Abstract
In the multivariable control literature there are few techniques that face the problem of selecting suitable loop pairings in non-linear multivariable systems. Most techniques analyze the linearized system at a specific operating point. This paper proposes a new methodology to optimally and simultaneously select the loop pairings and the tuning of the parameters of the decentralized control by applying a multi-objective optimization approach directly on the non-linear system. The main contribution of this work is that the proposed methodology enables a detailed multi-dimensional analysis of the performances and trade-offs in the available loop pairings to control a multivariable non-linear system. The methodology is applied in this paper to three examples that analyze how the different types of loop pairings conflict. In one of the examples, the proposed methodology was applied first in the linearized system and later in the non-linear system. The results were contradictory and show how the application of loop pairing techniques for linear systems can be inaccurate when they are applied on a non-linear system previously linearized at an operating point. The following examples show that the operating point of a non-linear system, the design objectives of each multi-objective problem, as well as the designer's preferences have important roles in the selection of an optimal loop pairing.
Highlights
The development of efficient control strategies for multiple-input and multiple-output (MIMO) systems remains a challenge for designers or control engineers
The analysis in the decision making stage is more complex compared to a scenario of only two design objectives. Another advantage is that having more information on each multi-objective optimization problem (MOP) helps a designer choose an optimal solution with greater certainty. It can be seen in this first example that the optimal inputoutput pairing for the decentralized control of the non-linear multivariable system shown in Fig. 5 depends on the following aspects: the operating point in which the system is analyzed and its dynamics at that point; the design objectives proposed for each design concept; the designer’s preferences relative to the design objectives; and the type of controller structure
This paper shows a new framework for analyzing the problem of selecting optimal input-output pairings for decentralized control of non-linear multivariable systems
Summary
The development of efficient control strategies for multiple-input and multiple-output (MIMO) systems remains a challenge for designers or control engineers. An interesting aspect of the proposed loop pairing methodology is that it is associated with both the selection of input-output pairings, as well as the tuning of each MIMO system controller in the multi-objective optimization (MOO) process This new methodology is compared to other methodologies from the existing literature and its benefits and convenience are demonstrated. It is possible to find a loop pairing that successfully controls the level of each tank This last example is proposed to show the applicability of the methodology in non-linear MIMO systems with a greater number of inputs and outputs. The proper selection of an input-output pairing to perform the decentralized control of a non-linear MIMO system is strongly related to the following aspects: the designer’s preferences over the design objectives of each MOP; the optimal tuning of control structures; as well as the operation zone where a non-linear multivariable system is analyzed.
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