Consider a discrete-time nonlinear system with random disturbances appearing in the real plant and the output channel where the randomly perturbed output is measurable. An iterative procedure based on the linear quadratic Gaussian optimal control model is developed for solving the optimal control of this stochastic system. The optimal state estimate provided by Kalman filtering theory and the optimal control law obtained from the linear quadratic regulator problem are then integrated into the dynamic integrated system optimisation and parameter estimation algorithm. The iterative solutions of the optimal control problem for the model obtained converge to the solution of the original optimal control problem of the discrete-time nonlinear system, despite model-reality differences, when the convergence is achieved. An illustrative example is solved using the method proposed. The results obtained show the effectiveness of the algorithm proposed.
Electrochemical dechlorination of chlorobenzenes in the presence of various arene mediators such as naphthalene, biphenyl, phenanthrene, anthracene, and pyrene, was studied. The amount of mediator required was able to be reduced to 0.01 equiv. for all mediators except for anthracene, with the complete dechlorination of mono-, 1,3-di- and 1,2,4-trichlorobenzene still achieved. This catalytic amount of mediator plays an important role in accelerating the dechlorination through the rapid formation of radical anions prior to reduction of the chlorobenzenes.
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