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Abstract: This paper presents an effective method for robustness analysis and synthesis of a multi-PID controller for non-linear systems where desirable robustness and performance properties must be maintained across a large range of operating conditions. The robustness analysis problem is solved using an uncertain multimodel of the original non-linear system. The model of uncertainties used is an interval matrix modeled by a stochastic matrix which gives poor conservatism in the analysis of stability robustness. Moreover, the robust stability margin is interpreted as a smallest interval matrix that causes instability. This stability margin is evaluated using a random search algorithm. Simulation studies are used to demonstrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: This paper discusses universal learning network (ULN) and its application to control a class of nonlinear systems with long time delay. Two control architectures, model predictive control based on ULN model and single neuron PID (SN-PID) controller based on ULN predictor, are designed to control pH neutralization process, respectively. In addition, to verify the performance of ULN, two comparisons are also made. One is the generalization ability between ULN and back-propagation (BP) network, the other comparison is ULN predictor and Smith predictor, in which the same controller is used. Simulation results prove the applicability and effectiveness of the ULN model. The special architecture and its learning algorithm give ULN more representing abilities to model and control complicated nonlinear systems with long time delay. [Copyright &y& Elsevier]