This paper present a new approach methods for analysis and optimal control of nonlinear system including time-varying parameters.
Concerned with those problems, this paper uses the adaptive approach scheme and block pulse transformations for solving ...
This paper present a new approach methods for analysis and optimal control of nonlinear system including time-varying parameters.
Concerned with those problems, this paper uses the adaptive approach scheme and block pulse transformations for solving state equation and the Riccati differential equation which is usually quite difficult.
Recently block pulse function finds application in a variety of fields such as analysis and design of nonlinear systems, solution of distributed systems and identification problems because computer control is usually implemented on the basis of the discrete time where the step functions produced by sampling and holding can be precisely expressed by finite block pulse function series.
To obtain the new abaptive approach method, the following steps are used :
First, the nonlinear system is modeled as x(t)=A(x, t)x(t) + B(x, t)u(t). Second, systems matrices A(x, t) and B(x, t) are considered constant at their present time t_(i). Third, optimal control vector is determined by intergrating the matrix Riccati equation backward from final time t_(f) to present time t_(i) via block pulse transformations. Fourth, the nonlinear system is controlled for a short time until some new present time t_(i+1)=t_(i) +Δt is reached. Fifth, at this new t_(i+1) the state and system parameters are updated and the optimal control vector is recalculated as the same manners. These steps are processed reculsively for present time t_(i) is reached to final t_(f).
This proposed method is applied to linear and nonlinear system examples and the viabiity of this method is established with simulation results for comparision with other approach method.
The method proposed in this paper is simple and computationally advantageous. Furthermore this method is very applicable to analysis and optimal control problems of nonlinear systems.