Institute for Systems Research Technical Reports
Permanent URI for this collectionhttp://hdl.handle.net/1903/4376
This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.
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Item Comparison of Run-to-Run Control Methods in Semiconductor Manufacturing Processes(2000) Zhang, Chang; Deng, Hao; Baras, John S.; Baras, John S.; ISRRun-to Run (RtR) control plays an important role in semiconductor manufacturing.In this paper, RtR control methods are generalized. The set-valued RtR controllers with ellipsoidapproximation are compared with other RtR controllers bysimulation according to the following criteria: A good RtR controller should be able to compensate for variousdisturbances, such as process drifts, process shifts (step disturbance)and model errors; moreover, it should beable to deal with limitations, bounds, cost requirement, multipletargets and time delays that are often encountered in realprocesses.
Preliminary results show the good performance of the set-valued RtRcontroller. Furthermore, this paper shows that it is insufficient to uselinear models to approximate nonlinear processes and it is necessary to developnonlinear model based RtR controllers.
Item The Set-Valued Run-to-Run Controller with Ellipsoid Approximation(2000) Zhang, Chang; Baras, John S.; Baras, John S.; ISRIn order to successfully apply Run-to-Run (RtR) control or real time control ina semiconductor process, it is very important to estimate the processmodel. Traditional semiconductor process control methods neglect theimportance of robustness due to the estimation methods they use.A new approach, namely the set-valued RtR controller with ellipsoidapproximation, is proposed to estimate the process model from acompletely different point of view. Because the set-valued RtRcontroller identifies the process model in the feasible parameter setwhich is insensitive to noises, the controller is robust to theenvironment noises.Ellipsoid approximation can significantly reduce the computation load for the set-valued method.
In this paper, the Modified Optimal Volume Ellipsoid (MOVE) algorithm is used toestimate the process model in each run. Designof the corresponding controller and parameter selection of the controller are introduced.Simulation results showed that the controller is robust toenvironment noises and model errors.
Item Robust H∞ Output Feedback Control of Bilinear Systems(1996) Teolis, C.A.; Yuliar, S.; James, Matthew R.; Baras, John S.; ISRThe study of robust nonlinear control has attracted increasing interest over the last few years. Progress has been aided by the recent entension [FM91, Jam92] of the linear quadratic results [Jac73, Whi81] linking the theories of L2 gain control (nonlinear H∞ control), different games, and the stochastic risk sensitive control. Most of the previous research conducted in the area of robust nonlinear control has focused on the case where full state information is available. Thus, previously little attention has been given to the problem of robust nonlinear control via output feedback. In this paper we address the problem of robust H∞ output feedback control for the special case of bilinear systems.Item A Framework for Robust Run by Run Control with Lot Delayed Measurement(1995) Baras, John S.; Patel, N.S.; ISRThis paper considers the run by run control problem. We develop a framework to solve the problem in a robust fashion. The framework also encompasses the case where the system is subject to delayed measurements. Recent results available for the control of such systems are reviewed, and two simple examples are presented. The first example is based on the end-pointing problem for a deposition process, and is subject to noise which has both Gaussian and uniform components. The second one is concerned with rate control in a LPCVD reactor.Item Nonlinear HControl with Delayed Measurements(1995) Baras, John S.; Patel, N.S.; ISRThis paper considers the nonlinear Hcontrol problem for systems subject to delayed measurements. Necessary and sufficient conditions for the solvability of the problem are presented. We employ the concept of an information state to achieve separation between estimation and control. In particular, the information state derived is no longer the ﲷorst case cost to come function. We also briefly discuss certainty equivalence for systems with delayed measurements.Item Reduced Complexity Output Feedback Nonlinear HControllers and Relation to Certainty Equivalence(1995) Baras, John S.; Patel, N.S.; ISRIn this paper, we consider the problem of constructing reduced complexity controllers for output feedback nonlinear Hcontrol. We give sufficient conditions, under which the controllers so obtained, guarantee asymptotic stability of the closed-loop system when there are no exogenous inputs. The controllers obtained are non-optimal in general. However, in case optimality holds, we show that these controllers are in fact the certainty equivalence controllers.Item Robust Control of Set-Valued Discrete Time Dynamical Systems(1994) Baras, John S.; Patel, N.S.; ISRThis paper presents results obtained for the robust control of discrete time dynamical systems. The problem is formulated and solved using dynamic programming. Both necessary and sufficient conditions in terms of (stationary ) dynamic programming equalities are presented. The output feedback problem is solved using the concept of an information state, where a decoupling between estimation and control is obtained.Item Information State for Robust Control of Set-Valued Discrete Time Systems(1994) Baras, John S.; Patel, N.S.; ISRIn this paper, we construct the information state for robust output feedback control of set-valued discrete time dynamical systems. The information state is obtained as the small noise limit of an appropriate risk-sensitive stochastic control problem. It is possible to obtain this limit by an extension of the Vardgan-Laplace lemma. Finally, the relationship between the information state, and the indicator function of feasible sets is examined.Item A Computational Method for Hontroller Design in the Frequency Domain(1994) Frankpitt, Bernard A.; Berenstein, Carlos A.; Baras, John S.; ISRA new approach to frequency domain design of robust controllers for distributed parameter systems is presented. The central idea is to use techniques that were developed for the solution of the Corona Problem, for the solution of both the Bezout equation and an auxiliary equation that arises form the Nehari interpolation problem. An algebraic reformulation of these equations allows the solution to be computed from the solution of an inhomogeneous Cauchy Riemann equation with a Carleson measure as the inhomogeneous term. The theory is applied to a single input single output system with delay to yield the transfer function of a stabilizing controller with guaranteed Hstability margin. Finally the framework is extended to handle multi-input multi- output systemsItem Robust and Risk-Sensitive Output Feedback Control for Finite State Machines and Hidden Markov Models(1994) Baras, John S.; James, Matthew R.; ISRThe purpose of this paper is to develop a framework for designing controllers for finite state systems which are robust with respect to uncertainties. A deterministic model for uncertainties is introduced, leading to a dynamic game formulation of the robust control problem. This problem is solved using an appropriate information state. A risk-sensitive stochastic control problem is formulated and solved for Hidden Markov Models, corresponding to situations where the model for the uncertainties is stochastic. The two problems are related using small noise limits.