Here, we have utilised the concept of fuzzy logic and Karl Popper’s notion of verisimilitude to advocate navigating the complexity of psychiatric nosology, emphasising that psychiatric disorders defy Boolean logic. We underscore the importance of embracing imprecision and collecting extensive data for a more nuanced understanding of psychiatric disorders, asserting that falsifiability is crucial for scientific progress. We encourage the advancement of personalised psychiatric taxonomy, urging the continual accumulation of data to inform emerging advancements like artificial intelligence in reshaping current psychiatric nosology.

Friction stir welding is a prominent technique for making defect-free joints of aluminum alloys. The aluminum alloy AA2014-T6 finds wide applications in aerospace, naval and automotive applications. This paper attempts to predict the tensile strength and hardness characteristics of friction stir welded aluminum alloy AA2014-T6 by a fuzzy logic model. Friction stir welding was carried out by varying tool rotational speed (700, 1,000 and 1,400rpm), welding speed (20, 35, 50mm/min) and axial force (10, 12, 14kN) at three levels. The tensile strength and hardness characteristics of the welded specimens were obtained from the experiments conducted as per Taguchi’s L27 orthogonal array. A Mamdani-type fuzzy logic model was developed to predict the tensile strength and nugget hardness characteristics of the FSW joints. The fuzzy model was evaluated by comparing the results of confirmation experiments with that of the results predicted by the model. The confirmation experiments were conducted with a new set of parameters other than the ones used for building the model. The fuzzy model exhibits marginal variations of 2.53% for tensile strength and 2.42% for weld nugget hardness compared to the results of the conformation experiments.

Robotics with artificial intelligence techniques have been the center of attraction among researchers as it is well equipped in the area of human intervention. Here, the krill herd (KH) optimization algorithm is modified and hybridized with a fuzzy logic controller to frame an intelligent controller for optimal trajectory planning and control of mobile robots in obscure environments. The controller is demonstrated for single and multiple robot’s trajectory planning. A Petri-net controller has also been added to avoid conflict situations in multi-robot navigation. MATLAB and V-REP software are used to simulate the work, backed with real-time experiments under laboratory conditions. The robots efficiently achieved the goals by tracing an optimal path without any collision. Trajectory length and time spent during navigation are recorded, and a good agreement between the results is observed. The proposed technique is compared against existing research techniques, and an improvement of 14.26% is noted in terms of path length.

One of the biggest challenges of companies developing new solutions is how to properly manage the different relationships with external partners, especially in the case of Product-Service Systems (PSS). Developing a PSS requires for Original Equipment Manufacturers (OEM) to rethink the organization and roles of the different stakeholders regarding the characteristics of such environments. This paper aims to introduce a methodology to build a framework for inter-enterprise collaboration performance assessment and its corresponding Key Performance Indicators (KPIs). An extensive list of KPIs is established from key factors of collaboration performance and organizational characteristics in PSS context. Finally, further steps of the methodology are discussed where fuzzy techniques are used.

This paper deals with the problem of fault-tolerant control (FTC) for redundant multirotor unmanned aerial vehicles (UAVs) subject to actuators failures. A fuzzy logic approach is used to solve the constrained control allocation problem by adjusting the components of the multiplexing vector once a motor failure is detected. This fuzzy logic allocation problem is tuned using the Bacterial Foraging Algorithm (BFA), a powerful bio-inspired optimisation technique. The effectiveness of this approach is illustrated through real experimental application to a hexarotor UAV, where up to two motors failures are considered.

This paper shows that any propositional logic that extends a basic substructural logic BSL (a weak, nondistributive, nonassociative, and noncommutative version of Full Lambek logic with a paraconsistent negation) can be enriched with questions in the style of inquisitive semantics and logic. We introduce a relational semantic framework for substructural logics that enables us to define the notion of an inquisitive extension of λ, denoted as ${\lambda ^?}$, for any logic λ that is at least as strong as BSL. A general theory of these “inquisitive extensions” is worked out. In particular, it is shown how to axiomatize ${\lambda ^?}$, given the axiomatization of λ. Furthermore, the general theory is applied to some prominent logical systems in the class: classical logic Cl, intuitionistic logic Int, and t-norm based fuzzy logics, including for example Łukasiewicz fuzzy logic Ł. For the inquisitive extensions of these logics, axiomatization is provided and a suitable semantics found.

The operations of expansion and refinement on nondeterministic matrices (Nmatrices) are composed to form a new operation called rexpansion. Properties of this operation are investigated, together with their effects on the induced consequence relations. Using rexpansions, a semantic method for obtaining conservative extensions of (N)matrix-defined logics is introduced and applied to fragments of the classical two-valued matrix, as well as to other many-valued matrices and Nmatrices. The main application of this method is the construction and investigation of truth-preserving ¬-paraconsistent conservative extensions of Gödel fuzzy logic, in which ¬ has several desired properties. This is followed by some results regarding the relations between the constructed logics.

Propeller synchrophasing control is an active method to reduce the noise and vibration of turboprop aircraft without additional weight and power. Phase control accuracy has a great influence on the noise reduction effect of synchrophasing. An integrated power/speed/synchrophasing control strategy is proposed to improve the control precision. Speed/phase control transformation logic based on a multi-blade phase plane is adopted which can take both the rapidity of speed response and phase control precision into account, but there exists switching oscillation during the mode transform process. In order to suppress the phase fluctuation due to exterior disturbance, a slave-slave control scheme is provided to take place of a master-slave scheme. Simulation results based on an integrated turboprop engine/propeller real-time non-linear model show that speed/phase integration logic can improve the response rapidity of both the speed and phase. The precision of the control system is verified to be in acceptable range.

This article aims to present a novel control strategy for quadrotor helicopter. It is composed of three main parts constituting the system modelling, the integral back-stepping control, and fuzzy logic compensator. In the first part, a non-linear model is presented taking in consideration some non-linearities and variables that are usually neglected. In the second part, a controller based on the integral back-stepping algorithm has been developed for the system in order to make the system follows a desired path. However, due to complexity of paths and to the presence of unknown disturbances, a fuzzy logic compensator is added in parallel to the integral back-stepping controller to improve trajectory tracking in some critical conditions (high wind speed, mass variation, etc.). Simulation results have been presented to show the effectiveness of the proposed approach.

In this paper, the development of a fault-tolerant control system for an aircraft that exploits both the hardware and analytical redundancy in the system is considered. A control allocation approach is developed where the total control command is computed and distributed among the available control surfaces. The actuator’s position and rate limits are taken into account in the optimisation problem. Existing fault-tolerant control allocation techniques produce look-up tables of control gains based on certain faults in the model. In contrast, the developed reconfigurable approach presented here incorporates a new process that redistributes control efforts which is updated whenever a fault occurs. In order to correlate between control effort redistribution and the fault magnitude, a fuzzy logic scheme is implemented, which handles a wide range of fault magnitudes on-line. The approach is applied for the most severe type of fault, which is the “lock-in-place” (jam) fault. Results show that the developed approach successfully handles the faulty situations and enhances aircraft flying responses by utilising the available healthy controls.

Aeolian sands are the main reservoir rock in some of the largest gas fields, such as the Shell-Exxon Groningen Field, operated by NAM. Although aeolian reservoirs have been studied for many years, there is still room for improvement in the predictive modeling of such reservoirs. A pilot project with this objective was initiated by SIEP B.V. in 1997, together with Heriot-Watt University in Edinburgh, UK and with Uppsala University, Sweden, to evaluate the factors influencing aeolian systems, and to formulate a forward model using ‘fuzzy logic’.

The project was initiated to develop a fuzzy system for generic modeling of aeolian architectures. The key aims were to be able to predict the type, amount and distribution of major facies in generic aeolian systems and specifically to model regional-scale architecture in the sub-surface. Fuzzy rules and sets, which defined the behaviour of aeolian systems, were constructed and used to modify the pre-existing fuzzy modeling software which had been designed for shallow and deep marine systems. The modeling procedure used input data appropriate to the Rotliegend climate, and was validated by comparing the resulting models, in terms of thickness and spatial distribution of facies types, to well data from the Upper Rotliegend interval of the Lauwerszee Trough area, NE Netherlands (Figures 1 & 2).

Responding to growing concerns regarding energy-efficient facades, this paper describes the structure and process followed in the design of a responsive sun-shading system based on the use of rotating plates with two degrees of freedom. The proposal considers, among others, the definition of variable design parameters, areas of performance evaluation and control, and construction detailing development represented by a first 1:2 unit (module) model. In the process, computational simulation procedures were employed to explore configurational possibilities that would provide high-performance solutions to the light requirements of the particular covered spaces. In developing the system, it was noticed that due to the highly subjective requirements of users in terms of quantity and quality of lighting, a purely Boolean control system would not always be appropriate. Following from that, and taking advantage of the dynamic nature of the system, a further approach of control supported by fuzzy logic was also implemented at the operative state, whose logic is explained. Digital simulations were carried out to assess the performance of the system, and their results demonstrate more even light distribution levels compared to traditional systems.