UB - University at Buffalo, The State University of New York UB Mechanical and Aerospace Engineering
Dynamics, Control, and Mechatronics image

Dynamics, Control, and Mechatronics

Faculty

Affiliated Faculty

  • Liang, Z.

Laboratories

Research Summaries

Data Assimilation for Plume Forecasting
The objective of this project is the systematic study and elucidation of the basic physico-mathematical principles underlying data assimilation in the context of dispersion of material in the air in the form of plumes. Sparse spatio-temporal sensing mandates development of new technique for the integration uncertain sensor data with the model output. This problem is mathematically characterized by high dimensionality, profoundly nonlinear models, and uncertainties with non-Gaussian non-stationary distributions. The physical dispersion models involve a balance of numerous natural forces acting in the complex atmospheric medium and are propagated with meteorological data which is itself uncertain.
T. SINGH, P. Singla.
Robust Control of Uncertain Systems
Modeling uncertainties which are present in any system representation have tempered the performance of controllers designed to meet stringent specifications. These uncertainties include errors in model parameters and unmodeled dynamics. The effect of parametric uncertainties is accentuated when the controllers are required to switch between their limits as in time-optimal and fuel/time optimal controllers. This work focuses on developing techniques to design robust controllers. Techniques to map the uncertain parameters to the performance space are used to design controllers which are not conservative.
T. SINGH.
Modeling and Control of Glucose in Type 1 Diabetic Subjects
Type 1 diabetes, also known as juvenile diabetes is a chronic disease and need careful and constant monitoring to prevent the subject from hyperglycemia and hypoglycemia. Diurnal variations of the glucose-insulin dynamics and the change in model as a function of the level of activity of the subject, makes the design of high performance controllers a challenging task. This research focuses on the modeling and control aspects which accounts for intra and inter subject variability.
T. SINGH.
Controller design for Non-minimum Phase systems
Input-Shaping/Time-delay filtering has proven to be a powerful approach for shaping reference input to vibratory system for precise point-to-point motion control. These techniques only account for the system poles. This research focuses on exploiting knowledge of the system zeros to design pre-filters which are robust to modeling uncertainties. The unstable or non-minimum phase zeros pose a particular challenge in the design and novel technique to account for non-minimum phase zeros is the focus of this work.
T. SINGH.
Simultaneous Feedback / Feed-Forward Control Design
Extensive work has been carried out related to the design of feedback controllers for vibrations attenuation of maneuvering systems. Over the past 10 years a large body of literature has also evolved related to the pre-filtering of reference input for vibration attenuation. These two design techniques have evolved independent of each other. This work focuses on the integration of the design of the feedback and the feed-forward controllers.
T. SINGH.
Image-Guided Tracking of Internal Organ and Tumor Motion
This research work deals with the development of safe and effective Adaptive Conformal Radiation Therapy for cancer treatment while minimizing the relapse rate of tumor and side effects of the lethal radiation dose. The main objective of this research work is to design and test a novel framework for accurate estimation of 7-D (position + orientation) tumor target dynamics based on the correlation of real-time imagery data from external and internal fiducial markers. The core tool at the heart of our approach is recently developed adaptive multi-resolution system identification algorithm, which makes use of recent advances in Neural Networks, Finite Element Methods and Nonlinear Adaptive Control. An important aspect of our work is to adapt respiratory models in real-time which helps us in addressing many critical issues specific to image-guided radiation therapy such as distinguishing between patient movement and respiratory motion, signal deficiencies, time latency, frequency of the measurement data and uncertainty in the breathing models currently in use.
P. SINGLA, T. SINGH.

 

  • UB MAE Research

    Research Spotlight

    MAE researchers have developed advanced computational techniques for Fire Simulation and multi-phase reacting turbulent flows.

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    UB MAE researchers in computational mechanics have developed a high fidelity volcanic landslide simulator to aid geologists in mapping the hazard areas at locations such as the island of Montserrat.

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    A Level Set Embedded Interface Method has been developed at Compuational Fluid Dynamics Laboratory to simulate Conjugate heat transfer for irregular geometries

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    MAE's Laser Flow Diagnostic Laboratory is a leader holographic particle image velocimetry, a three-dimensional, next generation flow diagnostics tool.

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    MAE's Automation, Robotics, and Mechatronics Laboratory is conducting research both on the theoretical formulation and experimental validation of such novel mechatronic systems as multi-robot collaboration.

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    The nonlinear estimation group is developing techniques for propagating uncertainties through nonlinear dynamical systems for better forecasting and output uncertainty characterization.

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    Study of Non-premixed flame-wall interaction using vortex ring configuration is done for the first time at the Computational Fluid Dynamics Laboratory.

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