This study presents a self-error compensated sequential predictive control (SE-SMPC) technique for three-phase multimodular matrix converters (MMMC). Traditional model-based predictive control (MPC) methods typically require manual tuning of weighting factors and involve significant computational effort. In contrast, the SE-SMPC method addresses these limitations by prioritizing control objectives hierarchically, thereby reducing the number of switching states without sacrificing system performance. A key feature of this approach is its builtin error self-compensation mechanism, which distributes and corrects prediction errors across modules, thereby improving dynamic accuracy. Simulation results show that the proposed controller provides accurate tracking of the load current, significantly reduces the input reactive power and offers high fault tolerance in the event of module failure. In addition, it has been shown to reduce total harmonic distortion (THD) without the need to design complex cost functions. These advantages make it particularly suitable for high-efficiency AC-AC power conversion in various renewable energy applications.

This paper presents the design and simulation of a multimodular power conversion system based on voltage source inverters (VSI), composed of two parallel-connected three-phase modules driving an induction motor. A self-error-compensated predictive current control strategy is proposed to coordinate the modules, enabling dynamic current sharing and fault-tolerant operation. In the event of a failure, the control scheme incorporates the tracking error of the faulty module into the cost function of the operational one, improving performance and continuity. Simulation results demonstrate the effectiveness of the proposed method, with improved dynamic response, reduced root mean square error (RMSE), and lower total harmonic distortion (THD) under both normal and fault conditions.

This paper presents the implementation of LoRaWAN-based non-invasive temperature sensor nodes for detecting loss points in distribution networks. The primary challenges involve integrating and calibrating the electronic components, including temperature sensors, LoRaWAN modules, and digital processors, to develop a robust system for analyzing loss points using thermal measurement techniques. The system employs activation by personalization for deploying sensor nodes, which simplifies the activation process and enhances network efficiency. The data collected is securely transmitted to a network server, then analyzed on an application server to identify loss points. This methodology aims to automate the analysis and detection of losses in medium and high voltage distribution networks, offering a technologically advanced, rapidly deployable, and cost-effective solution. Initial results demonstrate the system’s effectiveness in providing accurate and timely detection of loss points, contributing to improved network efficiency and sustainability.

This paper studied the design of a predictive current control strategy with fault tolerance and reactive power minimization applied to a multi-modular topology based on indirect 2-level matrix converters fed by a six-phase generator. The control algorithm of the proposed strategy involves coupled current signals to perform error compensation between the converter modules, aiming to address potential system faults while maintaining reactive power close to zero. The results, obtained through simulation, were evaluated considering each module’s input and output currents and the final load current, as well as reactive power minimization, incorporating the obtained values of total harmonic distortion and mean squared error. The behaviour was analyzed in steady-state and transient conditions, with the system operating nominally and under fault conditions. The results demonstrate the effectiveness and good performance of the proposed strategy with the utilized topology, achieving a satisfactory response to faults through compensation and constant reactive power minimization.

A predictive current control design for a multi-modular indirect matrix converter using a three-level neutral-point clamped for the inverter side is studied. The multi-modular topology is based on two 3-Level Indirect Matrix Converter modules, and the control strategy proposal involves a single model-based predictive current control and the use of a coupled current signal. It is the interaction between the two three-phase output current of each module for error compensation between these, along with the ability to operate in failures. This article shows the results of the simulation in Matlab/Simulink of the 3-level multi-modular indirect matrix converter with coupled control, compared with an independent control for each module of the converter, in order to verify the performance obtained in terms of total harmonic distortion and mean square error. In addition, the analysis was carried out with respect to the behavior in transient, stationary state and with simulated failures for each module. The results obtained support the effectiveness of the control strategy with the proposed topology showing, with the control coupled, a decrease in the mean square error in the current signal of the final load, having a good value of total harmonic distortion and the capacity for optimal operation in the event of failures of the generation or conversion system.

One of the most fundamental and well-studied problems in Tile Self-Assembly is the Unique Assembly Verification (UAV) problem. This algorithmic problem asks whether a given tile system uniquely assembles a specific assembly. The complexity of this problem in the 2-Handed Assembly Model (2HAM) at a constant temperature is a long-standing open problem since the model was introduced. Previously, only membership in the class coNP was known and that the problem is in P if the temperature is one ( $$\tau =1$$ ). The problem is known to be hard for many generalizations of the model, such as allowing one step into the third dimension or allowing the temperature of the system to be a variable, but the most fundamental version has remained open. In this paper, we prove the UAV problem in the 2HAM is hard even with a small constant temperature ( $$\tau = 2$$ ), and finally answer the complexity of this problem (open since 2013). Further, this result proves that UAV in the staged self-assembly model is coNP-complete with a single bin and stage (open since 2007), and that UAV in the q-tile model is also coNP-complete (open since 2004). We reduce from Monotone Planar 3-SAT with Neighboring Variable Pairs, a special case of 3SAT recently proven to be NP-hard. We accompany this reduction with a positive result showing that UAV is solvable in polynomial time with the promise that the given target assembly will have a tree-shaped bond graph, i.e., contains no cycles. We provide a $$\mathcal {O}(n^5)$$ algorithm for UAV on tree-bonded assemblies when the temperature is fixed to 2, and a $$\mathcal {O}(n^5\log \tau )$$ time algorithm when the temperature is part of the input.

We analyze the complexity of two fundamental verification problems within a generalization of the two-handed tile self-assembly model (2HAM) where initial system assemblies are not restricted to be singleton tiles, but may be larger prebuilt assemblies. Within this model we consider the producibility problem, which asks if a given tile system builds, or produces, a given assembly, and the unique assembly verification (UAV) problem, which asks if a given system uniquely produces a given assembly. We show that producibility is NP-complete and UAV is coNP N P -complete even when the initial assembly size and temperature threshold are both bounded by a constant. This is in stark contrast to results in the standard model with singleton input tiles where producibility is in P and UAV is coNP-complete with constant temperature. We further provide preliminary polynomial time results for producibility and UAV in the case of 1-dimensional linear assemblies with pre-built assemblies, as well as extend our results to the abstract Tile Assembly Model (aTAM) with constant-size attachable assemblies.

Preclinical experimentation demands for highly reliable and physiologically-relevant systems capable of recapitulating the complex human physiology. Further technological advances are in great need for improving our understanding about critical biological processes involved in tissue development or cancer progression, and for the discovery and screening of novel pharmacological drugs. Traditional in vitro models, albeit widely employed, fail to reproduce the complexity of the native scenario. Similarly, in vivo animal models poorly mimic the human condition and they are ethically questionable. During the last two decades, a new paradigm in preclinical modelling has emerged aiming to solve the limitations of the previous methods. The combination of advanced tissue engineering, cell biology and nanotechnology, has resulted in the development of cutting-edge microfluidics-based models with an unprecedented ability to recreate the native habitat of cells within a microengineered chip. Among the diverse variety of micro- and bio- fabrication techniques, UV-photolithography and soft lithography are considered the gold-standard methods for the fabrication of microfluidic chips to their simplicity, versatility, and rapid prototyping. In this paper, we describe a protocol for the fabrication of a microfluidic chip by UV-photolithography and replica molding, and an example of its use in cell migration assays.

Staged self-assembly has proven to be a powerful abstract model of self-assembly by modeling laboratory techniques where several nanoscale systems are allowed to assemble separately and then be mixed at a later stage. A fundamental problem in self-assembly is Unique Assembly Verification (UAV), which asks whether a single final assembly is uniquely constructed. This has previously been shown to be Π^{p}₂-hard in staged self-assembly with a constant number of stages, but a more precise complexity classification was left open related to the polynomial hierarchy. Covert Computation was recently introduced as a way to compute a function while hiding the input to that function for self-assembly systems. These Tile Assembly Computers (TACs), in a growth only negative aTAM system, can compute arbitrary circuits, which proves UAV is coNP-hard in that model. Here, we show that the staged assembly model is capable of covert computation using only 3 stages. We then utilize this construction to show UAV with only 3 stages is Π^{p}₂-hard. We then extend this technique to open problems and prove that general staged UAV is PSPACE-complete. Measuring the complexity of n stage UAV, we show Π^{p}_{n - 1}-hardness. We finish by showing a Π^{p}_{n + 1} algorithm to solve n stage UAV leaving only a constant gap between membership and hardness.

Multi-phase wind generation systems are emerging as a promising technology for distributed generation systems. These systems can present unbalanced voltages or phase faults for several reasons. In this paper a modular three-phase direct matrix converter topology is used as conversion stage in a six-phase generation system to supply the desired current to a load. To achieve a reliable performance in the conversion stage, an improved predictive current control is proposed that take advantage of the modularity of the converter to enhance the behavior and to provide the capability to work continuously even under unbalance in the source or during fault operation of the generation system whilst achieving the desired tracking and power quality. The technique is compared against a classical approach to show the benefits of the proposed.

Many models of self-assembly have been shown to be capable of performing computation. Tile Automata was recently introduced combining features of both Celluar Automata and the 2-Handed Model of self-assembly both capable of universal computation. In this work we study the complexity of Tile Automata utilizing features inherited from the two models mentioned above. We first present a construction for simulating Turing Machines that performs both covert and fuel efficient computation. We then explore the capabilities of limited Tile Automata systems such as 1-Dimensional systems (all assemblies are of height 1) and freezing Systems (tiles may not repeat states). Using these results we provide a connection between the problem of finding the largest uniquely producible assembly using n states and the busy beaver problem for non-freezing systems and provide a freezing system capable of uniquely assembling an assembly whose length is exponential in the number of states of the system. We finish by exploring the complexity of the Unique Assembly Verification problem in Tile Automata with different limitations such as freezing and systems without the power of detachment.

Advances in technology have given us the ability to create and manipulate robots for numerous applications at the molecular scale. At this size, fabrication tool limitations motivate the use of simple robots. The individual control of these simple objects can be infeasible. We investigate a model of robot motion planning, based on global external signals, known as the tilt model. Given a board and initial placement of polyominoes, the board may be tilted in any of the 4 cardinal directions, causing all slidable polyominoes to move maximally in the specified direction until blocked. We propose a new hierarchy of shapes and design a single configuration that is strongly universal for any w × h bounded shape within this hierarchy (it can be reconfigured to construct any w × h bounded shape in the hierarchy). This class of shapes constitutes the most general set of buildable shapes in the literature, with most previous work consisting of just the first-level of our hierarchy. We accompany this result with a O(n4 log n)-time algorithm for deciding if a given hole-free shape is a member of the hierarchy. For our second result, we resolve a long-standing open problem within the field: We show that deciding if a given position may be covered by a tile for a given initial board configuration is PSPACEcomplete, even when all movable pieces are 1 × 1 tiles with no glues. We achieve this result by a reduction from Non-deterministic Constraint Logic for a one-player unbounded game.

We investigate the problem of assembling general shapes and patterns in a model in which particles move based on uniform external forces until they encounter an obstacle. In this model, corresponding particles may bond when adjacent with one another. Succinctly, this model considers a 2D grid of “open” and “blocked” spaces, along with a set of slidable polyominoes placed at open locations on the board. The board may be tilted in any of the 4 cardinal directions, causing all slidable polyominoes to move maximally in the specified direction until blocked. By successively applying a sequence of such tilts, along with allowing different polyominoes to stick when adjacent, tilt sequences provide a method to reconfigure an initial board configuration so as to assemble a collection of previous separate polyominoes into a larger shape. While previous work within this model of assembly has focused on designing a specific board configuration for the assembly of a specific given shape, we propose the problem of designing universal configurations that are capable of constructing a large class of shapes and patterns. For these constructions, we present the notions of weak and strong universality which indicate the presence of “excess” polyominoes after the shape is constructed. In particular, for given integers h, w, we show that there exists a weakly universal configuration with O(hw) 1 × 1 slidable particles that can be reconfigured to build any h × w patterned rectangle. We then expand this result to show that there exists a weakly universal configuration that can build any h × w-bounded size connected shape. Following these results, which require an admittedly relaxed assembly definition, we go on to show the existence of a strongly universal configuration (no excess particles) which can assemble any shape within a previously studied “drop” class, while using quadratically less space than previous results. Finally, we include a study of the complexity of deciding if a particle within a configuration may be relocated to another position, and deciding if a given configuration may be transformed into a second given configuration. We show both problems to be PSPACE-complete even when no particles stick to one another and movable particles are restricted to 1 × 1 tiles and a single 2 × 2 polyomino.