Dynamic neural networks are often used for nonlinear system identification. This paper presents a novel series-parallel dynamic neural network structure which is suitable for nonlinear system identification. A theoretical proof is given showing that this type of dynamic neural network is able to approximate finite trajectories of nonlinear dynamical systems. Also, this neural network is trained...

Dynamic neural networks are often used for nonlinear system identification. This paper presents a novel series-parallel dynamic neural network structure which is suitable for nonlinear system identification. A theoretical proof is given showing that this type of dynamic neural network is able to approximate finite trajectories of nonlinear dynamical systems. Also, this neural network is trained...

planning robot trajectory is a complex task that plays a significant role in design and application of robots in task space. the problem is formulated as a trajectory optimization problem which is fundamentally a constrained nonlinear optimization problem. open-loop optimal control method is proposed as an approach for trajectory optimization of cable parallel manipulator for a given two-end-po...

The problem of observer-based fault diagnosis of a certain class of nonlinear dynamic systems is studied. To solve this problem, the following approach is suggested: replacing the initial nonlinear system by certain linear logic-dynamic system, obtaining the bank of linear logic-dynamic observers, and transforming these observes into the nonlinear ones. The procedure of the linear logic-dynamic...

A summarized study of the current state-of-the-art of the controlled intelligent systems based on the synergy of the potential of fuzzy logic in Takagy-Sugeno fuzzy systems with the structural flexibility and sustainability of switched nonlinear dynamic systems. In particular, following some of the fundamental theorems on quadratic stability of general nonlinear dynamic systems, due to Zhao and...

he nonlinearities of nonlinear dynamic systems have been traditionally handled in the literature by the use of classical linear control methods, which rely on linearized models approximating the dynamic system’s equations. These methods are just valid in a small operation range. When the required operation range has to be larger, the linear controller is likely to perform poorly. Nonlinear cont...

Nonlinear structural dynamic system identification is often more a subjective art than it is a direct application of some particular method in systems theory. The nonlinear problem is subjective because although there are many analytical methods from which to choose, there is no general approach to detect, characterise, or model input-output relationships in nonlinear systems. This paper is a s...