Based on a power-series approximation method, recurrent neural networks (RNN) are proposed for real-time synthesis and auto-tuning of feedback controllers for nonlinear output regulation systems. The proposed neurocontrol approach represents a novel application of recurrent neural networks to the nonlinear output regulation problem. The proposed approach completely inherits the stability and as...

In this study, a method of self-tuning single-input fuzzy logic controller (ST-SIFLC) is proposed to efficiently eliminate the chattering problem of perturbed time-delay systems with nonlinear input. This work has the tuning scheme derived from only two rules of fuzzy inference that result in an ultimate equation from defuzzification. This tuning algorithm is convenient and easy to utilize. The...

In this paper, a simple and effective scheme for tuning of fuzzy PI-PD controller based on fuzzy logic is proposed. Here the input scaling factors are tuned online by gain updating factors where values are determined by rule base with error and change in error as inputs according to the required controlled process. The performance comparison of conventional fuzzy logic controller, auto-tuned fu...

Purpose To present the results in the area of modern computer-aided control system design tools relating to system identification. Design/methodology/approach The finite-frequency identification method was designed for the needs of active identification. The test signal represents the sum of harmonics with automatically tuned (self-tuned) amplitudes and frequencies where the number of harmonics...

The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace ...

One approach to a recursive identification of continuous – time systems was implemented in self – tuning control of a system of interconnected tanks. Since derivatives of input and output variables of continuous – time systems can not be directly measured, differential filters and filtered variables are established to substitute primary variables. The filtered variables are then used in a recur...

The challenge of optimization control of batch processes is how to combine both discrete-time (batch-axis) information and continuous-time (time-axis) information into an integrated frame when designing optimal controller. By using data-driven technology, a novel integrated learning control system is proposed in this paper. Firstly, an iterative learning controller (ILC) is designed along the d...