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This article presents a new refinement design routine aimed at solving the robust multivariable tracking error problem with reduced conservatism. The prevailing multivariable quantitative feedback theory (QFT) approach is to implicitly overbound the model‐error tracking set frequency response in magnitude using the triangle inequality, with the intention of arriving at a set of univariate design constraints that independently describe the feedback controller solution space. While this method is effective in the low‐frequency range (where the loop gain tends to be large), the mid‐ to high‐frequency design regions (where diagonal dominance is not possible in general) suffers from arbitrarily large design conservatism. This inhibits minimum gain‐phase solutions and necessitates undesirable over‐design in the frequency band that can contribute to large, expensive control action. The proposed method follows a refinement approach that makes use of information from an a priori feedback control design. In this way, the tracking error problem is reposed as a differential design, and gain‐phase information from the previous iteration can be captured to reduce the conservatism imposed when applying the triangle inequality. Additionally, a constrained optimization routine is used to select a prototype feedforward filter that can relax the constraint set, thereby increasing the accessible solution space of the diagonal feedback controller. Finally, a nondiagonal, multivariable feedforward filter bound generation routine is defined that relies on existence conditions and is free of induced design conservatism. The viability of this design methodology is demonstrated on two benchmark problems of varying complexity, in order to demonstrate the widespread efficacy. [ABSTRACT FROM AUTHOR]

Summary: This article presents a solution to the 2 × 2 multivariable tracking error problem. Current quantitative feedback theory methods commonly employ plant‐inverting splittings in order to arrive at an approximately decoupled design on the feedback control elements. This results in suitable design regions in the high‐gain, low‐frequency range, but can result in conservative design at and above the gain‐crossover frequency, resulting in overdesigned feedback controllers. Our method aims to reduce this conservatism by supplementing a plant‐inverting design with a non‐plant‐inverting design, which tends to perform well at higher frequencies. Decoupling the design of the controller elements is facilitated by making use of appropriate existence conditions. The union of the two resulting design regions then describes a larger solution space, and by enlarging the admissible design regions for the feedback controller, lower gain feedback controller design at all design frequencies of interest may be possible. A benchmarking example is presented, showing the viability of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a method for designing a robust two‐degree‐of‐freedom control scheme, capable of satisfying multiple model‐error specifications on a plant by plant basis. Traditional quantitative feedback theory methods generally use a single model‐error or above‐below magnitude tracking specification, which can result in overdesign for plants located away from the bounding conditions. The performance specifications are also generally hand‐tuned, or iteratively adjusted to keep the underlying time‐domain signals within permissible levels. Our method aims to perform a model‐error design on a per‐plant basis, such that each plant's corresponding model tracking has equal weighting given the plant's inherent feedback requirements and capability. The quantitative feedback theory method allows this per‐plant approach to be undertaken with ease. Additionally, sufficiently low‐order model specifications are designed using simple optimisation, which take into account performance limiting effects, such as non‐minimum phase behaviour and signal constraints. A worked example is presented, showing the viability and transparency of the proposed method. [ABSTRACT FROM AUTHOR]

An actuated tail can impart large angular impulse over short time spans, but swinging in a plane results in inevitable tail angle saturation. Cheetahs (Acinonyx jubatus) are observed swinging the tail in a cone during turns [1], and this paper develops a simplified two-degree-of-freedom (pitch and roll) rigid tail model to investigate this motion. Trajectory optimization and experiments on a robotic platform confirm the observed cone motion as a useful solution to roll stabilization. These results are relevant to the understanding of tail motions in biomechanics and bioinspired tailed robots. [ABSTRACT FROM PUBLISHER]

Abstract: The behaviour of single input, single output, continuous time systems sampled with various types of jitter in both measurement and control action is investigated. It is shown that the effects of jitter can be modelled by approximations for the plant dynamics, and additive noise constructed by the modulation of plant signals with the jitter. These approximations give useful insights for digital controller design. [Copyright &y& Elsevier]

A loop-by-loop approach is used to analyse multivariable water flow and collecting vessel-level control problems during Benson® type boiler start-up. It is shown that the circulation loop must be tuned so that its bandwidth is less than the feed water loop bandwidth. [Copyright &y& Elsevier]

Discusses the measurement of the level of interaction in MIMO quantitative feedback design (QFT) using Perron-Frobenius root. Design approach to reduce interaction in uncertain plants via a precompensator; Application of a decentralized stability results.

Presents an algorithm for calculating design bounds in multivariable quantitative feedback theory tracking design. Use of the algorithm to solve the problem of trade-off between on- and off-diagonal constraints; Design specifications; Recommendation on the evaluation of the algorithm at each pair of elements of the plant set.

Presents an algorithm to calculate the nonconvex hull with minimum concave radius defined by the feedback system specifications. Determination of nonconvex hulls of quantitative feedback theory templates; Reduction in the computational effort required for bound calculation at a given frequency and controller phase.

The article reports on implicit quasi-steady-state approximation and application to a power plant evaporator. The construction of reduced order models using quasi-steady-state or singular perturbation approach can hardly offer good low frequency approximations. An implicit quasi-steady-state technique is planned for general nonlinear models. The resulting reduced order model is exact to first order in the perturbation parameter and its linearization is correct to first order in frequency.

This paper presents a method to classify flow regime and vapor quality in vertical two-phase (vapor-liquid) flow, using a video of the flow as the input; this represents the first high-performing and entirely camera image-based method for the classification of a vertical flow regime (which is effective across a wide range of regimes) and the first image-based tool for estimating vapor quality. The approach makes use of computer vision techniques and deep learning to train a convolutional neural network (CNN), which is used for individual frame classification and image feature extraction, and a deep long short-term memory (LSTM) network, used to capture temporal information present in a sequence of image feature sets and to make a final vapor quality or flow regime classification. This novel architecture for two-phase flow studies achieves accurate flow regime and vapor quality classifications in a practical application to two-phase CO2 flow in vertical tubes, based on offline data and an online prototype implementation, developed as a proof of concept for the use of these models within a feedback control loop. The use of automatically selected image features, produced by a CNN architecture in three distinct tasks comprising flow-image classification, flow-regime classification, and vapor quality prediction, confirms that these features are robust and useful, and offer a viable alternative to manually extracting image features for image-based flow studies. The successful application of the LSTM network reveals the significance of temporal information for image-based studies of two-phase flow. [ABSTRACT FROM AUTHOR]