy Management System for Connected PHEVs: Evaluation and Enhancement

The built-in Energy Management System (EMS) of Plug-in Hybrid Electric Vehicles (PHEVs) plays an important role in the fuel efficiency of these vehicles. Recently, it has been revealed that prior knowledge of the upcoming trip can assist EMS to enhance the distribution of power between the energy sources, i.e. the engine and the motor-generators used in PHEVs, resulting in lower fuel consumptions. This dissertation intends to further investigate on a Trip Planning-assisted EMS (TP-assisted EMS), by studying its feasibility for online implementation, and evaluating its performance and robustness with respect to the trip data uncertainties in various practical scenarios, to ultimately answer this question: Does the TP-assisted EMS function as a reliable system for PHEVs which can outperform conventional methods? This research starts with improving upon an existing Trip Planning module with an emphasis on its online integration with the EMS module. In particular, the power-balance model of PHEVs is introduced, which is computationally inexpensive and yet adequately accurate to be used for the optimizations involved in the Trip Planning module. To speed up the optimizations, the use of Particle Swarm Optimization (PSO) algorithm is suggested. These modifications result in the reduction of computational time, making TP-assisted EMS module suitable for online implementations. Once the TP-assisted EMS module has been integrated with a high-fidelity model of the baseline PHEV, namely, 2013 Toyota Prius PHEV, its performance and sensitivity/robustness have been extensively studied through Monte Carlo simulations, where numerous samples of standard as well as real-world drive cycles have been tested. However, in order to use these data for Model-in-the-Loop (MIL) and Hardware-in-the-Loop (HIL) tests, a Micro-trip Generator block has been developed. This block automatically segments the drive cycles, similar to the way that trip information is obtained in practice, making the simulation samples compatible with the Trip Planning module. Statistical analyses of the simulation results show that the TP-assisted EMS is a superior controller compared to the conventional EMS strategies. Moreover, these simulations present one of the first sensitivity analyses that have been performed in the context of TP-assisted EMS for PHEVs, showing that this system is robust despite the existence of random disturbances and meanwhile has low sensitivity against variations of the design parameters