Browsing by Author "Caska, Serkan"

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Adaptation of Symbolic Discrete Control Synthesis for Energy-Efficient Multi-Pocket Milling
(MDPI, 2024) Caska, Serkan; Ozbaltan, Mete
In engineering, cost minimization, especially in Computer Numerical Control (CNC) machining like pocket milling, is crucial. Existing tool path definition software often lacks optimization, particularly at critical starting and ending points. This study optimizes CNC machine tool paths for energy-efficient multi-pocket milling, utilizing the Symbolic Discrete Control Synthesis (SDCS) method for formal correctness. In our work, the tool path generation is formulated as a traveling salesman problem. We introduce a modeling framework to adapt SDCS to multi-pocket-milling processes, aiming to enhance precision and efficiency for potential cost savings, including energy and time, in engineering applications. This study reports experimental and comparative results, where comparative evaluations were made using metaheuristic algorithms. Our proposed approach improves CNC machining processes for multi-pocket milling. We experimentally evaluate our control algorithms and demonstrate and validate our approach through case studies.
Altitude Control of Quadcopter with Symbolic Limited Optimal Discrete Control
(Springer Nature, 2024) Ozbaltan, Mete; Caska, Serkan
In recent years, quadcopter UAVs have been extensively utilized. Controlling quadcopters is a major concern, and researchers are actively studying it. In this study, altitude control of a quadcopter UAV is achieved using the symbolic limited optimal discrete controller synthesis technique. The resulting controller is compared with the adaptive PID control method, where the PID controller's parameters are determined using the Dragonfly algorithm. The findings show the superior performance of our approach.
Incorporating Symbolic Discrete Controller Synthesis into a Virtual Robot Experimental Platform: An Implementation with Collaborative Unmanned Aerial Vehicle Robots
(MDPI, 2024) Ozbaltan, Mete; Caska, Serkan
We introduce a modeling framework aimed at incorporating symbolic discrete controller synthesis (DCS) into a virtual robot experimental platform. This framework involves symbolically representing the behaviors of robotic systems along with their control objectives using synchronous programming techniques. We employed DCS algorithms through the reactive synchronous environment ReaX to generate controllers that fulfill specified objectives. These resulting controllers were subsequently deployed on the virtual robot experimental platform Simscape. To demonstrate and validate our approach, we provide an implementation example involving collaborative UAV robots.