Robust controllers that stabilize dynamical systems even under disturbances and noise are often formulated as solutions of nonsmooth, nonconvex optimization problems. While methods such gradient sampling can handle the nonconvexity nonsmoothness, costs evaluating objective function may be substantial, making robust control challenging for with high-dimensional state spaces. In this work, we int...

In this study, a control strategy is presented for multiple quadrotors, inclusive of sliding mode and proportional derivative (PD) control, with the goal providing stability, robustness, reduced disturbance, formation tracking in uncertain conditions environments. The technique based on Newton-Euler equations satisfying Lyapunov’s stability conditions, using controller design PD design. designe...

A large number of problems in manufacturing processes, production planning, finance and engineering design require an understanding of potential sources of variations and quantification of the effect of variations on product behavior and performance. Traditionally, in engineering problems uncertainties have been formulated only through coarse safety factors. Such methods often lead to overdesig...

This paper deals with the modeling, analysis, design and simulation of a robust control method for a permanent magnet synchronous machine (PMSM) supplied with a PWM inverter based on a LPV (Linear Parameter Variation)  standard controller. Under the influence of uncertainties and external disturbances, by a variation of ±150% of motor parameters from the nominal values, the robust performance c...

Abstract Making design decisions is characterized by a high degree of uncertainty, especially in the early phase product development process, when little information known, while made have an impact on entire life cycle. Therefore, goal complexity management to reduce uncertainty order minimize or avoid need for changes late use phase. With our approach we model uncertainties with probabilistic...

TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed netw...