Stochastic control design techniques found in the chemical process control literature generally focus on the reduction of state or output variance to improve process operation. Most of these techniques address the problem of minimizing a quadratic cost function subject to linear process dynamics. In these cases, a linear feedback control law results and the disturbance, state and output PDF’s are Gaussian. In this paper, the problem of control design for nonlinear stochastic processes and nonsymmetric, nonquadratic cost functions is addressed. A control design technique is presented for first-order, discrete-time processes with a single input and additive Gaussian white noise.