Browse Topic: Computer simulation
Lane centering is a critical active safety feature whose effectiveness depends on robust design and validation across diverse driving conditions. This paper presents the development of a Lane Centering Controller (LCC) using a structured model-based design workflow in MATLAB and Simulink. A kinematic bicycle model was employed to simulate vehicle dynamics and evaluate an angle based steering controller integrating both feedforward and feedback control paths. The controller was tested across multiple road geometries and speeds up to 65 mph to ensure tracking consistency and stability under nominal and perturbed conditions. Perception noise models for lane curvature and curvature rate were extracted from onboard camera data under controlled conditions, revealing Gaussian characteristics. No filtering was applied, allowing direct evaluation of the controller’s inherent robustness to raw signal variability. The LCC maintained a peak lateral offset within ±0.35 m and lateral jerk within ±9
This paper builds on last year’s paper presenting DevOps automation in the context of model-based development. Following that paper, we interviewed Simulink users in passenger automotive, motorsports, commercial vehicles, aviation, rocketry, and industrial automation. We discovered that much of the benefit of DevOps platforms to reduce product development cycle time relies on their interactive features. We prototyped new tools to bridge interactive DevOps Git-based platforms with model-based development workflows, and then gathered reactions from another round of interviews. Here we present these interactive DevOps workflows with the feedback from these interviews to contextualize how engineering teams could adopt them to accelerate their own model-based workflows.
Ammonia is emerging as a promising energy vector for decarbonising the maritime sector. However, its low flame speed can lead to incomplete combustion, reduced engine efficiency, and increased emissions of unburned ammonia (NH3). Blending hydrogen with ammonia helps to address these issues, but the fundamental combustion characteristics of such mixtures remain insufficiently understood. This study examines the combustion dynamics of an NH3–H2 blend containing 30% hydrogen at 3 bar initial pressure. Experiments were performed in a 1.2 L optically accessible constant-volume combustion chamber fitted with a wall-mounted surface spark plug. High-speed shadowgraph imaging with 6,000 fps captured the flame evolution throughout the combustion process. The pressure and temperature values were monitored using piezoresistive pressure transducers and K-type thermocouples. Combustion times and flame extensions were extracted via post-processing of flame images using custom MATLAB algorithms. The
The exponentially growing complexity of engineering systems, such as robotic systems, autonomous vehicles, and unmanned aerial vehicles, require sophisticated control strategies that can efficiently coordinate system operation in various environments. The traditional control design approaches present significant challenges for control engineers to keep up with the increasing complexity and changing requirements. To advance embedded control system design, a paradigm shift from traditional development approaches toward more structured, systematic methodologies that can manage the multi-domain nature of control systems is critically needed. Model-based design approach is emerging as a solution for this demand. Model-based design approach uses a system model for control system development, from requirements capture to control system design, implementation, and testing. It provides an integrated environment for design, implementation, automatic code generation, and validation, which allows
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