Balaje T. Thumati

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In this paper, a single and multi-layer neural network (NN) controllers are developed for a class of nonlinear discrete time systems. Under a mild assumption on the system uncertainties, which include unmodeled dynamics and bounded disturbances, by using novel weight update laws and a robust term, local asymptotic stability of the closed-loop system is(More)
The optimal control of linear systems accompanied by quadratic cost functions can be achieved by solving the well-known Riccati equation. However, the optimal control of nonlinear discrete-time systems is a much more challenging task that often requires solving the nonlinear Hamilton-Jacobi-Bellman (HJB) equation. In the recent literature, discrete-time(More)
In this paper, a novel, unified model-based fault-detection and prediction (FDP) scheme is developed for nonlinear multiple-input-multiple-output (MIMO) discrete-time systems. The proposed scheme addresses both state and output faults by considering separate time profiles. The faults, which could be incipient or abrupt, are modeled using input and output(More)
In this paper, a new multi-layer neural network (MNN) based system identification scheme in discrete-time is proposed for a general class of nonlinear discrete-time systems with guaranteed asymptotic convergence of the identification error. Then, a MNN based direct adaptive MNN controller design is introduced for a different class of nonlinear discrete-time(More)
Discrete time approximate dynamic programming (ADP) techniques have been widely used in the recent literature to determine the optimal or near optimal control policies for nonlinear systems. However, an inherent assumption of ADP requires at least partial knowledge of the system dynamics as well as the value of the controlled plant one step ahead. In this(More)
In this paper, a novel fault diagnostics and prediction (FDP) scheme is introduced by using artificial immune system (AIS) as an online approximator for a class of nonlinear discrete-time systems. Traditionally, AIS is considered as an offline tool for fault detection (FD). However, in this paper, AIS is utilized as an online approximator in discrete-time(More)
In this paper, a model based fault detection and isolation (FDI) scheme with online fault learning capabilities is proposed for HVAC systems. An observer comprising of an online approximator in discrete-time (OLAD) and a robust term is used for detection. A fault is detected if the generated detection residual, which is defined as the error between the(More)
As explained in the literature, it is very hard to measure premise variables of a Takagi-Sugeno (TS) fuzzy system. Therefore, in this paper, a fault detection and prediction (FDP) scheme is designed for a class of TS fuzzy systems with immeasurable (unknown) premise variables and external disturbances. A fault detection (FD) observer is designed to(More)