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This 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. The controller design is carried out in the Quantitative Feedback Theory framework. The 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. This reduces useless fatigue and saturation risk of actuators. Different 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.

SUMMARYThis paper introduces a novel solution for the multi‐input multi‐output (MIMO) quantitative feedback theory control design problem with tracking error specifications. Looking for a minimum controller overdesign, the technique finds new controller quantitative feedback theory bounds based on necessary and sufficient conditions for the existence of suitable associated prefilter matrix elements. It improves previous approaches to the subject and includes (i) the possibility of a free selection of the nominal plant, (ii) a less conservative application of the Schwartz inequality to decisively reduce the potential controller overdesign, (iii) a methodology to design independently the elements of the prefilter matrix, and (iv) a scope of application to both sequential and nonsequential MIMO controller design methods. The benefits of the new control design technique are illustrated by means of two examples. The first one, a standard 2 × 2 MIMO problem, is provided for comparison purposes with previous approaches. The second example, included as a major control challenge, deals with a well‐known demanding distillation column benchmark problem. Copyright © 2013 John Wiley & Sons, Ltd.

SUMMARYThis article extends two recent contributions in the field of quantitative feedback theory to the multivariable case. They concern the model matching and the measured disturbance rejection problems. The model matching problem is a tracking control problem with specifications given as acceptable deviations from an ideal response. The measured disturbance rejection problem balances feedback and feedforward actions to reject disturbances. Both perspectives present advantages over classical quantitative feedback theory techniques in certain situations. This paper develops the necessary tools to solve both control problems in the case of multi-input multi-output plants. In particular, it shows how to derive nonconservative controller bounds for each of the single-input single-output control problems in which the overall multivariable problem is divided. The result is a systematic controller design methodology for multi-input multi-output plants with structured uncertainty. The application of the technique to the well-known quadruple-tank process illustrates the benefits of the method.

The regulation of a disturbed output can be improved when several manipulated inputs are available. A popular choice in these cases is the series control scheme, characterized by (1) a sequential intervention of loops and (2) faster loops being reset by slower loops, to keep their control action around convenient values. This paper tackles the problem from the frequency-domain perspective. First, the working frequencies for each loop are determined and closed-loop specifications are defined. Then, Quantitative Feedback Theory (QFT) bounds are computed for each loop, and a sequential loop-shaping of controllers takes place. The obtained controllers are placed in a new series architecture, which unlike the classical series architecture only requires one controller with integral action. The benefits of the method are greater as the number of control inputs grow. A continuous stirred tank reactor (CSTR) is presented as an application example.

SUMMARY An alternative to the traditional QFT tracking problem, in which upper and lower tolerances are imposed on the magnitude of the tracking transfer function, is to define the robust specification as a boundary on the deviation of such function from a predefined model. However, previous research exploring this approach reveals a certain overdesign and dependence on the choice of the nominal plant. This paper establishes a necessary condition on the controller from tracking error specifications. With this condition, the controller bounds introduce no overdesign, and the resulting two‐degrees‐of‐freedom design is independent of the choice of the nominal plant, similar to the traditional approach. Copyright © 2011 John Wiley & Sons, Ltd.

SUMMARYThis paper introduces a methodology to design a family of robust controllers able to go beyond the classical linear limitations. Combining robust designs and stable switching, the new controllers optimize the time response of the system by fast adaptation of the controller parameters during the transient response according to certain rules based on the amplitude of the error. The methodology is based on both a new graphical stability criterion for switching linear systems and the robust quantitative feedback theory (QFT). It is applied to the design of a pitch control system, which is one of the most critical issues in wind turbines, where a tight combination of high reliability (robustness), minimum mechanical fatigue and performance optimization is required.

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