Novel Framework for Navigation using Enhanced Fuzzy Approach with Sliding Mode Controller

Abstract

The reliability of any embedded navigator in advanced vehicular system depends upon correct and precise information of navigational data captured and processed to offer trustworthy path. After reviewing the existing system, a significant trade-off is explored between the existing navigational system and present state of controller design on various case studies and applications. The existing design of controller system for navigation using error-prone GPS/INS data doesn‟t emphasize on sliding mode controller. Although, there has been good number of studies in sliding mode controller, it is less attempted to optimize the navigational performance of a vehicle. Therefore, this paper presents a novel optimized design of a sliding mode controller that can be effectively deployed on advanced navigational system. The study outcome was found to offer higher speed, optimal control signal, and lower error occurances to prove that proposed system offers reliable and optimized navigational services in contrast to existing system.

A dynamic cruise control system (DCCS) for effective navigation system

“…In order to enhance the performance of the navigational system, the introduced study incorporats the variables of the mathematical model with the planar motion of the vehicle. Also, it has been aimed to improvise the fuzzy controller using sliding mode (proposed in [46]) and achieve accurate direction of mobility considering the vehicular characteristics as a constraint. In this model, the fuzzy logic is associated with the formulation of the various rule set to have a better dependency on resources during the navigational process.…”

An Important Landmarks Construction for a GIS-Map based on Indexing of Dolly Images

“…If the intersection point between only two segments that means we need to save two images associated with this point feature class such as points (4 and 8) in the Figure 4. Each image represents one segment of road, in the case of point (4) the first image represents the segment (13) and the second image represent the segment (16). If the intersection point between three segments that means we need to save four images associated with this point feature class such as points (1, 2 and 3).…”

“…The input to the system is a pathway depends on the segment number of the road rout. In Figure 5, there are three cases of the input rout step when the route (1) has the segments number (1,2,9,4,5), while the route (2) has the segments number (16,14,12) and route (3) has the segments number (8, 9, 4, 3, 2, 7) consecutively.…”

“…Recently, the most camcorders are mounted with GPS and enabled the linkage between video and GPS. Most videos present only graphics without a position of such video [15,16]. If the video can be visualized with its traveling path on GIS and snapshot of video can be gotten with its location, this will be very useful for GIS people to make use this media for updating GIS data [17,18].…”

An implementation of optimal control methods (LQI, LQG, LTR) for geostationary satellite attitude control

“…The attitude control of geostationary spacecrafts [1][2][3][4], has important applications for telecommunication space missions such as pointing and for motion flying, the Attitude Determination and Control Subsystem (ADCS) provides attitude information and maintains the required spacecraft attitude during all phases of the mission, starting at spacecraft separation from the launch vehicle and throughout its operational lifetime [5][6][7][8].The selection of an ADCS is a function of many factors, Including mission objectives, satellite design, distributions torques, design constraints and stabilization required. Several control methods have been developed over the past years since the first satellite was launched.…”