Abstract
In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control (MRAC) system technique is proposed. Although many adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that do not require neither high processing power nor long processing time, as opposed to identification technique calculations. Additionally, a modified hill climbing algorithm that is developed in this research is specifically designed, configured and tailored for the automatic tuning of control systems. The modified hill climbing algorithm uses a systematic movement when searching for new solution candidates. The algorithm measures the quality of the solution candidate based on error function. The error function is generated by comparing the system response with a desired reference response. The algorithm tests new solution candidates using step signals iteratively. The results showed the algorithm effectiveness to drive the system response. The simulation results illustrate that the method schemes proposed in this study show a viable and versatile solution to deal with controller tuning for systems with model inaccuracies as well as controller real-time calibration problem.
Highlights
The increasing complexity of industrial processes is always pushing for advancements and innovations in technologies involved in industrial processing, includingDeterministic Artificial Intelligence control systems engineering
The Model reference adaptive control (MRAC) system structure is generally considered to have two feedback loops [12, 17], an inner feedback loop that is the ordinary feedback that is compared with the set point and fed to the controller and an outer feedback loop that modifies controller parameters based on the adaptation mechanism
To emphasize the advantages and usability of the proposed modified hill climbing algorithm, this section discusses the properties of the algorithm under real-time controller tuning considerations
Summary
The increasing complexity of industrial processes is always pushing for advancements and innovations in technologies involved in industrial processing, including. Instead of relying on manual calibration, this research proposes an automatic tuning scheme and algorithm designed for control systems to deal with model inaccuracies and parameter fluctuations during real-time operation without the need to halt plant operation. The MRAC system structure is generally considered to have two feedback loops [12, 17], an inner feedback loop that is the ordinary feedback that is compared with the set point and fed to the controller and an outer feedback loop that modifies controller parameters based on the adaptation mechanism In this technique, a reference response is to be followed by the system. Some STRs can be considered as MRAC and vice versa [12, 17]
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