
The authors consider a control system such that plant \(P(s)\) and controller \(C(s)\) have the following state-space representations \[ \dot x_p= A_0 x_p + B_1 w + B_2 v, \qquad z= C_1 x_p,\qquad y= C_2 x_p, \] and \[ \dot x_c= M x_c + L y, \qquad u= K x_c, \] where \(x_p\) and \(x_c\) are the states of the plant and the controller respectively and \(u, v, w, y, z \in \mathbb{R}.\) The disturbance \(w\) is a standard white noise and the actuator characteristics is \(v =\phi(u)\) where \(\phi(u)\) is standard saturation function \[ \phi(u) = \begin{cases} +1, \quad u > +1 \\ u, \quad -1 \leq u \leq +1 \\ -1,\quad u 0\), find a controller \(C(s)\) that stabilizes the system when \(w \equiv 0\) and minimizes \(J = \sigma_z^2 + \rho \sigma_u^2.\) The authors use the method of stochastic linearization. The solution involves nonlinear equations and simple bisection algorithms that can be used for the solution of these equations are provided.
Perturbations in control/observation systems, Adaptive or robust stabilization, actuator saturation, disturbance rejection, Nonlinear systems in control theory, stochastic linearization, control system, white noise, Linearizations
Perturbations in control/observation systems, Adaptive or robust stabilization, actuator saturation, disturbance rejection, Nonlinear systems in control theory, stochastic linearization, control system, white noise, Linearizations
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