This paper presents a methodology which considers an interpolation between Linear Parameter-Varying (LPV) controllers that were designed separately for different objectives. The quadratic stability of the closed-loop system is proved under arbitrary in terms set Matrix Inequalities (LMIs). strategy based on Youla–Kucera (YK) parameterization. proposed method can help multi-variable and multi-ob...

Different aspects of modeling faults in dynamic systems are considered in connection with reliable control (RC). The fault models include models with additive faults, multiplicative faults and structural changes in the models due to faults in the systems. These descriptions are considered in connection with reliable control and feedback control with fault rejection. The main emphasis is on faul...

This paper explores the benefits of transforming spectral peaks in voice conversion. First, in examining classic GMMbased transformation with cepstral coefficients, we show that the lack of transformed data variance ("over-smoothing") can be related to the choice of spectral parameterization. Consequently, we propose an alternative parameterization using spectral peaks. The peaks are transforme...

The task of inducing, via continuous static state-feedback control, an asymptotically stable heteroclinic orbit in a nonlinear control system is considered this paper. main motivation comes from the problem ensuring convergence to so-called point-to-point maneuver underactuated mechanical system. Namely, smooth curve its state--control space, which consistent with dynamics and connects two (lin...

Many control problems take place in continuous state-action spaces, e.g., as in manipulator robotics, where the control objective is often defined as finding a desired trajectory that reaches a particular goal state. While reinforcement learning offers a theoretical framework to learn such control policies from scratch, its applicability to higher dimensional continuous state-action spaces rema...

In this paper we present a direct method for the numerical solution of the constrained optimal control problem when the gradient information is not available. At this aim, a new control parameterization based on Bernstein basis functions is suggested to convert control problem into nonlinear programing problem (NLP), and then a recently proposed stochastic algorithm called Probabilistic Global ...