Stable Control System Research Articles

Development of intelligent mechatronic motion module of mobile industrial robot

Modern industry is inextricably linked with mobile industrial robots, which plays a key role in production processes and warehouse logistics. The intensive introduction of mobile industrial robots has increased the need to improve the energy efficiency of robotic installations due to their significant impact on overall production costs. At the same time, there is a pressing need to reduce the time required to develop and implement mobile industrial robots. This leads to the need to improve and optimize the properties of all components that make up a mobile industrial robot. Currently, electric drives are most widely used in mobile industrial robots. Research shows that the use of modern high-tech solutions in the construction of electric drive control systems can improve the energy efficiency of mobile industrial robots. In turn, the introduction of an intelligent component into mechatronic motion modules allows to reduce the time required for their construction and integration into mobile industrial robots. The purpose of the study is to increase the energy efficiency of an intelligent mechatronic motion module by using a multi-motor electric drive in the movement system of a mobile industrial robot and to develop a stable and energy-efficient intelligent automatic control system based on a neural network, taking into account the nonlinear properties of the control object under conditions of uncertainty.

The Method of Synthesis of a Stable Closed-Loop Object Control System with Limiters

The Method of Synthesis of a Stable Closed-Loop Object Control System with Limiters

Improved Adaptive Feedforward Controller Based on Internal Model Principle with Disturbance Observer for Laser-Beam Steering Systems

This study presents an effective control algorithm to improve the robustness of fast steering mirror (FSM)-based laser-beam steering systems against dynamic disturbances, such as repetitive disturbances resulting from operating conditions. A stable control system must be able to maintain the required high-precision control, even when dynamic disturbances affect the FSM system. In this study, an improved control method is proposed using an internal model principle (IMP)-based nonlinear controller with a disturbance observer (DOB) for the FSM system. This IMP-based controller with DOB can attenuate the residual control-error signal under dynamic disturbance conditions.

Machine learning assisted prediction for hydrogen production of advanced photovoltaic technologies

The photovoltaic (PV) water electrolysis method currently stands as the most promising approach for green hydrogen production. The rapid iteration of photovoltaic technologies has significantly affected on the technical and economic evaluation for photovoltaic hydrogen production. In this work, the photovoltaic hydrogen production of three most advanced silicon photovoltaic technologies is systematically compared for the first time under the climatic conditions of the Kucha region. All-weather stable hydrogen production control system with optimal charging and discharging strategies is constructed to realize stable and efficient hydrogen energy production. Seven machine learning (ML) algorithms are used to forecast the performance in power generation and hydrogen production of a 100 ​MW photovoltaic hydrogen production and energy storage (PH-S) system throughout its operational life. The long short-term memory (LSTM) algorithm exhibits the best performance, achieving mean absolute error (MAE) of 0.0415, root mean square error (RMSE) of 0.0891, and coefficient of determination (R2) of 0.8402. In terms of cost-effectiveness, heterojunction with intrinsic thin layer (HJT) PV technology achieves the lowest levelized cost of electricity (LCOE) and hydrogen (LCOH) at 0.025 $/kWh and 6.95 $/kg, respectively. According to the sensitivity analysis, when the cost of proton exchange membrane electrolysis (PEMEC) reduced 50%, the LCOH for PH-S system decreased 21.40%. This study provides valuable insights for the practical implementation of large-scale photovoltaic hydrogen production and cost reduction in PH-S systems.

Real-Time EtherCAT-Based Control Architecture for Electro-Hydraulic Humanoid

Electro-hydraulic actuators have witnessed significant development over recent years due to their remarkable abilities to perform complex and dynamic movements. Integrating such an actuator in humanoids is highly beneficial, leading to a humanoid capable of performing complex tasks requiring high force. This highlights the importance of safety, especially since high power output and safe interaction seem to be contradictory; the greater the robot’s ability to generate high dynamic movements, the more difficult it is to achieve safety, as this requires managing a large amount of motor energy before, during, and after the collision. No matter what technology or algorithm is used to achieve safety, none can be implemented without a stable control system. Hence, one of the main parameters remains the quality and reliability of the robot’s control architecture through handling a huge amount of data without system failure. This paper addresses the development of a stable control architecture that ensures, in later stages, that the safety algorithm is implemented correctly. The optimum control architecture to utilize and ensure the maximum benefit of electro-hydraulic actuators in humanoid robots is one of the important subjects in this field. For a stable and safe functioning of the humanoid, the development of the control architecture and the communication between the different components should adhere to some requirements such as stability, robustness, speed, and reduced complexity, ensuring the easy addition of numerous components. This paper presents the developed control architecture for an underdeveloped electro-hydraulic actuated humanoid. The proposed solution has the advantage of being a distributed, real-time, open-source, modular, and adaptable control architecture, enabling simple integration of numerous sensors and actuators to emulate human actions and safely interact with them. The contribution of this paper is an enhancement of the updated rate compared to other humanoids by 20% and by 40 % in the latency of the master. The results demonstrate the potential of using EtherCAT fieldbus and open-source software to develop a stable robot control architecture capable of integrating safety and security algorithms in later stages.

New Findings in the Stability Analysis of PI-state Controlled Systems with Actuator Saturation

In this paper, a simple, generally valid stability proof for an anti-windup method for PI-state controlled systems is presented, with which it is possible to directly conclude the stability of the PI-state controlled system from a stable P-state controlled system with constraints in the manipulated variables, i.e. without having to perform a separate stability investigation of the anti-windup measures. The technique presented is based on the system description by means of state equations and Lyapunov's Direct Method using quadratic Lyapunov functions. Furthermore, the PI-state controller is designed in such a way that it provides the same command response as the P-state controller, for which a stability statement is already available. Both continuous-time and discrete-time systems are considered, which, apart from the saturation of the manipulated variables, show linear, time-invariant behavior. In addition, a general stability proof is given for discrete-time systems, which makes it possible to establish stable anti-windup methods for P- and PI-state controlled systems, which contain dead time elements in the path of the manipulated variables, without having to carry out separate stability investigations for them. For this purpose, the state controller design for the system with dead time elements in the manipulated variable paths is based on the principle that the same characteristics of the control behavior should be achieved as for the system without such dead time elements, but delayed by the dead time. The effectiveness of the presented methods is illustrated by an example from the field of electrical drives.

CONSTRUCTION OF A SET OF DIFFERENTIAL EQUATIONS SYSTEMSAND STABILITY IN THE VICINITY OF A PROGRAM MANIFOLD

The problem of constructing a entire set of differential equation systems for a given program manifold is addressed. Necessary and sufficient conditions have been compiled to ensure that the program manifold is integral to the systems being developed. These conditions form a rectangular linear algebraic system in relation to the required functions. Using the property of a rectangular matrix, the set of differential equation systems was constructed. Additionally, the problem of designing indirect automatic control systems with rigid feedback is explored. Since the given program is not always executed perfectly due to initial or ongoing disturbances, it is reasonable to require stability of the program manifold with respect to a certain function. This leads to the analysis of the stability of the system of equations in relation to the given program manifold. Through the construction of Lyapunov functions for the system in canonical form, sufficient conditions for the absolute stability of the program manifold are derived. These results can be applied to the design of stable automatic indirect control systems.

On the Global Stability of Nonlinear Hurwitz Control Systems

The problem of designing nonlinear control systems by the algebraic polynomial-matrix method using quasilinear models is considered. The quasilinear models of nonlinear plants are easily created on the basis of their nonlinear equations in the Cauchy form. To create these models only the differentiability of the plants nonlinearities is required. The solution to the design problem of the nonlinear Hurwitz control systems using the algebraic polynomial-matrix method is available if the quasilinear model of the plant is controllable. The design with application of this method consists of creating the quasilinear model of the nonlinear plant, generating several polynomials, composing and solving a system of linear algebraic equations. The theorem about the global stability of the equilibrium of the nonlinear systems, represented in the quasilinear model, is proved by the method of Lyapunov functions. The numerical examples of the design of nonlinear Hurwitz control systems are given. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is concerned with the creation of stable nonlinear control systems with nonlinear elements since the linear systems can’t fulfill the quality requirements demanded from modern control systems. Additionally, the known design methods of nonlinear systems, such as the input-state feedback linearization, backstepping, passivity and others, require the transformation of the original nonlinear equations of the plant into some special form. These transformations are often very difficult to find and to execute. A new algebraic polynomial-matrix design method of the nonlinear control systems using the quasilinear models of nonlinear plants is proposed in the article. This method can be applied if the nonlinearities of the plant are differentiable, and the quasilinear model of the plant is controllable. The theorem about global stability of the equilibrium is proved for the systems designed with this approach. The quasilinear models are easily created on the basis of the original equations in the Cauchy form for a given nonlinear plant. The algebraic polynomial-matrix design method is very simple: the quasilinear model is created; several polynomials are calculated with the use of this model and the linear algebraic equations system is composed. The solution of this system allows us to write down the expression which defines the control law as a nonlinear function of the plant’s state variables. This system will be globally or locally stable if the conditions of the theorem or the corollaries, proved in this article, are satisfied. The numerical examples illustrate the application of the suggested approach to the design of nonlinear Hurwitz control systems for the nonlinear plants. The main advantages of this approach: the quasilinear models are created quite easily; the nonlinear control law is found as a solution to the system of linear equations. The results can be applied to the creation of nonlinear control systems of nonlinear plants in many industries: shipbuilding, aircraft construction, automobile construction, agriculture and many others.

Learning the Optimal Energy-based Control Strategy for Port-Hamiltonian Systems

This paper describes a synthesis and tuning procedure of discrete-time, energy-based regulators for port-Hamiltonian systems. Based on a discrete-time approximation of the plant, the control system is designed within the energy-shaping plus damping injection paradigm. This approach guarantees asymptotic stability, but it is not able “as is” to meet other requirements, such as task performance optimisation. The contribution is integrating the power of artificial neural networks as parametric function approximators and passivity-based control to enhance the performance of an asymptotically stable controlled system. The idea is to employ artificial neural networks that are optimally shaped to enhance the performances during task execution through the solution of an optimisation problem.

Development of Adaptive Control System for Aerial Vehicles

This article represents and compares two control systems for a vertical takeoff and landing (VTOL) unmanned aerial vehicle (UAV): a sliding proportional–integral–derivative (PID) controller and an adaptive L1 controller. The goal is to design a high-performing and stable control system for a specific VTOL drone. The mathematical model of the unique VTOL drone is presented as a control object. The sliding PID and adaptive L1 controllers are then developed and simulated, and their performance is compared. Simulation results demonstrate that both control systems achieve stable and accurate flight of the VTOL drone, but the adaptive L1 controller outperforms the sliding PID controller in terms of robustness and adaptation to changing conditions. This research contributes to ongoing work on adaptive control systems for VTOL UAVs and highlights the potential benefits of using L1 adaptive control for this application.

ℋ∞ robust control of discrete‐time systems based on new linear matrix inequality formulations and evolutionary optimization

AbstractThis study presents novel formulations for robust state‐feedback control synthesis for discrete‐time linear time‐invariant systems based on linear matrix inequalities. The proposed formulations require searching for two adjustment matrices. The synthesis formulations include other formulations from the literature as particular cases according to specific values of the adjustment matrices. We propose the application of evolutionary optimization to determine the optimal values of these two adjustment matrices. One approach to obtaining a single‐step formulation for static output‐feedback control synthesis is to transform a state‐feedback control synthesis formulation via the simple change of variables. The alteration of variables considered in this study requires an adjustment matrix. The adjustment matrix influences the performance of the resulting controller or the existence of a feasible solution to the problem. Here, we also propose the application of evolutionary optimization to determine the optimal value of this adjustment matrix and the two adjustment matrices of the proposed formulations to obtain the optimal robust control system. Case studies verify that despite the increased complexity, the proposed formulations and the method required to tune them may be indispensable in achieving a robustly stable control system or an enhanced performance for more intricate problems.

Analysis of energy consumption of tobacco drying process based on industrial big data

To promote green upgrading, energy conservation, and consumption reduction in the tobacco manufacturing process, the process relationship between parameters of drying and the thermal energy consumption is qualitatively and quantitatively studied by using statistical analysis methods such as interpretable machine learning (RF, Extra-Trees, XGBoost, and LightGBM) and regression analysis. At the same time, the key indicators of energy saving and consumption reduction are concerned with various mathematical models. The thermal energy consumption during drying is mainly affected by the main steam temperature generated by the power workshop. 145 ∼ 275 MJ/h energy (for every 2 °C reduction in mainstream temperature) are saved in production based on main steam temperature regulation. Therefore, stable high-temperature steam and control systems are essential for green upgrades. By regulating the process parameters of other equipment, an energy-saving effect of 2.1 ∼ 2.2% (main steam temperature is 184 ∼ 188 °C) can be further achieved, which is about 81.9 ∼ 90.2 MJ/h. This research provides an improved guidance for green, energy-saving, and intelligent processing of tobacco manufacturing.

Ensuring the thermal regime of spacecraft structures

The main requirement for the smooth operation of the spacecraft is its stable thermal regime. A particularly difficult task is to ensure a stable temperature control system of the device, taking into account strict restrictions on energy and mass costs for temperature control devices. These tasks need to be solved at every stage of the creation of satellites. At each stage, thermal calculations are carried out with the choice of optimal thermophysical parameters. This amount of work is about a tenth of all work with the satellite. The need for theoretical and experimental refinement of calculation methods is an urgent task that will significantly reduce the material and time costs of designing, testing and fine-tuning the device. Therefore, the calculation and analysis of the thermal regimes of spacecraft is an important stage in the design of satellites. Ground thermal vacuum tests are very costly, both in time and financially. The essence of the concept is to conduct only stationary thermal modes under conditions of maximum and minimum thermal loads on the satellite as a whole and its individual external elements, followed by ensuring convergence of test results with calculated results. And the confirmation of intermediate requirements to ensure the specified thermal conditions is carried out by calculation. The article considers the tasks of ensuring the thermal regime of spacecraft structures. Classification of devices used to ensure the thermal regime. Ground-based testing of the thermal regime of communication satellites during thermal vacuum tests. Ensuring the thermal regime of the communication spacecraft during ground-based electrical tests. Thermal regime of spacecraft structures during transportation from the manufacturer to the technical position.

Establishment of new convenient two-line system for hybrid production by targeting mutation of OPR3 in allopolyploid Brassica napus

Abstract The two-line pollination control system, which usually depends on the utilization of thermosensitive or photoperiod genic male-sterile lines, has been widely used in various crops. However, this system is susceptible to instability issues caused by uncontrollable weather fluctuations. A stable and handy two-line pollination control system is highly desirable in many crop species for heterosis exploitation. Oxophytodienoic acid reductase 3 (OPR3) was proven to be involved in jasmonate biosynthesis. In the present study, CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeat) was utilized to mutate two OPR3 homologs in Brassica napus. After two OPR3 homologs were simultaneously mutated, mutants exhibited complete male sterility, and fertility could be easily restored by exogenous MeJA treatment. Hybrids produced from crosses between the opr3 sterile lines and normal varieties exhibited heterosis. This new two-line system based on OPR3 mutation provides higher stability and convenience than traditional systems. By using exogenous MeJA treatment to restore fertility, the system enables more precise control of male fertility transition, which has great potential to significantly contribute to the maneuverable production of hybrid seeds in rapeseed as well as other Brassica species crops.

Modified Differential Evolution Algorithm for Governing Virtual Inertia of an Isolated Microgrid Integrating Electric Vehicles

In modern power systems, there is a greater penetration of renewable sources, resulting in the expansion of microgrid. By implementing RES instead of conventional synchronous machines, the system’s overall inertia is significantly reduced. Modern and future power systems must reduce system inertia and keep the frequency at its nominal value since frequency oscillation impacts on the functionality, stability, and resilience of the system. Therefore, creating a stable, scalable, and reliable virtual inertia control system is crucial to effectively minimize the deviations during significant contingencies. Consequently, taking into account the probable issues, the foremost objective of this research work is to improve the dynamic security of an island microgrid through the implementation of a frequency control concept based on virtual inertia control. In the research study, the proposed microgrid system comprises of photovoltaics, wind-generating units, thermal power units, storage units, electric vehicles (EVs), and loads. A cascaded PIDFN controller is optimally designed using a novel metaheuristic modified differential evolution (MDE) algorithm that regulates the frequency based on virtual inertia control. In the MATLAB®/SIMULINK environment, various operating situations such as load variations, RES, and EVs disconnection are investigated, and the performance of the VIC-based MDE controller was compared to that of other controllers based on evolutionary optimization algorithms such as DE and TLBO. The results validate that the recommended virtual inertia control strategy enhances the reliability of the system.

Application of Model-based Deep Reinforcement Learning Framework to Thermal Power Plant Operation Considering Performance Change

In recent years, there have been increasing expectations for the development of advanced plant operational support systems that can automate complex tasks and autonomouslyoptimize operational procedures in thermal power plants. The performance of the equipment changes during operation and maintenance; hence, it is necessary to adjust the operating process to satisfy the operational constraints. In this study, we investigated a framework based on model-based deep reinforcement learning for acquiring control methods that are robust to changes in equipment performance using a digital twin model. A case study of the operational planning of a thermal power plant was presented and it was demonstrated that a stable control system can be constructed even when plant characteristics are changing.

Stable Fiber-illumination for Extremely Precise Radial Velocities with NEID

NEID is a high-resolution red–optical precision radial velocity (RV) spectrograph recently commissioned at the WIYN 3.5 m telescope at Kitt Peak National Observatory, Arizona, USA. NEID has an extremely stable environmental control system, and spans a wavelength range of 380–930 nm with two observing modes: a High Resolution mode at R ∼ 112,000 for maximum RV precision, and a High Efficiency mode at R ∼ 72,000 for faint targets. In this paper we present a detailed description of the components of NEID’s optical fiber feed, which include the instrument, exposure meter, calibration system, and telescope fibers. Many parts of the optical fiber feed can lead to uncalibratable RV errors, which cannot be corrected for using a stable wavelength reference source. We show how these errors directly cascade down to performance requirements on the fiber feed and the scrambling system. We detail the design, assembly, and testing of each component. Designed and built from the bottom-up with a single-visit instrument precision requirement of 27 cm s−1, close attention is paid to the error contribution from each NEID subsystem. Finally, we include the lab and on-sky tests performed during instrument commissioning to test the illumination stability, and discuss the path to achieving the instrumental stability required to search for a true Earth twin around a solar-type star.

Regions of robust relative stability for PI controllers and LTI plants with unstructured multiplicative uncertainty: A second-order-based example

This example-oriented article addresses the computation of regions of all robustly relatively stabilizing Proportional-Integral (PI) controllers under various robust stability margins α for Linear Time-Invariant (LTI) plants with unstructured multiplicative uncertainty, where the plant model with multiplicative uncertainty is built on the basis of the second-order plant with three uncertain parameters. The applied graphical method, adopted from the authors’ previous work, is grounded in finding the contour that is linked to the pairs of P–I coefficients marginally fulfilling the condition of robust relative stability expressed using the H∞ norm. The illustrative example in the current article emphasizes that the technique itself for plotting the boundary contour of robust relative stability needs to be combined with the precondition of the nominally stable feedback control system and with the line for which the integral parameter equals zero in order to get the final robust relative stability regions. The calculations of the robust relative stability regions for various robust stability margins α are followed by the demonstration of the control behavior for two selected controllers applied to a set of members from the family of plants.

Stability of the program manifold of automatic indirect control systems taking into account the external load

The problems of stability system that arises in the construction of different automatic systems of indirect control are considered. It is known that a given program is not always exactly performed, since there are always initial, constantly acting perturbations.&#x0D; Therefore, it is also reasonable to require the stability of the program manifold itself with respect to some function. In the first part, the stability being investigated of automatic indirect control systems with rigid and tachometric feedback. Necessary and sufficient conditions for the absolute stability of a program manifold are established separately. In the second part, the automatic systems of indirect control taking into account the external load are considered. The equations of the hydraulic actuator, taking into account the action of an external load, are presented in a convenient form for research. Then it reduces to studying the stability of the system of equations with respect to a given program manifold. By constructing LyapunovВ’s functions for the system in canonical form, sufficient conditions are obtained for the absolute stability of the program manifold. The results obtained can be used in the construction of stable automatic indirect control systems.

Virtual Inertia Control of Isolated Microgrids Using an NN-Based VFOPID Controller

Reduction in system inertia and maintaining the frequency at the nominal value is a staple of today's and future power systems since their operation, stability, and resiliency are degraded by frequency oscillation and cascading failures. Consequently, designing a stable, scalable, and robust virtual inertia control system is highly relevant to skillfully diminishing the deviations during major contingencies. Therefore, considering the potential problems in predesigned nonflexible control systems with offline tuning techniques, we propose a variable fractional-order PID controller for virtual inertia control applications, which is tuned online using a modified neural network-based algorithm. The new proposed tuner algorithm is trained using a deep reinforcement learning strategy with a simplified deep deterministic policy gradient, which considers microgrid uncertainties. Compared with existing methods, all the tuning knobs of the discrete type and fully tunable variable FOPID controller (for both gain and order) can be captured based on the proposed hybrid algorithm, which inherits features from both classical and advanced techniques. To demonstrate the effectiveness of the training of the proposed controller, a comparative analysis with the standard FOPID and PID controllers is given under three different scenarios with a smooth (dis)connection of renewable energy sources and loads.