Choon Lih Hoo

Steady-State Integral Proportional Integral Controller for PI Motor Speed Controllers

The output of the controller is said to exceed the input limits of the plant being controlled when a control system operates in a non-linear region. This process is called the windup phenomenon. The windup phenomenon is not preferable in the control system because it leads to performance degradation, such as overshoot and system instability. Many anti-windup strategies involve switching, where the integral component differently operates between the linear and the non-linear states. The range of state for the non-overshoot performance is better illustrated by the boundary integral error plane than the proportional–integral (PI) plane in windup inspection. This study proposes a PI controller with a separate closed-loop integral controller and reference value set with respect to the input command and external torque. The PI controller is compared with existing conventional proportional integral, conditional integration, tracking back calculation, and integral state prediction schemes by using ScicosLab simulations. The controller is also experimentally verified on a direct current motor under no-load and loading conditions. The proposed controller shows a promising potential with its ability to eliminate overshoot with short settling time using the decoupling mode in both conditions.

A Brief Survey on Artificial Intelligence Methods in Synchronous Motor Control

Many industrial applications require efficient servo drives and speed control to obtain the necessary performance with respect to different applications. As time passes, artificial intelligence has grown and replaced many traditional control methods in order to attain greater robustness to uncertainties, faster dynamic response and smaller position and speed errors. This paper briefly reviews several artificial intelligence implementations in synchronous motor control systems and briefly indicates the advantages and disadvantages of each method.

Development of Fuel Injector Monitoring Using Strain Gauge Signal

The Fuel injector is an important component in a vehicle engine for determining the performance of an engine. It is believed that, by knowing the current state of the injector, one can take any prior safety measure and ensuring the optimal performance of the engine. However, it is very difficult to study and analyse the fuel injection system in real time during the operation of the vehicle. A study was conducted in developing a method to monitor the fuel injector using the strain signal generated from the strain gauge sensors installed on the fuel injector. This method is practically implementable and can be used on the actual operation of the engine. A research rig was developed in order to visualise the behaviour of the injector at any instant by obtaining the three key parameters from the strain gage sensors which are the pulse width (ms), frequency (Hz) and pressure (bar). All data obtained from this experiment will be analysed using the Matlab software, where the I-kaz (Z∞) will be applied as the main method to clearly visualize the operation of the machine. The result shows that for the same pulse width and pressure, the series have the same pattern for I-kaz coefficient. They have a consistent trend compared to the Skewness and Kurtosis parameters. This method serves to predict and describe the behaviour of the fuel injector to ease the monitoring task at any instant throughout the engine operation.

A floating point conversion algorithm for mixed precision computations

The floating point number is the most commonly used real number representation for digital computations due to its high precision characteristics. It is used on computers and on single chip applications such as DSP chips. Double precision (64-bit) representations allow for a wider range of real numbers to be denoted. However, single precision (32-bit) operations are more efficient. Recently, there has been an increasing interest in mixed precision computations which take advantage of single precision efficiency on 64-bit numbers. This calls for the ability to interchange between the two formats. In this paper, an algorithm that converts floating point numbers from 64-to 32-bit representations is presented. The algorithm was implemented as a Verilog code and tested on field programmable gate array (FPGA) using the Quartus II DE2 board and Agilent 16821A portable logic analyzer. Results indicate that the algorithm can perform the conversion reliably and accurately within a constant execution time of 25 ns with a 20 MHz clock frequency regardless of the number being converted.

Algorithm for Real-Time AI-Based PI Controller in PMSM

Motor control is essential for good performance especially now the servo and speed drives application has gaining much attention. Proportional-integral controller is popular among motor control but yet is mostly with preset control parameter. The proposed real-time artificial intelligence based controller is aimed for adaptive control throughout the whole motor operating condition. The proposed has improved and better speed and torque performance in constant and ramp input functions but not in the step input function and the attempt requires further research and modification for global application.