The minimization control problem of quadratic functionals for the class of affine nonlinear systems with the hypothesis of nilpotent associated Lie algebra is analyzed. The optimal control corresponding to the first-, second-, and third-order nilpotent operators is determined. In this paper, we have considered the minimum fuel problem for the multi-input nilpotent control and for a scalar input...

In this paper, the robust tracking control scheme is proposed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with input saturation and unknown external disturbance based on the recurrent wavelet neural network disturbance observer (RWNNDO) and the backstepping technique. And then, the developed robust tracking control scheme is applied to an unmanned aerial vehic...

In order to effectively implement a good model based control strategy, the combination of different linear models working at various operating regions are mostly utilised since a single model that can operate in that fashion is always a difficult task to develop. This work presents the use of soft computing approaches such as evolutional algorithm called simulated annealing (SA), a genetic algo...

This paper presents a theoretical approach to implementation of the “Multi-realization of nonlinear MIMO systems”. This method aims to find state-variable realization for a set of systems, sharing as many parameters as possible. In this paper a special nonlinear multi-realization problem, namely the multi-realization of feedback linearizable nonlinear systems is considered and an algorithm for ...

Multi-motor synchronous system is a multi-input multi-output, nonlinear and high coupling control system. The neural network generalized inverse system can realize the linearization and decoupling of the nonlinear control. Local minima, irrationality learning rate and over learning easily occur in traditional feedforward neural networks. To overcome the problems, it put forward a single hidden-...

This paper proposes a novel strategy for dynamic open-loop optimization of multivariable nonlinear systems. The methodology is based on the Fourier series and orthonormal polynomials control vector parameterization in sequential direct solution approach. advantages this technique are that few number parameters required smooth profile obtained. proposed evaluated case study recombinant protein p...

We extend the results in [14] to multi-input systems, and utilize these to obtain necessary and sufficient conditions for the linearization of discrete-time nonlinear systems via restricted dynamic feedback. We observe that for discrete-time nonlinear systems, the bound on the number of delays (or integrators) needed to synthesize the linearizing dynamic feedback differs from the continuous-tim...

This paper considers output estimator based fault detection problem for a class of nonlinear systems with unknown system parameters. Because observer design for such systems is extremely difficult if not impossible, output estimator design is used for the purpose of fault detection. In order to achieve output estimator design using adaptive approaches, a multi-input multi-output (MIMO) nonlinea...