“…DCS approaches are applied in several disciplines, such as software engineering, robotics, control systems and communication networks, for synthesizing controllers that can effectively handle complex systems. For example, DCS was applied to generate controllers for robotic systems for precise control and steady motion in [13]; Ref. [14] addressed DCS for communication networks that provide dependable and effective data flow; and [15] performed DCS to create controllers that guarantee the safety and correctness of programs.…”
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.
“…DCS approaches are applied in several disciplines, such as software engineering, robotics, control systems and communication networks, for synthesizing controllers that can effectively handle complex systems. For example, DCS was applied to generate controllers for robotic systems for precise control and steady motion in [13]; Ref. [14] addressed DCS for communication networks that provide dependable and effective data flow; and [15] performed DCS to create controllers that guarantee the safety and correctness of programs.…”
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.
“…where the max operator is applied elementwise. The normal vectors are unaffected by c and α as shifting a zonotope and stretching its generators does not change its normal vectors (see proof of [46,Thm. 1]).…”
Tool presentation: When formally verifying models of cyber-physical systems, it is obviously important that their verification results can be transferred to all previous observations of the modeled systems. Our tool CORA makes it possible to transfer safety properties by checking whether all measurements of the real system lie in the set of reachable outputs of the corresponding model -- we call this reachset conformance checking. In addition, we provide strategies to establish reachset conformance by injecting nondeterminism in models. This can be seen as some form of system identification, where instead of finding the most likely parameters, we compute a set of parameter values -- not only for the model dynamics but also for the set of disturbances and measurement errors -- to establish reachset conformance. By replacing real measurements with simulation results from a high-fidelity model, one can also check whether a high-fidelity model conforms to a simple model. We demonstrate the usefulness of reachset conformance by several use cases.
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