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Found 12 papers, 0 papers with code
Mass Loss and Displacement Modeling for Multi-Axis Milling
During the cutting process, material of the workpiece is continuously being removed by the cutting tool, which results in a reduction of mass as well as a displacement in the center of the workpiece mass.
Vehicle Cabin Climate MPC Parameter Tuning Using Constrained Contextual Bayesian Optimization (C-CMES)
Model Predictive Controllers (MPCs) have shown promising results in achieving temperature tracking in vehicle cabins and may improve upon model-free control performance.
Automated Tuning of Nonlinear Kalman Filters for Optimal Trajectory Tracking Performance of AUVs
To enable a fair comparison, filter parameters are auto-tuned with Bayesian optimization (BO) for open and closed-loop performance, which is novel in AUV navigation.
Benchmark of Bayesian Optimization and Metaheuristics for Control Engineering Tuning Problems with Crash Constraints
Results indicate that deterministic noise, low multimodality, and substantial areas with infeasible parametrizations (crash constraints) characterize control engineering tuning problems.
Reduction and Observer Design for a Grey-Box Model in Continuous Pharmaceutical Manufacturing
It is shown that the ROM could reproduce the FOM states accurately with a relative mean square error below $0. 3\,\%$ for the experimental data simulation.
Joint Constrained Bayesian Optimization of Planning, Guidance, Control, and State Estimation of an Autonomous Underwater Vehicle
Our objective is to automatically tune these parameters with respect to arbitrary high-level control objectives within different operational scenarios.
Machine Learning Integrated with Model Predictive Control for Imitative Optimal Control of Compression Ignition Engines
One solution is the use of machine learning (ML) and model predictive control (MPC) to minimize emissions and fuel consumption, without adding substantial computational cost to the engine controller.
Deep Learning based Model Predictive Control for Compression Ignition Engines
Machine learning (ML) and a nonlinear model predictive controller (NMPC) are used in this paper to minimize the emissions and fuel consumption of a compression ignition engine.
Towards Real-Time Monitoring and Control of Water Networks
A reduced order model (ROM) with a 50 mm spatial resolution, i. e. 1200 discretization points, is constructed and utilized as the identification model for a single path of the test bench.
Model Order Reduction of The Time-Dependent Advection-Diffusion-Reaction Equation with Time-Varying Coefficients: Application to Real-Time Water Quality Monitoring
Optimality of the reduced order model regarding the reduction induced error is achieved by using an H2-norm reduction method.
Robust state and protection-level estimation within tightly coupled GNSS/INS navigation system
In autonomous applications for mobility and transport, a high-rate and highly accurate vehicle-state estimation is achieved by fusing measurements of global navigation satellite systems (GNSS) and inertial sensors.
Depth Camera Based Particle Filter for Robotic Osteotomy Navigation
Active surgical robots lack acceptance in clinical practice, because they do not offer the flexibility and usability required for a versatile usage: the systems require a large installation space or a complicated registration step, where the preoperative plan is aligned to the patient and transformed to the base frame of the robot.
