Iterative Controller Tuning by Real-Time Optimization

Abstract

The present article looks at the problem of iterative controller tuning, where the parameters of a given controller are adapted in an iterative manner to bring the user-defined performance metric to a local minimum for some repetitive process. Specifically, we cast the controller tuning problem as a real-time optimization (RTO) problem, which allows us to exploit the available RTO theory to enforce both convergence and performance guarantees. We verify the effectiveness of the proposed methodology on an experimental torsional system and note that the results are particularly promising considering the simplicity of the method.

A Real-Time Optimization Framework for the Iterative Controller Tuning Problem

“…We qualify this via the following assumption, which was originally stated in the MPC context in [19] and then extended to the general controller in [20]. …”

“…Not surprisingly, this presents a computational challenge, as the sampling time for this system is only 60 ms, which is, with the current version of the solver, insufficient-the solver needing at least a few seconds to provide a new choice of parameters. While a much simpler implementation that satisfies this real-time constraint has already been successfully carried out on the same system [20], we choose to apply the methodology presented in this paper by using a wait-and-synchronize approach. Here, the solver takes all of the available data and starts its computations, with no adaptation of the parameters being done until the solver's computations are finished.…”

Sufficient Conditions for Feasibility and Optimality of Real-Time Optimization Schemes - II. Implementation Issues

“…Finally, it would be interesting to see how SCFO-supplemented RTO schemes perform in real experimental problems! While a rudimentary application of the SCFO to an unconstrained problem of iterative controller tuning has already given positive results (Bunin et al, 2013c), it is of great interest to see the results for all sorts of RTO problems, and several other applications are already in planning, together with an open-source solver that incorporates all of the theory discussed in this paper (Bunin et al, 2013b).…”

Fractional order Proportional-Integral-Derivative Controller parameter selection based on iterative feedback tuning. Case study: Ball Levitation system

“…The gradient is calculated based on a series of experiments, not based on the system model, making it a model-free method. IFT has already been used in applications like: control of wafer stage system (Heertjes et al, 2016), servo motor speed and position control (Kissling et al, 2009), control of inverted pendulum (Precup et al, 2008), head positioning servomechanism control in hard disk drives (Al Mamun et al, 2007), torsional system control (Bunin et al, 2013) and waste water treatment (Mahathanakiet et al, 2002). Navalkar and Wingerden (2015) employed IFT method to reduce the life time dynamic loads on wind turbines blades.…”