26 citations · 82 across the 15 of their papers we have counts for
18 papers
Stable state and signal estimation in a network context
Robert R. Bitmead
Power grid, communications, computer and product reticulation networks are frequently layered or subdivided by design. The layering divides responsibilities and can be driven by op…
State estimation for control: an approach for output-feedback stochastic MPC
Mohammad S. Ramadan, Robert R. Bitmead, Ke Huang
The paper provides a new approach to the determination of a single state value for stochastic output feedback problems using paradigms from Model Predictive Control, particularly t…
Control-orientation, conservation of mass and model-based control of compressible fluid networks
Sven Brüggemann, Robert H. Moroto, Robert R. Bitmead
We study a gas network flow regulation control problem showing the closed-loop consequences of using interconnected component models, which have been designed to preserve a variant…
A Compendium of Control-Oriented Models of Gas Processing Equipment Components
Sven Brüggemann, Robert H. Moroto, Robert R. Bitmead
This work provides linear control-oriented state space models of gas flow through standard equipment, such as valves, compressors, manifolds and non-trivial pipe geometries. After…
Control-Oriented Modeling of Pipe Flow in Gas Processing Facilities
Sven Brüggemann, Robert H. Moroto, Robert R. Bitmead
Pipe flow models are developed with a focus on their eventual use for feedback control design at the process control level, as opposed to the unit level, in gas processing faciliti…
Control-Oriented Modeling of Pipe Flow through Intersecting Pipe Geometries
Sven Brüggemann, Robert R. Bitmead
We present control-oriented models for transient dynamics of isothermal one-dimensional gas flow through multiple pipes in series and intersecting pipe geometries. These composite…
Maximum Likelihood Recursive State Estimation using the Expectation Maximization Algorithm
Mohammad S. Ramadan, Robert R. Bitmead
A Maximum Likelihood recursive state estimator is derived for non-linear and non-Gaussian state-space models. The estimator combines a particle filter to generate the conditional d…
Simultaneous input & state estimation, singular filtering and stability
Mohammad Ali Abooshahab, Mohammed M. J. Alyaseen, Robert R. Bitmead +1
Input estimation is a signal processing technique associated with deconvolution of measured signals after filtering through a known dynamic system. Kitanidis and others extended th…
LQG Control Performance with Low Bitrate Periodic Coding
Behrooz Amini, Robert R. Bitmead
Specific low-bitrate coding strategies are examined through their effect on LQ control performance. By limiting the subject to these methods, we are able to identify principles und…
Forward-looking persistent excitation in model predictive control
Sven Brüggemann, Robert R. Bitmead
This work deals with the problem of simultaneous regulation and model parameter estimation in adaptive model predictive control. We propose an adaptive model predictive control and…
Exponential convergence of recursive least squares with forgetting factor for multiple-output systems
Sven Brüggemann, Robert R. Bitmead
We extend results of the recursive-least-squares-with-forgetting-factor identifier for single-input-single-output systems to the multiple-output case by, under the assumption of pe…
Stochastic Model Predictive Control: Output-Feedback, Duality and Guaranteed Performance
Martin A Sehr, Robert R Bitmead
A new formulation of Stochastic Model Predictive Output Feedback Control is presented and analyzed as a translation of Stochastic Optimal Output Feedback Control into a receding ho…
Performance of Model Predictive Control of POMDPs
Martin A. Sehr, Robert R. Bitmead
We revisit closed-loop performance guarantees for Model Predictive Control in the deterministic and stochastic cases, which extend to novel performance results applicable to recedi…
Tractable Dual Optimal Stochastic Model Predictive Control: An Example in Healthcare
Martin A. Sehr, Robert R. Bitmead
Output-Feedback Stochastic Model Predictive Control based on Stochastic Optimal Control for nonlinear systems is computationally intractable because of the need to solve a Finite H…
Quantized Innovations Bayesian Filtering
Chun-Chia Huang, Robert R. Bitmead
The paper provides simple formulas of Bayesian filtering for the exact recursive computation of state conditional probability density functions given quantized innovations signal m…
Subspace Identification with Multiple Data Records: unlocking the archive
Chad M. Holcomb, Robert R. Bitmead
We develop an approach to subspace system identification using multiple data records and present a simple rank-based test for the adequacy of these data for fitting the unique line…
Particle Model Predictive Control: Tractable Stochastic Nonlinear Output-Feedback MPC
Martin A. Sehr, Robert R. Bitmead
We combine conditional state density construction with an extension of the Scenario Approach for stochastic Model Predictive Control to nonlinear systems to yield a novel particle-…
Sequential Detection with Mutual Information Stopping Cost
Vikram Krishnamurthy, Robert Bitmead, Michel Gevers +1
This paper formulates and solves a sequential detection problem that involves the mutual information (stochastic observability) of a Gaussian process observed in noise with missing…