Research Article Quantitative Feedback Control of Multiple Input Single Output Systems Javier Rico-Azagra, 1 Montserrat Gil-Martínez, 1 and Jorge Elso 2 1 Electrical Engineering Department, University of La Rioja, 26004 Logro˜ no, Spain 2 Automatic Control and Computer Science Department, Public University of Navarra, 31006 Pamplona, Spain Correspondence should be addressed to Javier Rico-Azagra; javier.rico@unirioja.es Received 24 September 2013; Revised 9 December 2013; Accepted 13 December 2013; Published 7April 2014 Academic Editor: Baoyong Zhang Copyright © 2014 Javier Rico-Azagra et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tis paper presents a robust feedback control solution for systems with multiple manipulated inputs and a single measurable output. A structure of parallel controllers achieves robust stability and robust disturbance rejection. Each controller uses the least possible amount of feedback at each frequency. Te controller design is carried out in the Quantitative Feedback Teory framework. Te method pursues a smart load sharing along the frequency spectrum, where each branch must either collaborate in the control task or be inhibited at each frequency. Tis reduces useless fatigue and saturation risk of actuators. Diferent examples illustrate the ability to deal with complex control problems that current MISO methodologies cannot solve. Main control challenges arise due to the uncertainty of plant and disturbance models and when a fast-slow hierarchy of plants cannot be uniquely established. 1. Introduction Tis paper deals with systems where multiple inputs are used to govern a single output. Although scientifc literature refers to them with diverse names, here they will simply be called MISO systems. In some cases, each individual output is accessible, as in distributed energy generation systems [1], decentralised production systems [2], or unmanned feets [3]. Usually, this leads to complex multiloop control structures [4]. However, a lot of engineering MISO systems lack physical individual outputs or sensors to measure them. Such systems are common in process industry [5], where the MISO control sometimes pursues the management of the global production system [6], whereas other times it governs low-level process variables (typical examples are two pumps or a pump and a valve, used as actuators in pressure or fow control [7–9]). In other cases the MISO control attends certain subsystems in a process, such as chemical reactors [10–12] or biological reactors [13–15]. More specifc usages can be found in drying sections of paper machines [7, 16] or in aerobic digesters of waste water treatment plants [17]. Heat exchangers [18– 20], chemical reactors in polymerization processes [9, 18], or distillation columns [9, 20–23] are repeated references in the scientifc literature as MISO control applications. Te automotive industry has also adopted these principles, frstly for the government of internal combustion engines [24–27] and recently for HCCI (Homogeneous Charge Compression Ignition) engines [28–30]. Another area devoted to MISO control is the consumer electronics, and particularly the massive data storage devices [31–33]. And fnally, biological engineering applications can be found in [18, 34]. Within those MISO systems with nonindividual mea- surable outputs, the control strategies can be divided into noncollaborative and collaborative ones. Noncollaborative control selects a plant inside a battery of them, which covers a wide range of operating points for the output. Te selection criterion is based on the stationary capacity of each plant. Tus, the control law is designed for an equivalent SISO system. A selector splits online the control action to the plant or plants with capacity to regulate the output in the actual operating point. Te split-range control [35, 36] is the most representative of this methodology. A simpler method reduces to a pure SISO control system, which closes a single feedback loop around a plant. Te inputs to the other plants are manipulated manually or are lef constant [37]. Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2014, Article ID 136497, 17 pages http://dx.doi.org/10.1155/2014/136497