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EN
This paper presents a concept of architecture and ontology layouts for the development of multiagent model-based predictive control systems. The presented architecture provides guidelines to simplify the development of agent-based systems and improve their maintainability. The proposed multiagent system (MAS) layout is split into multiple subsystems that include agents dedicated to performing assigned tasks. MAS implementation was prepared which can use provided algorithms and actuators and can react to changes in its environment to reach the best available control quality. An example of MAS based on the proposed architecture is shown in the application of dissolved oxygen (DO) concentration control in a laboratory-activated sludge setup with a biological reactor. For that application, MAS incorporates agent-based controllers from the boundary-based predictive controllers (BBPC) family. Presented experiments prove the flexibility, resilience, and online reconfiguration ability of the proposed multiagent system.
EN
In the paper, problem of proper tuning of second-order Reduced Active Disturbance Rejection Controller (RADRC2) is considered in application for industrial processes with significant (but not dominant) delay time. For First-Order plus Delay Time (FOPDT) and Second-Order plus Delay Time (SOPDT) processes, tuning rules are derived to provide minimal Integral Absolute Error (IAE) assuming robustness defined by gain and phase margins. Derivation was made using optimization procedure based on D-partition method. The paper also shows results of comprehensive simulation validation based on examplary benchmark processes of more complex dynamics as well as final practical validation. Comparison with PID controller shows that RADRC2 tuned by the proposed rules can be practical alternative for industrial control applications.
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