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This paper studies off-line control and on-line control based on Adaptive Dynamical Programming and proposes an optimal adaptive algorithm with the combination of off-line and on-line training; The method using off-line value iteration algorithm gets off-line opitical controller, then using on-line policy iteration algorithm of Q learning improves the off-line opitical controller. Simulation results...
With the development of urbanization, the environmental quality of urban soil has been declining. Transport has become an important source of heavy metals in soil. To have a preliminary understanding of soil heavy metals pollution in the urban road, in this study, the contents of Cd, As, Pb, Zn, Cu, Ni and Cr in soil of urban road of Quanzhou City were analyzed and investigated to evaluate environmental...
This paper presents a novel real-time optimal neural controller which is based on improved Action-Depended Dual Heuristic Dynamic Programming (ADDHP) method, including its schematic diagram, the training algorithms and its implementation steps. This method requires neither an explicit model of the controlled plant nor the indispensable system performance index `J' which is explicitly defined in the...
The boiler combustion process of power plant is a typical process with the features of multi-input, multi-output, strong non-linearity, strong jamming and close coupling. The coupling relationship between its parameters correlated with combustion process is very anfractuous, so it is very hard to solve its optimal control problem with conventional control methods. And Adaptive Critic Designs (ACDs)...
Synchronous generator is a system which has a series of dynamic characteristics as non-linear, fast response and so on. It ensures the stability and security of the power grid and plays an important role. As a result, the effective control of the synchronous generator, it is particularly important. This paper provides a new type of adaptive neural controller, which is based on heuristic dynamic programming...
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