In the present paper, an approach is proposed for structural topology optimization based on combination of Radial Basis Function (RBF) Level Set Method (LSM) with Isogeometric Analysis (IGA). The corresponding combined algorithm is detailed. First, in this approach, the discrete problem is formulated in Isogeometric Analysis framework. The objective function based on compliance of particular lo...

We consider the problem of asymptotic reconstruction of the state and parameter values for dynamical systems that cannot be transformed into the canonical adaptive observer form. A solution to this problem is proposed for a class of systems for which the unknowns are allowed to be nonlinearly parameterized functions of state and time. Going beyond asymptotic Lyapunov stability, we provide for t...

We consider the problem of asymptotic reconstruction of the state and parameter values for dynamical systems that cannot be transformed into the canonical adaptive observer form. A solution to this problem is proposed for a class of systems for which the unknowns are allowed to be nonlinearly parameterized functions of state and time. Going beyond asymptotic Lyapunov stability, we provide for t...

In this paper, an adaptive observer for multivariable nonlinear systems that present an unknown general state equation and known linear output equation is developed. The observer is based on linearly parameterized neural networks and Lyapunov methods are used for stability analysis. We consider a more general class of systems than in previous works and the usual SPR (strictly positive real) ass...

The construction of an input-to-state stability (ISS) Lyapunov function for networks of ISS system will be presented. First we construct ISS Lyapunov functions for each strongly connected component, then what remains is a cascade (or disconnected aggregation) of these strongly connected components. Using known results the constructed Lyapunov functions can be aggregated to one single ISS Lyapun...

This paper presents an adaptive tracking control method for a class of nonlinearly parameterized MIMO dynamic systems with time-varying delay and unknown nonlinear dead-zone inputs. A new high dimensional integral Lyapunov-Krasovskii functional is introduced for the adaptive controller to guarantee global stability of the considered systems and also ensure convergence of the tracking errors to ...

This article addresses the challenge of attitude synchronization a group rigid bodies (considered to be agents) with zero final angular velocity. A collaborative control strategy is proposed tackle this issue, using decentralized consensus within leader-follower scheme, and communication between agents activated by events. The parameterized unit quaternion. law incorporates an event function sp...

We propose a technique for the design and analysis of decentralized adaptation algorithms in interconnected dynamical systems. Our technique does not require Lyapunov stability of the target dynamics and allows nonlinearly parameterized uncertainties. We show that for the considered class of systems, conditions for reaching the control goals can be formulated in terms of the nonlinear L2-gains ...

In this paper, an estimator with an appropriate adaptive law for updating parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. Using the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for indirect ...

This paper deals with a catalytic continuous stirred tank reactor (CCSTR) example, mo deled as a two-input constrained nonlinear system. Based on the Lyapunov-based linearization strategy, the saturation-type parameterized control design can reduce the effect of actuator subject to amplitude and rate constraints, and the integrated two-input control framework can ensure the asymptotic output re...