@conference {
	title = {Robust H$\infty$ Output Feedback Control of Bilinear Systems},
	author = {Teolis, Carole A., Yuliar, S., James, Matthew R., Baras, John S.},
	year = {1994},
	month = {12/1994},
	abstract = {In this paper we present a solution to the robust Hoo output feedback control problem for bilinear systems over a finite time interval. The solution is obtained through the use of the information state method. We discuss the relation of the information state controller with the certainty equivalence controller under smoothness and uniqueness assumptions. Finally, numerical examples are provided to illustrate implementation issues of the information state feedback controller.},
	address = {Lake Buena Vista, Florida},
	booktitle = {The 33rd CDC Conference},
	pages = {pp. 1421-1426}
}
@conference {
	title = {Nonlinear H$\infty$ Control},
	author = {Baras, John S., James, Matthew R.},
	year = {1994},
	month = {12/1994},
	abstract = {This paper discusses various aspects of recent developments concerning the robust Hoo problem for continuous-time nonlinear systems. In the state feedback case, the problem can be solved in the framework of dissipative systems, and the associated storage functions solve the PDI in the viscosity sense. The main problem is then one of controller synthesis. In the output feedback case, the information state concept provides the appropriate framework. The solution is expressed in terms of a PDE for the information state (filter), and an infinite dimensional PDE or dissipation-type PDI for the value function (control). The attendant mathematical issues are discussed.},
	address = {Lake Buena Vista, Florida},
	booktitle = {The 33rd CDC Conference},
	pages = {pp. 1435-1438}
}
@conference {
	title = {Output Feedback Risk-Sensitive Control and Differential Games for Continuous-Time Nonlinear Systems},
	author = {James, Matthew R., Baras, John S., Elliott, Robert J.},
	year = {1993},
	month = {12/1993},
	abstract = {In this paper, we carry out a formal analysis of an output feedback risk-sensitive~stochastic control problem. Using large derivation limits this problem is related to a deterministic differential game. Both problems are solved using appropriate information states. The use of an information state~for the game problem is new and is the principal contribution of our work. Our results have important~implications for the nonlinear robust stabilization problem.},
	address = {San Antonio, Texas},
	booktitle = {The 1993 32nd  IEEE Conference on Decision and Control},
	pages = {pp. 3357-3360},
	organization = {Marriott rivercenter}
}
@conference {
	title = {Robust Output Feedback Control for Discrete-Time Nonlinear Systems:  The Finite Time Case},
	author = {Baras, John S., James, Matthew R.},
	year = {1993},
	month = {12/1993},
	abstract = {In this paper we present a new approach to the solution of the output feedback robust control problem. We employ the recently developed concept of information state for output feedback dynamic games and obtain necessary and sufficient conditions for the solution to the robust control problem expressed in terms of the information state. The resulting controller is an information state feedback controller~and is intrinsically infinite dimensional.},
	address = {San Antonio, Texas},
	booktitle = {The 1993 32nd  IEEE Conference on Decision and Control},
	pages = {pp. 51-55},
	organization = {Marriott rivercenter}
}
@conference {
	title = {Implementation of a Dynamic Game Controller for Partially Observed Discrete-Time Nonlinear Systems},
	author = {Teolis, Carole A., James, Matthew R., Baras, John S.},
	year = {1993},
	month = {12/1993},
	abstract = {In this paper we describe an implementation of a certainty equivalence controller for a discrete time partially observed dynamic game problem.},
	address = {San Antonio, Texas},
	booktitle = {The 1993 32nd  IEEE Conference on Decision and Control},
	pages = {pp. 2997-2998},
	organization = {Marriott rivercenter}
}
@conference {
	title = {Nonlinear Filtering Asymptotics, Large Deviations and Observers for Nonlinear Systems},
	author = {Baras, John S., James, Matthew R.},
	year = {1990},
	month = {04/1990},
	address = {Santa Barbara, CA},
	booktitle = {NSF-UC-NASA Workshop on Nonlinear Control},
	pages = {pp. 29-30},
	organization = {UCSB}
}
@conference {
	title = {Nonlinear Filtering Asymptotics, Large Deviations and Observers for Nonlinear Systems},
	author = {Baras, John S., James, Matthew R.},
	year = {1988},
	month = {11/1988},
	abstract = {We present a methodology for the construction of the dynamic observers for nonlinear systems. The basic methodology used is to construct these observers as limits of nonlinear filters when certain noise parameters tend to zero. We, therefore, make contact with some interesting results on large derivations~of filtered diffusion processes. Some examples illustrate the results. ~},
	address = {Osaka, Japan},
	booktitle = {20th ISCIE Symposium on Stochastic Systems Theory and its Applications},
	pages = {pp. 1-12}
}
@conference {
	title = {An Observer Design for Nonlinear Control Systems},
	author = {James, Matthew R., Baras, John S.},
	year = {1988},
	month = {06/1988},
	abstract = {We present an observer design for systems with controlled nonlinear dynamics and nonlinear observation. The design is a development of earlier work, which was motivated by nonlinear filtering asymptotics. The basic design requires that the initial conditions belong to a bounded region determined by the data and design parameters. However, for a certain class of systems, no such a priori knowledge is required. To illustrate the utility of our design, several examples are given.},
	address = {Antibes, France},
	booktitle = {The 8th International Conference on Analysis and Optimization of Systems},
	pages = {pp. 170-180},
	organization = {INRIA}
}
@conference {
	title = {Nonlinear Filtering and Large Deviations},
	author = {James, Matthew R., Baras, John S.},
	year = {1987},
	month = {12/1987},
	abstract = {We consider the nonlinear filtering problem dx~= f(x)dt + (~∈~)dw, dy = h(x)dt + (~∈~)^1/2 dv, and obtain lim ~∈~-\&gt;0 log q^t (x,t) = -W (x, t) for unnormalised conditional densities q{\textquoteright}(x, t) using PDE methods. Here, W(x,t) is the value function for a deterministic optimal control problem arising in Mortensen{\textquoteright}s deterministic estimation, and is the unique viscosity solution of a Hamilton-Jacobi-Bellman equation.},
	address = {Los Angeles, California},
	booktitle = {The 26th IEEE Conference on Decision and Control},
	pages = {pp. 1588-1589}
}
@article {
	title = {Dynamic Observers as Asymptotic Limits of Recursive Filters: Special Cases},
	author = {Baras, John S., Bensoussan, Alain., James, Matthew R.},
	year = {1988},
	month = {10/1988},
	abstract = {A method for constructing observers for dynamical systems as asymptotic limits of filters is described. The program is carried out in detail for linear systems, and in addition~an observer is obtained for a class of systems with nonlinear dynamics and linear observations. The method is motivated by some large deviation results of Hijab for certain conditional measures.},
	pages = {pp. 1147-1158},
	volume = {Vol. 48},
	number = {No.  5},
	journal = {SIAM Jounal on Applied Mathematics}
}
@article {
	title = {Robust and Risk-Sensitive Output Feedback Control for Finite State Machines and Hidden Markov Models},
	author = {Baras, John S., James, Matthew R.},
	year = {1997},
	month = {01/1997},
	abstract = {The 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.},
	pages = {pp. 371-374},
	volume = {Vol. 7},
	number = {No. 3},
	journal = {Journal of Mathematical Systems, Estimation, and Control}
}
@article {
	title = {Partially Observed Differential Games, Infinite Dimensional HJI Equations, and Nonlinear H$\infty$~Control},
	author = {James, Matthew R., Baras, John S.},
	year = {1996},
	month = {07/1996},
	abstract = {This paper presents new results for partially observed nonlinear differential games. Using the concept of information state, we solve this problem in terms of an infinite-dimensional partial differential equation, which turns out to be the Hamilton-Jacobi-Isaacs (HJI) equation for partially observed differential games. We give definitions of smooth and viscosity solutions and prove that the value function is a viscosity solution of the HJI equation. We prove a verification theorem, which implies that the optimal controls are separated in that they depend on the observations through the information state. This constitutes a separation principle for partially observed differential games. We also present some new results concerning the certainty equivalence principle under certain standard assumptions. Our results are applied to a nonlinear output feedback H$\infty$~ robust control problem.},
	pages = {pp.  1342-1364},
	volume = {Vol. 34},
	number = {No. 4},
	journal = {SIAM Journal on Control and Optimization}
}
@article {
	title = {Robust H$\infty$~Output Feedback Control for Nonlinear Systems},
	author = {James, Matthew R., Baras, John S.},
	year = {1995},
	month = {06/1995},
	abstract = {In this paper, we present a new approach to the solution of the output feedback robust H$\infty$~control problem. We employ the recently developed concept of information state for output feedback dynamic games and obtain necessary and sufficient conditions for the solution to the robust control problem expressed in terms of the information state. The resulting controller is an information state feedback controller and is intrinsically infinite dimensional. Stability results are obtained using the theory of dissipative systems, and indeed, our results are expressed in terms of dissipation inequalities.},
	pages = {pp. 1007-1017},
	volume = {Vol. 40},
	number = {No.  6},
	journal = {IEEE Transactions on Automatic Control.}
}
@article {
	title = {Risk-Sensitive Control and Dynamic Games for Partially Observed Discrete-Time Nonlinear Systems},
	author = {James, Matthew R., Baras, John S., Elliott, Robert J.},
	year = {1994},
	month = {04/1994},
	abstract = {In this paper, we solve a finite-horizon partially observed risk-sensitive stochastic optimal control problem for discrete-time nonlinear systems and obtain small noise and small risk limits. The small noise limit is interpreted as a deterministic partially observed dynamic game, and new insights into the optimal solution of such game problems are obtained. Both the risk-sensitive stochastic control problem and the deterministic dynamic game problem are solved using information states, dynamic programming, and associated separated policies. A certainty equivalence principle is also discussed. Our results have implications for the nonlinear robust stabilization problem. The small risk limit is a standard partially observed risk-neutral stochastic optimal control problem.},
	pages = {pp.  780-792},
	volume = {Vol. 39},
	number = {No. 9},
	journal = {IEEE Transactions on Automatic Control.}
}
@article {
	title = {Nonlinear Filtering and Large Deviations: A PDE-Control Theoretic Approach},
	author = {James, Matthew R., Baras, John S.},
	year = {1988},
	month = {01/1988},
	abstract = {We consider the nonlinear filtering problem dx = f(x)dt + √(є)dw, dy = h(x)dt + √(є)dv, and obtain lim[є{\textrightarrow}0] є log qє (x,t) = -W(x,t) for unnormalized conditional densities qє (x,t) using PDE methods. Here, W(x,t) is the value function for a deterministic optimal control problem arising in Mortensen{\textquoteright}s deterministic estimation and is the unique viscosity solution of a Hamilton-Jacobi-Bellman equation. Hijab has also studied this filtering problem, and we extend his large deviation result for certain unnormalized conditional measures. The resulting variational problem corresponds to the above control problem.},
	pages = {pp. 391-412},
	volume = {Vol. 23},
	journal = {Stochastics}
}
