Kok Yew Ng

Development of a convenient wireless control of an autonomous vehicle using apple iOS SDK

Remote control of autonomous robots/vehicles has been an interesting research area with many ongoing developments being done. However, most implementation methods either require additional hardware or involve certain trained individuals to operate the system. This paper aims to present a convenient method to wirelessly remote control a car mounted with the BlackWidow 1.0 microcontroller using the iPhone, with software written on the iOS SDK platform. A Wi-Fi standard of 802.11b broadcast from the microcontroller was used for experimentation.

New result in robust actuator fault reconstruction with application to an aircraft

This paper presents a robust actuator fault reconstruction scheme for linear uncertain systems using sliding mode observers. In existing work, fault reconstruction via sliding modes is limited to either linear certain systems subject to unknown inputs, relative degree one systems or a specific class of relative degree two systems. This paper presents a new method that is applicable to a wider class of systems with relative degree higher than one, and can also be used for systems with more unknown inputs than outputs. The method uses two sliding mode observers in cascade. Signals from the first observer are processed and used to drive the second observer. Overall this results in actuator fault reconstruction being feasible for a wider class of systems than existing methods. In this paper the results are applied to an aircraft system.

Real-Time Lane Detection and Rear-End Collision Warning System on a Mobile Computing Platform

Accident prevention systems have recently been a part of many modern cars to reduce injuries and casualties on the road. However, the high cost of components and equipment have limited such safety systems to higher-end and luxury vehicles. This paper proposes an economical method of using a smartphone application for real-time lane detection and rearend collision warning system for drivers on the road. The Android-based application uses image-processing algorithms coupled with the monoscopic camera on the smartphone as the main sensor to perform lane and vehicle detections. The novelty of this work lies in the use of the monocular vision of the camera to estimate the distance with the vehicle up ahead. The system is able to distinguish unintentional lane departure and if the driver is traveling too close to the vehicle ahead. An acoustic warning will notify the driver of a potential accident.

Disturbance Decoupled Fault Reconstruction using Sliding Mode Observers

Abstract The objective of a robust fault reconstruction scheme is to generate an accurate reconstruction of the fault that is unaffected by disturbances. A typical method for robust fault reconstruction is to reconstruct the faults and disturbances, which is conservative and requires stringent conditions. This paper investigates and presents conditions that guarantee a fault reconstruction that rejects the effects of disturbances, which are less stringent than those of previous work. A VTOL aircraft model is used to validate the work of this paper.

Real-time face detection and motorized tracking using ScicosLab and SMCube on SoC's

This paper presents a method for real-time detection and tracking of the human face. This is achieved using the Raspberry Pi microcomputer and the Easylab microcontroller as the main hardware with a camera mounted on servomotors for continuous image feed-in. Real-time face detection is performed using Haar-feature classifiers and ScicosLab in the Raspberry Pi. Then, the Easylab is responsible for face tracking, keeping the face in the middle of the frame through a pair of servomotors that control the horizontal and vertical movements of the camera. The servomotors are in turn controlled based on the state-diagrams designed using SMCube in the EasyLab. The methodology is verified via practical experimentation.

ReCon-AVe: Remote Controlled Automobile Vehicle for Data Mining and Analysis

This paper explores the control of an automobile mounted with a BlackWidow 1.0 microcontroller from a remote location using a smartphone or a computer as a data mining and analysis device as well as for the purposes of first response search and rescue during a disaster relief operation. Custom application programs; ReCon-A for the Android platform and ReCon-V for Microsoft Windows are designed specifically for this project to control the ReCon-AVe vehicle. It is found that the remote controllers are able to control the automobile from distance of more than 20m away in indoor conditions using direct connections. In outdoor conditions, communications using the computer as the remote controller can reach up to 35m while using the smartphone can achieve up to 25m away. Other than that, tests show that the response time of ReCon-AVe is less than 60ms in indoor conditions and 85ms in outdoor conditions. In addition, it can provide visual feedback to the user at a minimum 16fps that also comes with a panning capability. Apart from that, ReCon-AVe proves its capabilities to acquire two different types of sensory data obtained from sensors and then have them transferred back to the user wirelessly for data mining and analysis.

New results in disturbance decoupled fault reconstruction in linear uncertain systems using two sliding mode observers in cascade

This paper presents a disturbance decoupled fault reconstruction (DDFR) scheme using two sliding mode observers in cascade. Measurable signals from the first observer are found to be the output of a fictitious system that is driven by the fault and disturbances. Then the signals are fed into a second observer which will reconstruct the fault. Sufficient conditions which guarantee DDFR are investigated and presented in terms of the original system matrices, and they are found to be less conservative than if only one single observer is used; therefore DDFR can be achieved for a wider class of systems using two sliding mode observers. A simulation example validates the claims made in this paper.

Tolerance towards sensor failures: an application to a double inverted pendulum

In this paper we present a sensor fault tolerance control scheme that is applied to a double inverted pendulum. Sensor faults will affect the system when it is used in closed-loop feedback. The scheme uses a linear observer reconstruct the sensor fault and to subtract the reconstruction from the faulty sensor. The net result is then used for the closed-loop feedback. It was found that the scheme restored the performance to the fault-free scenario