Search Results (7)

This work presents the results of a research study focused on the development and evaluation of an algorithmic optimal control framework for energy-efficient operation of screw compressors in smart power systems. The proposed approach is based on the Pontryagin maximum principle (PMP), which enables the synthesis of a mathematically grounded regulator that minimizes the total energy consumption of a nonlinear electromechanical system composed of a screw compressor and a variable-frequency induction motor. Unlike conventional PID controllers, the developed algorithm explicitly incorporates system constraints, nonlinear dynamics, and performance trade-offs into the control law, allowing for improved adaptability and energy-aware operation. Simulation results obtained using MATLAB/Simulink confirm that the PMP-based regulator outperforms classical PID solutions in both transient and steady-state regimes. Experimental tests conducted in accordance with standard energy consumption evaluation methods showed that the proposed PMP-based controller provides a reduction in specific energy consumption of up to 18% under dynamic load conditions compared to a well-tuned basic PID controller, while maintaining high control accuracy, faster settling, and complete suppression of overshoot under external disturbances. The control system demonstrates robustness to parametric uncertainty and load variability, maintaining a statistical pressure error below 0.2%. The regulator’s structure is compatible with real-time execution on industrial programmable logic controllers (PLCs), supporting integration into intelligent automation systems and smart grid infrastructures. The discrete-time PLC implementation of the regulator requires only 10³ arithmetic operations per cycle and less than 10² kB of RAM for state, buffers, and logging, making it suitable for mid-range industrial controllers under 2–10 ms task cycles. Fault-tolerance is ensured via range and rate-of-change checks, residual-based plausibility tests, and safe fallbacks (baseline PID or torque-limited speed hold) in case of sensor faults. Furthermore, the proposed approach lays the groundwork for hybrid extensions combining model-based control with AI-driven optimization and learning mechanisms, including reinforcement learning, surrogate modeling, and digital twins. These enhancements open pathways toward predictive, self-adaptive compressor control with embedded energy optimization. The research outcomes contribute to the broader field of algorithmic control in power electronics, offering a scalable and analytically justified alternative to heuristic and empirical tuning approaches commonly used in industry. The results highlight the potential of advanced control algorithms to enhance the efficiency, stability, and intelligence of energy-intensive components within the context of Industry 4.0 and sustainable energy systems. Full article

The mechanical systems were modeled using various combinations of mass-damper-spring elements to analyze the system dynamics and improve the system stability. Due to the marginal stability property of the mass-damper rectilinear system, a proper control law is required to control the mass position accurately, improve the relative stability, and enhance the dynamical response. In this paper, a mathematical model of the electromechanical system was first derived and analyzed. Next, a digital PID controller was developed based on the root locus technique, and a systematic design procedure is presented in detail. The proposed digital control system was simulated in MATLAB and compared with other control schemes to check their tracking performance and transient response characteristics. In addition, the digital PID control algorithm of the mass-damper rectilinear system was implemented via dSPACE platform to investigate the real-time control system performance and validate the control design methodology. It has been shown that the digital PID controller yields zero percentage overshoot, fast transient response, adequate stability margins, and zero steady-state error. Full article

Real-time Simulation (RTS) is one of the effective means via which to study device level or system level dynamics, such as power converter online testing, evaluation, and control, and power system stability analysis. The RTS -enabled design-chain offers a time -effective, low-cost, and fail-safe development process. As the penetration of renewable energy is becoming higher, the demand in hybrid system real-time simulation becomes imperative, where fast-dynamic device level power converters and slow -dynamic large -scale power systems are simulated at the same time. This paper introduces a novel hybrid real-time simulation architecture based on the central processing unit (CPU) and the field-programmable gate array (FPGA). Compared with the off-the-shelf power system real-time simulation system, it offers both wide time scale simulation and high accuracy. The multi-time scale model can perform electromechanical electromagnetic transient hybrid simulation, which can be applied to the research of power systems penetrated with power converters. In the proposed simulation platform, the communication delay is introduced when different RTS platforms exchange real-time data. The communication delay should be considered in the stability analysis of the grid-connected inverters in a weak grid environment. Based on the virtual impedance characteristic formed by the control loop with and without communication delay, the impedance characteristics are analyzed and inter-simulator delay impacts are revealed in this paper. Theoretical analysis indicates that the communication delay, contrary to expectation, can improve the virtual impedance characteristics of the system. With the same hardware simulation parameters, the grid-converter system is verified on both the Typhoon system alone and the Typhoon-dSPACE-SpaceR hybrid simulation platform. The THD value of grid current in a weak grid environment that works in the Typhoon system is 4.98%, and 2.38% in the Typhoon-dSPACE-SpaceR hybrid simulation platform. This study eventually reveals the fact that the inter-simulation delay creates the illusion that the control system built in the novel hybrid real-time simulation is more stable under weak grid conditions. Full article

Lead Zirconate Titanate (PZT) sensors have become popular in structural health monitoring (SHM) using the electromechanical impedance (EMI) technique for damage identification. The vibrations generated during the casting process in concrete structures substantially impact the conductance signature’s (real part of admittance) magnitude and sensitivity. The concept of smart sensing units (SSU) is presented, composed of a PZT patch, an adhesive layer, and a steel plate. It is embedded in the concrete structure to study the impact of damage since it has high sensitivity to detect any structural changes, resulting in a high electrical conductance signature. The conductance signatures are obtained from the EMI technique at the damage state in the 10–500 kHz high-frequency range. The wave propagation technique proposes implementing the novel embedded SSUs to detect damage in the host structure. The numerical simulation is carried out with COMSOL multiphysics, and the received voltage signal is compared between the damaged and undamaged concrete beam with the applied actuation signal. A five-cycle sine burst modulated by a Hanning window is employed as the transient excitation signal. For numerical investigation, six cases are explored to better understand how the wave travels when a structural discontinuity is accounted for. The changes in the received signal during actuator–receiver mode in the damage state of the host structure are quantified using time of flight (TOF). Furthermore, the numerical studies are carried out by combining the EMI-WP technique, which implies synchronous activation of EMI-based measurements and wave stimulation. The fundamental idea is to implement EMI-WP to improve the effectiveness of SSU patches in detecting both near-field and far-field damage in structures. One SSU is used as an EMI admittance sensor for local damage identification. Meanwhile, the same EMI admittance sensor is used to acquire elastic waves generated by another SSU to monitor damages outside the EMI admittance sensor’s sensing area. Finally, the experimental validation is carried out to verify the proposed methodology. The results show that combining both techniques is an effective SHM method for detecting damage in concrete structures. Full article

Development of control system based on digital twins of physical processes is a promising area of research in the rolling industry. Closed-loop control systems are developed to control the coordinates of two-mass electromechanical systems in order to limit the dynamic loads on the equipment of main rolling lines. These control systems are based on observers (digital shadows) that indirectly detect (reconstruct) the roll speed and the elastic torque of the shaft (spindle) in real time. Notably, observers are required to work fast in order to reconstruct transients attributable to shock (impact) loads. Literature review shows that the known observers, which use complex algorithms to compute coordinates, do not respond fast enough. The paper analyzes the kinematic diagram of Mill 5000, a plate rolling mill. It presents oscillograms that prove that the elastic torque does oscillate as the rolls grip the strip dynamically. The authors hereof have developed an observer that reconstructs the coordinates of the uncontrolled mass (the shaft) and the spindle torque from the parameters of the controlled mass, namely the torque and speed of the motor. The paper further rationalizes an approach that consists of simulating the processes on a model to further directly configure them on the object. The authors analyze the transients of the reconstructed two-mass system coordinates, which are associated with the rolls gripping the strip. The paper compares data against oscillograms recorded on the mill itself. The accuracy is satisfactory. The proposed observer has been used to developed a three-loop automatic speed control system for the uncontrolled mass. Controller configurations are substantiated. The paper shows coordinates obtained by simulation modeling as functions of time. It further presents experiments run on Mill 5000; the conclusions are that the amplitude and oscillations of the elastic torque drop significantly. The paper concludes with recommendations on industrial adoption of the observer and the novel electric drive coordinate control system. Study presented herein substantiates and implements a concept of developing algorithms that solve specific problems and are readily implementable on the existing equipment without need for additional computing devices. The contribution of the paper consists of stating and solving the problem of developing and testing an automatic elastic torque control system for the shaft of a heavy-duty rolling mill. This system has been implemented in the form of algorithms that run in the software of the existing industrial controllers (PLCs). It is simple and performs well. It does not need additional sensors or computers to be implemented, nor does it rely on complex computational algorithms. Such algorithms are based on computational tables that require a priori data on numerous process parameters. In our literature review, we have not come across any industrial implementation of such algorithms on hot-rolling mills. Full article

The dynamics of power systems is often analyzed using real-time simulators. The basic requirements of these simulators are the speed of obtaining the results and their accuracy. Known algorithms (backward Euler or trapezoidal rule) used in real-time simulations force the integration time step to be reduced to obtain the appropriate accuracy, which extends the time of obtaining the results. The acceleration of obtaining the results is achieved by using parallel calculations. The paper presents an algorithm for mathematical modeling of the dynamics of linear electrical systems, which works stably with a relatively large integration time step and with accuracy much better than other algorithms widely described in the literature. The algorithm takes into account the possibility of using parallel calculations. The proposed algorithm combines the advantages of known methods used in the analysis of electrical circuits, such as nodal analysis, multi-terminal electrical component theory, and transient states analysis methods. However, the main advantage over other algorithms is the use of the method based on average voltages in the integration step (AVIS method). The attention was focused on the presentation of the scientifically acceptable general principle offered to mathematical modeling of dynamics of linear electrical systems with parallel computations. However, the evidence of its effective application in the analysis of the dynamics of electric power and electromechanical systems was indicated in the works carried out by the team of authors from the Institute of Electrical Engineering UTP University of Science and Technology in Bydgoszcz (Poland). Full article

A field-programmable gate array (FPGA)-based digital solver for real-time electromechanical transient simulation is designed in this paper. The solving process for a device or sub-network in an electromechanical transient simulation is packaged into the orders in soft function solvers. The orders are reused by soft function solvers that are invoked by microprocessor cores. The data exchange between the microprocessor cores and soft function solvers is enhanced through explicit and implicit channels. The orders of the microprocessor cores are stored in the synchronous dynamic random access memory on the FPGA board, which solves the problem of insufficient storage space for the orders in electromechanical transient simulation. A real-time digital solver for electromechanical transient simulation, whose feasibility is verified by a simulation of part of the power system in East China, is successfully constructed by applying a small number of microprocessor cores and multiple soft function solvers. Full article