Moreover, in the industrial context, once the control design phase is accomplished and the control system is implemented into final products, an end-of-line tuning phase is usually scheduled to deal with constructive tolerances and production spreads which cause the final system to be different from the prototype one used for control validation and testing. Hence, this phase is tailored to optimize the controller parameters so as to guarantee that the expected gear shifting performance is achieved on all vehicles. Usually, this phase is carried out by human testers, who tune the controller parameters based on personal driving preferences and experience. Thus, is it clear that end-of-line tuning is a crucial and difficult phase to deal with. As a matter of fact, since no objective indexes to evaluate the gear shift performance and comfort exist, a gear shift can be qualified as comfortable by one operator, but not by another one: this means that the final tuning can lead to very different gear shift behaviors on different vehicles of the same type. Note that, as the vehicle handling qualities, of which the gear shift characteristics are a significant component, is often considered as a trademark of the single manufacturer, the ability of delivering vehicles with identical manoeuvre features can be a key to achieve customers’ satisfaction and to promote customers’ loyalty to the brand. Moreover, another significant advantage of the proposed approach is that of reducing the industrial costs associated with end-of-line tuning by reducing the number of gear shifts needed to tune each vehicle and by making the process automatic, thus not requiring highly experienced operators to perform it.
It is worth noting that the approach presented in this work, even though tailored to a specific application, has a validity which goes beyond the considered problem, as the aforementioned design steps constitute a working paradigm which can be applied in many different production contexts. As a matter of fact, this paper is one of the first contributions which aims at formalizing the end-of-line tuning of industrial applications endowed with control systems, proposing a systematic approach to the considered problem. In this respect, the results in [13] and [16] offer other applications of the proposed methodology and address the problem of quantifying of the driving style and safety via measured data, and of designing and objectively tuning the motion inversion control of an agricultural tractor, respectively.
Although being different problems with respect to that considered herein, both these works share (all or part of) the systematic approach presented in this work, which is constituted by the following steps:
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an evaluation of the characteristic features which define the quality of the considered system;
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an experimental sensitivity analysis to single out the relation between the features to be optimized and the measurable variables;
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the definition of the cost functions;
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the design of the control algorithm and of the procedures for its end-of-line tuning grounded on the cost functions optimization.