High‐Gain Scheduling of the Proportional‐Integral‐Observer

Abstract

Estimation of states and unknown inputs simultaneously can be done by Proportional-Integral-Observer (PIO). This observer is used in nonlinear and robust control. It has additional integral feedback loop in comparison with the usual Luenberger observer. Increasing the gain of this observer the performance would be increased, however due to this high gain the performance is influenced by measurement noise. Advanced PI-Observer (API) algorithm is a method which is used for scheduling the optimal gain of PI-Observer based on the cost function and by using a bank of PI-Observer. In this contribution the proposed method obtains relative optimal gain by using a given cost function. Afterwards the absolute optimal gain is computed by changing the design parameters at each step based on the desired performance criteria. The absolute optimal gain is found instead of relative optimal gain in comparison with the API-Observer. Simulation results estimating contact forces acting to a vibrating elastic beam based on indirect measurements illustrate the improvement of the proposed method.

Proportional-Integral-Observer: A brief survey with special attention to the actual methods using ACC Benchmark

“…In the consequence of changing and scheduling the gain of PI-Observer based on the cost function, the performance is improved in comparison to PI-Observer and especially in the presence of noise. To achieve an absolute optimal gain, defined as the best possible gain with respect to the criteria evaluated at each step of numerical integration procedure, Modified API-Observer (MAPI-Observer) has been proposed by Bakhshande and Söffker (2014). In Fig.…”

“…It has the capability to define the relative optimal gain at each step size of the PI-Observer integration routine. Modified Advanced PI-Observer (MAPIO) has been introduced by Bakhshande and Söffker (2014) to achieve better estimation performance during the numerical integration.…”