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The paper presents a modified adaptation algorithm for the super-twisted sliding mode controller structure, based on the barrier function method. The aim of the paper is to reduce the chattering phenomena of the controller, which limited the use of the controller in different applications. The chattering phenomena are mostly caused by the overestimated controller gain due to the assumed disturbance bound, which is mostly inaccurate. The chattering origins are also the unknown parasitic dynamic of the system and discrete implementation of the controller. The proposed method with the Barrier function is used to alleviate the chattering phenomena with the adaptation of the controller parameters. The novelty of the method is using an adaptation procedure only in prescribed regions of the sliding variable, otherwise, the adaptation is not used. The advantage of the method is the proper rejection of the chattering phenomena in the vicinity of the manifold of the sliding variable, regardless of the order of the system. With proper selection of the adaptation boundary, the effect of discrete implementation, especially for a longer sampling time of the algorithm, can be suppressed efficiently, as well as the effect of the overestimated controller parameters. The proposed method is verified and compared with a standard version of the algorithm in simulation and real-time environments.

This paper presents an improved monitoring system for the failure detection of engraving tool steel inserts during the injection molding cycle. This system uses acoustic emission PZT sensors mounted through acoustic waveguides on the engraving insert. We were thus able to clearly distinguish the defect through measured AE signals. Two engraving tool steel inserts were tested during the production of standard test specimens, each under the same processing conditions. By closely comparing the captured AE signals on both engraving inserts during the filling and packing stages, we were able to detect the presence of macro-cracks on one engraving insert. Gabor wavelet analysis was used for closer examination of the captured AE signals' peak amplitudes during the filling and packing stages. The obtained results revealed that such a system could be used successfully as an improved tool for monitoring the integrity of an injection molding process.

This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution.

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