This paper investigates the use of an adaptive slope seeking strategy for Single Input Single Output (SISO) process control. The static map between input and output is assumed to be of quadratic form, part of a Hammerstein model representation and model parameters are estimated by a RLS/RELS algorithm. The contribution of this paper is threefold. First, an algorithm providing an explicit expression for slope reference generation is presented. Then, a self-governed pole placement controller design strategy with integral action is proposed, avoiding the complex design of the control loop integrator gain. Eventually, the proposed slope seeking strategy eectiveness is assessed in simulation on a realistic continuous micro-algae culture in order to achieve both optimal and sub-optimal operations under the presence of measurement noise.
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