The paper aims to compare and prove a pair of disturbance/uncertainty rejection control laws for the well-known four tank control problems. Control requirements are expressed in terms of a set point sequence as it usual in the literature. Uncertainty class is defined as the union of four sub-classes: unknown disturbance, parametric uncertainty, measurement errors and neglected dynamics. Modelling and design allow insight of the dynamic properties of the problem. They are formulated by a pair of theorems which fix the range of application. Theorem are confirmed by the results simulated runs, and indicate the correct way to further broaden control design applicability. Disturbance rejection (better uncertainty) design is deployed using the Embedded Model Control methodology: only unknown disturbance and parametric uncertainty can be rejected, whereas neglected dynamics effects must be filtered. As a result, simple performance and stability inequality can be formulated in the frequency domain and lead to closed-loop pole placement. Inequalities are such to reveal whether pole placement is feasible and how feasibility can be recovered, an issue which at authors knowledge is rarely encountered in the literature. Simulated runs prove the design procedure.

The four-tank control problem: Comparison of two disturbance rejection control solutions / Huang, Congzhi; Canuto, Enrico; Novara, Carlo. - In: ISA TRANSACTIONS. - ISSN 0019-0578. - 71:(2017), pp. 252-271. [10.1016/j.isatra.2017.07.020]

The four-tank control problem: Comparison of two disturbance rejection control solutions

CANUTO, Enrico;NOVARA, Carlo
2017

Abstract

The paper aims to compare and prove a pair of disturbance/uncertainty rejection control laws for the well-known four tank control problems. Control requirements are expressed in terms of a set point sequence as it usual in the literature. Uncertainty class is defined as the union of four sub-classes: unknown disturbance, parametric uncertainty, measurement errors and neglected dynamics. Modelling and design allow insight of the dynamic properties of the problem. They are formulated by a pair of theorems which fix the range of application. Theorem are confirmed by the results simulated runs, and indicate the correct way to further broaden control design applicability. Disturbance rejection (better uncertainty) design is deployed using the Embedded Model Control methodology: only unknown disturbance and parametric uncertainty can be rejected, whereas neglected dynamics effects must be filtered. As a result, simple performance and stability inequality can be formulated in the frequency domain and lead to closed-loop pole placement. Inequalities are such to reveal whether pole placement is feasible and how feasibility can be recovered, an issue which at authors knowledge is rarely encountered in the literature. Simulated runs prove the design procedure.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2678904
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