This paper presents a flight control strategy based on nonlinear dynamic inversion. The approach presented, called incremental nonlinear dynamic inversion, uses properties of general mechanical systems and nonlinear dynamic inversion by feeding back angular accelerations. Theoretically, feedback of angular accelerations eliminates sensitivity to model mismatch, greatly increasing the robust performance of the system compared with conventional nonlinear dynamic inversion. However, angular accelerations are not readily available. Furthermore, it is shown that angular acceleration feedback is sensitive to sensor measurement time delays. Therefore, a linear predictive filter is proposed that predicts the angular accelerations, solving the time delay and angular acceleration availability problem. The predictive filter uses only references and measurements of angular rates. Hence, the proposed control method makes incremental nonlinear dynamic inversion practically available using conventional inertial measurement units.

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This paper attempts to quantify the sustainability of technological processes. It is based on thermodynamics with energy carriers and materials (products, waste, etc.) expressed in the same calculable quantity-exergy (Joule). The results have three considerations. One factor reflects to that extent renewable resources are used. In addition, the technological efficiency has to be accounted for as it affects sustainability. Finally, the results take into account the generation of waste products and the exergy required for converting the waste into products which are harmless or assimilable in the ecosphere. The proposed measure of sustainability has been illustrated for two types of products. In the first illustration, ethanol production was studied. Two routes were investigated, one starting from fossil oil and the other from agricultural products. Additionally, a route based on the synthesis from carbon dioxide and hydrogen was examined, in which hydrogen was generated by splitting water with electricity from photovoltaic solar energy conversion. The second product studied was electricity, generated from the combustion of natural gas or from photovoltaic solar energy conversion. The merit of the obtained results are that they treat technological sustainability not only in qualitative but also in quantitative terms. The insights obtained can help to account for sustainability in the development of new concepts of chemical technology. Green ContextSustainability is a much used but also much mis-used term. This paper examines the meaning of the word in the context of technology and attempts to introduce a degree of quantification to it. A technological process such as the manufacture of a chemical product can be non-sustaining if it takes raw materials from the ecosphere at a rate faster than the raw material is being generated or if it produces products (typically waste) that can damage the ecological mechanisms and hence resource production. Here, three aspects of sustainability, the use of renewable resources, the technological efficiency and the waste produced, are quantified for two types of products. It seems very likely that this type of calculation will be increasingly applied as we seek the least eco-threatening option for future manufacturing. JHC

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The advantages of constrained model predictive control over proportional integral derivative (PID) control applied to a feedback-linearized entry flight-control problem are discussed. The feedback linearization is based on the full rotational equations of motion rather than on a conventional model derived from timescale separation. Input and state constraints are applied to avoid input saturations, to guarantee a minimum level of tracking performance, and to avoid physical vehicle state constraints violation. A constraint mapping algorithm is developed to map the input and state constraints on the new inputs after feedback linearization. The performance of the constrained model predictive control design is compared with that of two PID control designs. Simulation of a complete entry flight demonstrates the advantages of the constrained model predictive control design, because control surfaces do not saturate, control actions are more smooth and efficient, no gain scheduling is required, and all performance requirements are satisfied.

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