Iterative control has been widely studied in recent years as an efficient methodology for the design of highly-performing controllers of complex plants. The idea behind iterative design is that, when the plant is exceedingly complex, the design of the controller in one shot is hazardous. Instead, one can perform a sequence of closedloop identification and controller design steps, aiming at prog...

In this manuscript, a new method is proposed to provide a perfect tracking of the supercavitation system based on a new two-state model. The tracking of the pitch rate and angle of attack for fin and cavitator input is of the aim. The pitch rate of the supercavitation with respect to fin angle is found as a non-minimum phase behavior. This effect reduces the speed of command pitch rate. Control...

This paper introduces the research on possibility of global optimization elements and ε-insensitive learning techniques integration in aim of fuzzy if-then rules extraction quality increase. The new learning algorithm of neuro-fuzzy system with parameterized consequents is introduced. It consists in integration of deterministic annealing and ε iterative quadratic programming method. The propose...

One of the most important issues in control system design is to obtain an accurate model of the plant to be controlled. Though most of the existing identification methods are described in discrete-time, it would be more appropriate to have continuous-time models directly from the sampled I/O data. From this viewpoint, the authors have developed such a direct identification method based on ILC (...

This note deals with the problem of designing an iterative learning control for uncertain systems. Given a linear time-invariant plant with multiplicative perturbations, a suucient condition for the convergence of the learning process for all the plant uncertainty is derived. Based on the obtained suucient condition, we show that the iterative learning control design can be reformulated as the ...