A hybrid method for the optimal linear control of nonlinear systems
Hybird method for optimal linear control of nonlinear systems
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Hybird method for optimal linear control of nonlinear systems
A recursive estimator, the ridge filter, was developed for the linear discrete dynamic estimation problem. Theorems were established to show that the ridge filter can be, on the average, closer to the expected value of the system state than the Kalman filter. On the other hand, Kalman filter, on the average, is closer to the instantaneous system state than the ridge filter. The ridge filter has been formulated in such a way that the computational features of the Kalman filter are preserved.
When tracking control systems are used in repetitive operations such as robots in various manufacturing processes, the controller will make the same errors repeatedly. Here consideration is given to learning controllers that look at the tracking errors in each repetition of the process and adjust the control to decrease these errors in the next repetition. A general formalism is developed for learning control of discrete-time (time-varying or time-invariant) linear multivariable systems. Methods of specifying a desired trajectory (such that the trajectory can actually be performed by the discrete system) are discussed, and learning controllers are developed. Stability criteria are obtained which are relatively easy to use to insure convergence of the learning process, and proper gain settings are discussed in light of measurement noise and system uncertainties.
A linear shift-invariant image preprocessing technique is examined which requires no specific knowledge of any parameter of the original image and which is sufficiently general to allow the effective radius of the composite imaging system to be arbitrarily shaped and reduced, subject primarily to the noise power constraint. In addition, the size of the point-spread function of the preprocessing filter can be arbitrarily controlled, thus minimizing truncation errors.
In this paper, a necessary and sufficient condition for the existence of a proportional semistate feedback is established such that the closed loop system is regular and of index at most two. The condition is characterized by a rank condition that involves only the original system coefficient matrices. Also, a new rank condition ensuring that a given linear time-invariant descriptor system is regular and of index at most some specific value is also derived. The developed theory is illustrated through physical and numerical examples.
Purpose: To reduce internal target volume (ITV), respiratory management is a must in imaging and treatment for lung, liver, and breast cancers. We investigated the dosimetric accuracy of VMAT treatment delivery with a Response™ gating system linked to linear accelerator. Methods: The Response™ gating module designed to directly control radiation beam by breath-holding with a ABC system (Elekta AB, Stockholm, Sweden) was tested for VMAT treatments. Seven VMAT plans including three conventional and four stereotactic body radiotherapy (SBRT) cases were evaluated. Each plan was composed of two or four arcs of 6MV radiation beam with prescribed dose ranged from 1.8 to 9 Gy per fraction. Each plan was delivered continuously without gating and delivered with multiple interruptions by the ResponseTM gating module with a 20 or 30 second breath-holding period. MapCheck2 and Gafchromic EBT3 films sandwiched in MapPHAN were used to measure the delivered dose with and without gating. Films were scanned on a flatbed color scanner, and red channel was extracted for film dosimetry. Gamma analysis was performed to analyze the dosimetrical accuracy of the radiation delivery with gating. Results: The measured doses with gating remarkably agree with the planned dose distributions in the results of gamma index passing rate (within 20% isodose; >98% for 3%/3mm and >92% for 2%/2mm in MapCheck2, and >91% for 3%/3mm criteria in EBT3 film except one case which was for large target and highly modulated). No significant difference (student t-test: p-value < 0.0005) was shown between the doses delivered with and without gating. There was no indication of radiation gap or overlapping during deliver interruption in film dosimetry. Conclusion: The Response™ gating system can be safely used during VMAT treatment. The accurate performance of the gating system linked to ABC can contribute to ITV reduction for SBRT using VMAT.
This work derives a residual-based a posteriori error estimator for reduced models learned with non-intrusive model reduction from data of high-dimensional systems governed by linear parabolic partial differential equations with control inputs. It is shown that quantities that are necessary for the error estimator can be either obtained exactly as the solutions of least-squares problems in a non-intrusive way from data such as initial conditions, control inputs, and high-dimensional solution trajectories or bounded in a probabilistic sense. Here, the computational procedure follows an offline/online decomposition. In the offline (training) phase, the high-dimensional system is judiciously solved in a black-box fashion to generate data and to set up the error estimator. In the online phase, the estimator is used to bound the error of the reduced-model predictions for new initial conditions and new control inputs without recourse to the high-dimensional system. Numerical results demonstrate the workflow of the proposed approach from data to reduced models to certified predictions.
A compact, fiber-coupled, six degree-of-freedom measurement system which enables fast, accurate calibration, and error mapping of precision linear stages is presented. The novel design has the advantages of simplicity, compactness, and relatively low cost. This proposed sensor can simultaneously measure displacement, two straightness errors, and changes in pitch, yaw, and roll using a single optical beam traveling between the measurement system and a small target. The optical configuration of the system and the working principle for all degrees-of-freedom are presented along with the influence and compensation of crosstalk motions in roll and straightness measurements. Several comparison experiments are conducted to investigate the feasibility and performance of the proposed system in each degree-of-freedom independently. Comparison experiments to a commercial interferometer demonstrate error standard deviations of 0.33 μm in straightness, 0.14 μrad in pitch, 0.44 μradin yaw, and 45.8 μrad in roll.
Optimal bounded control of linear sample-data systems in terms of control matrices and regions of application
Optimal linear estimation and control theory application to high precision optical spacecraft tracking systems design
Electropneumatic linear actuator for thrust vector control on J- 2 rocket engine
A classification of all the compensators that stabilize a given general plant in a linear, time-invariant multi-input, multi-output feedback system is developed. This classification, along with the associated necessary and sufficient conditions for stability of the feedback system, is achieved through the introduction of a new parameterization, referred to as R-Parameterization, which is a dual of the familiar Q-Parameterization. The classification is made to the stability conditions of the compensators and the plant by themselves; and necessary and sufficient conditions are based on the stability of Q and R themselves.
Algorithm for reducing linear time-invariant differential systems to state form applied to systems described by transfer functions
The well-known stabilizing property of linear quadratic state feedback design is utilized to evaluate the robustness of a linear quadratic feedback design in the presence of modeling errors. Two general conditions are obtained for allowable modeling errors such that the resulting closed-loop system remains stable. One of these conditions is applied to obtain two more particular conditions which are readily applicable to practical situations where a designer has information on the bounds of modeling errors. Relations are established between the allowable parameter uncertainty and the weighting matrices of the quadratic performance index, thereby enabling the designer to select appropriate weighting matrices to attain a robust feedback design.
Linear Algebra is essential for numerous aerospace problems of interest. Formal reasoning about hybrid systems that contain variables modeled by differential equations rely on concepts from Linear Algebra such as eigenvalues, matrix decompositions, and matrix valued functions. For example, the long-term dynamics of a system of differential equations depend on the stability/instability of its equilibrium points, which often reduces to an eigenvalue problem. This talk will embark on a quest to formalize theorems and results about eigenvalues and eigenvectors using PVS. We shall start our journey with 2 x 2 complex matrices, where we will apply our PVS code to a simple example of a dynamical system. Since it can be difficult or impossible to give simple expressions of eigenvalues for larger matrices (i.e. 5 x 5 or higher), we then move towards specifying the power method for verified computation of eigenvalue approximations in PVS. This effort requires development of multivariate complex arithmetic. At the end of the day, having such additions to the PVS NASA libraries will help move towards the use of formal methods to verify concepts of control theory and system level verification.
Purpose: Develop and benchmark an inverse treatment planning system (TPS) for proton radiotherapy integrating fast analytical dose and LET calculations in patient geometries and a dual objective function with both dose and LET components, enabling us to apply optimization techniques to improve the predicted outcome of treatments based on radiobiological models. Methods: The software package was developed in MATLAB and implements a fluence-dose calculation technique based on a pencil beam model for dose calculations and a 3D LET model based on the extension of the LET in the radial direction as a function of the predicted radiological pathway. Both models were benchmarked against commissioning data from our institution, dose calculations performed with a commercial treatment planning system and Monte Carlo simulations. The optimization is based on the adaptive simulated annealing approach . Results: The dose and LET calculations were tested in a water phantom and several real patient treatments. The pass rate for the gamma index analysis (3%/3mm) test was above 90% for all test cases analyzed, and the calculation time was of the order of seconds. The inverse planning module produced plans with a significantly higher mean LET in the target compared to traditional plans, without any loss of target coverage. The clinical relevance of this improvement is under consideration . Conclusion: The developed treatment planning system is a valuable clinical and research tool that enables us to incorporate LET effects into proton radiotherapy planning in a streamlined fashion.
We present a goal-oriented framework for constructing digital twins with the following properties: (1) they employ discretizations of high-fidelity partial differential equation (PDE) models governed by autonomous dynamical systems, leading to large-scale forward problems; (2) they solve a linear inverse problem to assimilate observational data to infer uncertain model components followed by a forward prediction of the evolving dynamics; and (3) the entire end-to-end, data-to-inference-to-prediction computation is carried out without approximation and in real time through a Bayesian framework that rigorously accounts for uncertainties. Several challenges must be overcome to realize this framework, including the large scale of the forward problem, the high dimensionality of the parameter space, and for a class of problems including those we target, the slow decay of the singular values of the parameter-to-observable map. Here we introduce a methodology to overcome these challenges by exploiting the autonomous structure of the forward model to decompose the solution of the inverse problem into a one-time-only offline phase in which the PDE model is solved a limited number of times (equal to the number of sensors), and an online phase that maps well onto GPUs and computes the parameter inference and prediction of quantities of interest in real time, given observational data. Our ultimate goal is to apply this framework to construct digital twins for subduction zones, including Cascadia, to provide early warning for tsunamis generated by megathrust earthquakes. To this end, we demonstrate how our methodology can be used to employ seafloor pressure observations, along with the coupled acoustic–gravity wave equations, to infer the earthquake-induced spatiotemporal seafloor motion (discretized with $\mathscr{O}$ (10 9 ) parameters) and forward predict the tsunami propagation. We present results of an end-to-end inference, prediction, and uncertainty quantification for a representative test problem with $\mathscr{O}$ (10 8 ) inversion parameters for which goal-oriented Bayesian inference is accomplished exactly and in real time, that is, in a matter of seconds.
Abstract. While most physics involved in wind energy are nonlinear, linearization of the underlying nonlinear wind system equations is often important for understanding the system response and exploiting well-established methods and tools for analyzing linear systems. Linearized models are important for eigenanalysis (to derive structural natural frequencies, damping ratios, and mode shapes), controls design (based on linear state-space models), etc. In controls co-design, wherein methods often rely on linearized time-domain models of the physics, the physical structure (often called the plant) and controller are designed and optimized concurrently, so it is important to understand how changes to the physical design affect the linearized system. This work summarizes efforts done to understand the impact of design parameter variations in the physical system (e.g., mass, stiffness, geometry, and aerodynamic and hydrodynamic coefficients) on the linearized system using OpenFAST.