This paper presents a novel framework for integrating artificial empathy into robot swarms to improve communication and cooperation. The proposed model uses fuzzy state vectors to represent the knowledge and environment of individual agents, accommodating uncertainties in the real world. By utilizing similarity measures, the model compares states, enabling empathetic reasoning for synchronized swarm behavior. The paper presents a practical application example that demonstrates the efficacy of the model in a robot swarm working toward a common goal. The evaluation methodology involves the open-source physical-based experimentation platform (OPEP), which emphasizes empirical validation in real-world scenarios. The paper proposes a transitional environment that enables automated and repeatable execution of experiments on a swarm of robots using physical devices.

The goal of this paper is evaluation of cuckoo search algorithm applied as an optimization method for finding parameters values of 2DOF -PID speed controller in two-sided electrical drive. The assumed structure of the controlled mechanism consists of three-mass system with backlash. Mechanical resonances revealed by the system are located low enough to be actively damped by the controller. The results of cuckoo search optimization for two-side speed control system are compared with those found for conventional one-side drive system. An analysis of effectiveness of optimized control system for these two cases of its structure was performed, taking into consideration various control quality factors.

The following paper presents a method for improving the dynamics of a PMSM drive torque control loop by using Quasi Z-Source Direct Matrix Converter. In recent research Quasi Z-Source, which is a boost converter, was connected with the Matrix Converter in order to allow operation with unity voltage transfer ratio. In this paper voltage boost of the mentioned device was used to speed up the increase and decrease of the current in motor coils. A Field Oriented Control for Matrix Converter method is presented, which is adapted to operate with Quasi Z-Source controlled by the Simple Boost. The simulation research comparing the traditional Matrix Converter with the proposed system was performed. The following were analysed: motor current rise time, power grid THD, spectrum and power consumption of both devices. Quasi Z-Source Direct Matrix Converter turned out to have higher torque control loop dynamics and lower values of the current control error integral but at the cost of an increase of power consumption and THD.

This paper introduces a novel artificial intelligence model that integrates artificial empathy into the decision-making processes of collaborative agent systems. The existing models of collaborative behaviors, especially in swarm applications, lack the aspect of empathy, known to improve cooperation in human teams. Emphasizing both cognitive and emotional aspects of empathy, the introduced model navigates communication uncertainties and ambiguities, transforming these challenges into opportunities for learning and adaptation in dynamic environments. A significant feature of this model is its handling of imprecision through fuzzy logic, using fuzzy similarity measures in the decision process. The main objective of the presented research is to introduce a new model for improving cooperativeness in multi-agent systems with the use of cognitive empathy. Future research focus on implementing the model on physical platform and optimize the artificial empathy algorithms in the decision-making module.

In the paper, an adaptive structure for two-sided electrical drive is presented. The control object has a multiple-input multiple output structure, since two input signals (motor torques) are available for the controller. The assumed model of the plant is non-linear (presence of backlash) and reveals resonant nature (elasticity in the mechanical structure). The controller is a two-layer recursive neural network, which outputs are reference torques of motors of the electromechanical plant. The conducted research investigation included variety of structures of the neural controller, with different numbers of recursive feedbacks, different horizon of former measurements. Operation of this control structure with and without external anti-resonant filtration was compared as well.

This paper presents optimisation results of input filter parameters for a Direct Torque Control driven Matrix Converter-fed PMSM drive. The main objective of performed research was to achieve better quality indicators of input filter as compared to the analytic method. DTC method is based on controlling the length and angle of a stator flux linkage vector with MC states chosen from a Switching Table. Therefore, presented method has a variable switching frequency, which makes it difficult to analytically appoint a suitable filter. The optimization was performed using one of the newest metaheuristic algorithms - Cuckoo Search. In the article author proposes an objective function, optimization restrictions and filter quality indicators connected with the power factor, electromagnetic torque error, current drawn from the grid, voltage THD and grid current. As a result of this analysis, best filters were chosen, whose performances were then compared in simulation research. Eventually, a filter appointed by mentioned optimization achieved better results for power factor and grid current distortion indicators. Remaining parameters were similar to those of analytic filter.