In this paper, a new approach is developed for robust control of nonlinear chemical processes. The methodology proposed is based on passivity theory. Uncertainty and perturbations are taken into account in the stability analysis and controller synthesis such that the resulting closed-loop system can achieve better robustness and performance. The suggested passivity framework can deal with a lar...

In this paper, dynamic multilayer neural networks are used for nonlinear system on-line identification. Passivity approach is applied to access several stability properties of the neuro identifier. The conditions for passivity, stability, asymptotic stability and inputto-state stability are established. We conclude that the commonly-used backpropagation algorithm with a modification term which ...

In this paper, dynamic neural networks are used for engine model at idle speed on-line identification. Passivity approach is applied to access several stability properties of the neuro identifier. The conditions for passivity, stability, asymptotic stability and input-to-state stability are established. We conclude that the commonly-used backpropagation algorithm with a modification term which ...

Nonlinear system online identification via dynamic neural networks is studied in this paper. The main contribution of the paper is that the passivity approach is applied to access several new stable properties of neuro identification. The conditions for passivity, stability, asymptotic stability, and input-to-state stability are established in certain senses. We conclude that the gradient desce...

Motivated by human compliant behaviors during interacting with unknown environments and how motions impedance to are adapted skilfully complete a task, this article develops motion planning scheme that is capable of generating trajectory online such tracking desired contacting forces under predefined task. First, an improved dynamical system (DS) designed generate adaptive scanning from the ori...

In this paper by using the port-controlled Hamiltonian (PCH) systems theory, a full-order nonlinear controlled model is first developed. Then a nonlinear passivity-based robust adaptive control (PBRAC) of switched reluctance motor in the presence of external disturbances for the purpose of torque ripple reduction and characteristic improvement is presented. The proposed controller design is sep...

This paper is concerned with the problem of enhanced results on robust finite-time passivity for uncertain discrete-time Markovian jumping BAM delayed neural networks with leakage delay. By implementing a proper Lyapunov-Krasovskii functional candidate, the reciprocally convex combination method together with linear matrix inequality technique, several sufficient conditions are derived for vary...

During the last two decades, important advances have been made in the field of bilateral teleoperation. Different techniques for performing stable teleoperation in non-ideal conditions have been developed, especially in a passivity framework. Until recently, however, no robust solutions for addressing this problem with variable delays and other drawbacks of packet-switched networks have been de...