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Full-Text Articles in Engineering
Exercising Real Unit Operational Options Under Price Uncertainty, Chung-Li Tseng
Exercising Real Unit Operational Options Under Price Uncertainty, Chung-Li Tseng
Engineering Management and Systems Engineering Faculty Research & Creative Works
In this paper, we use the real options framework to value the operation flexibility of a power plant. The power plant operation is formulated as a multi-stage stochastic problem. We assume that there are hourly spot markets for both electricity and the fuel used by the generator, and that their prices follow some Ito processes. At each hour, the power plant operator must decide whether or not to run the unit so as to maximize expected profit. However, the unit operation is subject to decision lead times and minimum uptime and downtime constraints, so the commitment decision must take into …
Comparison Of A Heuristic Dynamic Programming And A Dual Heuristic Programming Based Adaptive Critics Neurocontroller For A Turbogenerator, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Ronald G. Harley
Comparison Of A Heuristic Dynamic Programming And A Dual Heuristic Programming Based Adaptive Critics Neurocontroller For A Turbogenerator, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents the design of a neurocontroller for a turbogenerator that augments/replaces the conventional automatic voltage regulator and the turbine governor. The neurocontroller uses a novel technique based on the adaptive critic designs with emphasis on heuristic dynamic programming (HDP) and dual heuristic programming (DHP). Results are presented to show that the DHP based neurocontroller is robust and performs better than the HDP based neurocontroller, as well as the conventional controller, especially when the system conditions and configuration changes.
Convergence Analysis Of Adaptive Critic Based Optimal Control, S. N. Balakrishnan, Xin Liu
Convergence Analysis Of Adaptive Critic Based Optimal Control, S. N. Balakrishnan, Xin Liu
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Adaptive critic based neural networks have been found to be powerful tools in solving various optimal control problems. The adaptive critic approach consists of two neural networks which output the control values and the Lagrangian multipliers associated with optimal control. These networks are trained successively and when the outputs of the two networks are mutually consistent and satisfy the differential constraints, the controller network output produces optimal control. In this paper, we analyze the mechanics of convergence of the network solutions. We establish the necessary conditions for the network solutions to converge and show that the converged solution is optimal.
Infinite Time Optimal Neuro Control For Distributed Parameter Systems, S. N. Balakrishnan, Radhakant Padhi
Infinite Time Optimal Neuro Control For Distributed Parameter Systems, S. N. Balakrishnan, Radhakant Padhi
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The conventional dynamic programming methodology for the solution of optimal control, despite having many desirable features, is severely restricted by its computational requirements. However, in recent times, an alternate formulation, known as the adaptive-critic synthesis, has given it a new perspective. In this paper, we have attempted to use the philosophy of adaptive-critic design to the optimal control of distributed parameter systems. An important contribution of this study is the derivation of the necessary conditions of optimality for distributed parameter systems, described in discrete domain, following the principle of approximate dynamic programming. Then the derived necessary conditions of optimality are …
Neurocontroller Alternatives For "Fuzzy" Ball-And-Beam Systems With Nonuniform Nonlinear Friction, Danil V. Prokhorov, Donald C. Wunsch, Paul H. Eaton
Neurocontroller Alternatives For "Fuzzy" Ball-And-Beam Systems With Nonuniform Nonlinear Friction, Danil V. Prokhorov, Donald C. Wunsch, Paul H. Eaton
Electrical and Computer Engineering Faculty Research & Creative Works
The ball-and-beam problem is a benchmark for testing control algorithms. Zadeh proposed (1994) a twist to the problem, which, he suggested, would require a fuzzy logic controller. This experiment uses a beam, partially covered with a sticky substance, increasing the difficulty of predicting the ball's motion. We complicated this problem even more by not using any information concerning the ball's velocity. Although it is common to use the first differences of the ball's consecutive positions as a measure of velocity and explicit input to the controller, we preferred to exploit recurrent neural networks, inputting only consecutive positions instead. We have …