Browsing by Author "Leblebicioglu, Kemal"

Now showing 1 - 5 of 5

Citation - WoS: 2
Citation - Scopus: 2
Control structure design with constraints for a slung load quadrotor system
(Sage Publications Ltd, 2024) Ergezer, Halit; Ergezer, Halit; Leblebicioglu, Kemal; 293396
We propose a control structure for a quadrotor carrying a slung load with swing-angle constraints. This quadrotor is supposed to pass through the waypoints at specified speeds. First, a cascaded PID autopilot is designed, which adaptively gives attention to position and speed requirements as a function of their errors. Its parameters are found from an optimization problem solved using the PSO algorithm. Second, this controller's performance is improved by adding the Complementary Controller employing an ANN. 5. Training data for the ANN is created by solving optimal control problems. The ANN is activated when the swing angle constraint is about to be violated. It is trained using optimal control values corresponding to the cases where the swing angle falls in a particular band about the upper swing angle constraint. Simulations are performed in a MATLAB environment. Finally, some of the simulation results are validated on a physical system.
Citation - WoS: 0
Citation - Scopus: 0
Hierarchical Decision Making and Decision Fusion
(Ieee, 2007) Beldek, Ulas; Leblebicioglu, Kemal
In this study, a hierarchical decision making structure possessing a decision fusion technique is proposed in order to solve decision making problems efficiently. The proposed structure mainly depends on effects of the decisions made in the lower levels to decisions in the upper levels up to an activation degree. The proposed hierarchical structure is used for detecting the fault degrees for single and multiple fault scenarios artifically generated in a four tank system. The results obtained demonstrate the effectiveness of the proposed hierarchical decision making structure.
Citation - WoS: 3
Citation - Scopus: 5
Local decision making and decision fusion in hierarchical levels
(Springer, 2009) Beldek, Ulas; Beldek, Ulaş; Leblebicioglu, Kemal; 59950
Hierarchical problem solving is preferred when the problem is overwhelmingly complicated. In such a case, the problem should better be analyzed in hierarchical levels. At each level, some temporary solutions are obtained; then a suitable decision fusion technique is used to merge the temporary solutions for the next level. The hierarchical framework proposed in this study depends on reutilization or elimination of previous level local agents that together perform the decisions due to a decision-fusion technique: a performance criterion is set for local agents. The criterion checks the success of agents in their local regions. An agent satisfying this criterion is reutilized in the next level, whereas an agent not successful enough is removed from the agent pool in the next level. In place of a removed agent, a number of new local agents are developed. This framework is applied on a fault detection problem.
Citation - WoS: 3
Citation - Scopus: 5
Online path planning for unmanned aerial vehicles to maximize instantaneous information
(Sage Publications inc, 2021) Ergezer, Halit; Ergezer, Halit; Leblebicioglu, Kemal; 293396
In this article, an online path planning algorithm for multiple unmanned aerial vehicles (UAVs) has been proposed. The aim is to gather information from target areas (desired regions) while avoiding forbidden regions in a fixed time window starting from the present time. Vehicles should not violate forbidden zones during a mission. Additionally, the significance and reliability of the information collected about a target are assumed to decrease with time. The proposed solution finds each vehicle's path by solving an optimization problem over a planning horizon while obeying specific rules. The basic structure in our solution is the centralized task assignment problem, and it produces near-optimal solutions. The solution can handle moving, pop-up targets, and UAV loss. It is a complicated optimization problem, and its solution is to be produced in a very short time. To simplify the optimization problem and obtain the solution in nearly real time, we have developed some rules. Among these rules, there is one that involves the kinematic constraints in the construction of paths. There is another which tackles the real-time decision-making problem using heuristics imitating human- like intelligence. Simulations are realized in MATLAB environment. The planning algorithm has been tested on various scenarios, and the results are presented.
Citation - WoS: 5
Citation - Scopus: 9
Strategy creation, decomposition and distribution in particle navigation
(Elsevier Science inc, 2007) Beldek, Ulas; Beldek, Ulaş; Leblebicioglu, Kemal; 59950
Strategy planning is crucial to control a group to achieve a number of tasks in a closed area full of obstacles. In this study, genetic programming has been used to evolve rule-based hierarchical structures to move the particles in a grid region to accomplish navigation tasks. Communications operations such as receiving and sending commands between particles are also provided to develop improved strategies. In order to produce more capable strategies, a task decomposition procedure is proposed. In addition, a conflict module is constructed to handle the challenging situations and conflicts such as blockage of a particle's pathway to destination by other particles. (C) 2006 Elsevier Inc. All rights reserved.