An H1 control strategy has been designed for a SISO second-order nonlin- ear model of a biotechnological process with unknown statistical characteristics of a single-coefficient random perturbation and of the measurement noise. For this purpose, the model was linearised preliminarily in the neighbourhood of a chosen stepwise control action trajectory and of the known value of the coeffi- cient. The proposed controller consists of an H1 state regulator connected with an H1 filter providing optimal estimates of the unmeasurable state variables. The simulation studies performed under a realistic modelling of the above per- turbation and noise (as Gaussian white noises) evidence good performance, at the minimum equipollent to that of a classical PID controller, viz. perturba- tion compensation in the regulated output as well as enhanced rate of transition between the chosen setpoints.