Desired Control Research Articles

Tuning PID controller parameters of the DC motor with PSO algorithm

AbstractDirect current (DC) motors have superior features such as operating at different speeds, being affordable and easily controllable. Therefore, DC motors have many uses, such as machine tools and robotic systems in many factories up to the textile industry. The PID controller is one of the most common methods used to control DC motors. PID is a feedback controller with the terms Proportional, Integral, and Derivative. The proper selection of P, I, and D parameters is critical for achieving the desired control in the PID controller. In this study, the transfer function of a DC motor is first obtained, and the speed of the DC motor is controlled by the PID controller using this transfer function. Then, Particle Swarm Optimization (PSO), an optimization method based on swarm intelligence, is used to adjust the P, I, and D parameters. By using the obtained P, I, and D coefficients, the speed of the DC motor is tried to be controlled, and the effect of the filter coefficient on the system output is examined. The performance of the proposed PSO-PID controller with successful results is given in tables and graphics. Control and optimization studies are carried out with MATLAB Simulink.

Moment-Based Reinforcement Learning for Ensemble Control.

Problems involving controlling the collective behavior of a population of structurally similar dynamical systems, the so-called ensemble control, arise in diverse emerging applications and pose a grand challenge in systems science and control engineering. Owing to the severely under-actuated nature and the difficulty of placing large-scale sensor networks, ensemble systems are limited to being actuated and monitored at the population level. Moreover, mathematical models describing the dynamics of ensemble systems are often elusive. Therefore, it is essential to design broadcast controls that excite the entire population in such a way that the heterogeneity in system dynamics is robustly compensated. In this article, we propose a reinforcement learning (RL)-based data-driven control framework incorporating population-level aggregated measurement data to learn a global control signal for steering a dynamic population in the desired manner. In particular, we introduce the notion of ensemble moments induced by aggregated measurements and derive the associated moment system to the original ensemble system. Then, using the moment system, we learn an approximation of optimal value functions and the associated policies in terms of ensemble moments through RL. We illustrate the feasibility and scalability of the proposed moment-based approach via numerical experiments using a population of linear, bilinear, and nonlinear dynamic ensemble systems. We report that the proposed method achieves the desired control objectives of various ensemble control tasks and obtains significantly better averaged-reward when compared with three existing methods.

Control of Desire and Resistance to Torture: Masculinities and Virginity within Marriage in Ælfric’s Lives of Saints

ABSTRACT A commitment to virginity within marriage is far from normative in early medieval England. Yet three of the twenty-six saints' lives curated in one volume by Ælfric have virgin spouses as protagonists. Saints' lives provide an insight into behaviour that is, by definition, extraordinary, they also act as exempla. Thus, married virginity is not easily achievable, but it is of clear interest to Ælfric and his audience. In this article, I will examine the implications of this unusual identity for masculinity through an analysis of the legends of the married virgins Julian and Basilissa, Cecilia and Valerian and Chrysanthus and Daria in Ælfric's Lives of Saints (from this point, I will be collectively refer to them as The Lives of the Virgin Spouses). A virgin marriage can destabilise the process of gender performance through heterosexual desire. The virgin spouses, therefore, have the potential to subvert gender conventions by revealing the possibilities for alternative masculinities or a third gender, by troubling the more established masculinities present in hagiography such as martial or regal identities. Yet my analysis of these texts, through the lens of Douglas Schrock and Michael Schwalbe's theory of manhood acts, demonstrates that this potential is not realised as masculinity remains tied to concepts of dominance and female virginity is subordinated by its links to vulnerability. Schrock and Schwalbe describe how manhood acts can construct a more esteemed masculinity, compensating for perceived deficiencies in non-hegemonic masculinities. I explore how, in The Lives of the Virgin Spouses, manhood reinforces a contrast between masculinity and femininity, such as through alternative depictions of torture and sexual desire. Male virginity becomes centred around autonomy, self-discipline and commitment, producing a venerable identity in opposition to female virginity, which is focused on bodily enclosure. My discussion thus contributes to the understanding of manhood acts, as well as the functioning of masculinity within Old English literature. Virginity within marriage is more than an early-medieval Christian ideal unobtainable to most. Male virginity in hagiography provides new ways of understanding masculinity.

In vitro development and optimization of cell-laden injectable bioprinted gelatin methacryloyl (GelMA) microgels mineralized on the nanoscale

Bone defects may occur in different sizes and shapes due to trauma, infections, and cancer resection. Autografts are still considered the primary treatment choice for bone regeneration. However, they are hard to source and often create donor-site morbidity. Injectable microgels have attracted much attention in tissue engineering and regenerative medicine due to their ability to replace inert implants with a minimally invasive delivery. Here, we developed novel cell-laden bioprinted gelatin methacrylate (GelMA) injectable microgels, with controllable shapes and sizes that can be controllably mineralized on the nanoscale, while stimulating the response of cells embedded within the matrix. The injectable microgels were mineralized using a calcium and phosphate-rich medium that resulted in nanoscale crystalline hydroxyapatite deposition and increased stiffness within the crosslinked matrix of bioprinted GelMA microparticles. Next, we studied the effect of mineralization in osteocytes, a key bone homeostasis regulator. Viability stains showed that osteocytes were maintained at 98 % viability after mineralization with elevated expression of sclerostin in mineralized compared to non-mineralized microgels, showing that mineralization can effectively enhances osteocyte maturation. Based on our findings, bioprinted mineralized GelMA microgels appear to be an efficient material to approximate the bone microarchitecture and composition with desirable control of sample injectability and polymerization. These bone-like bioprinted mineralized biomaterials are exciting platforms for potential minimally invasive translational methods in bone regenerative therapies.

Model-Free Q-Learning for the Tracking Problem of Linear Discrete-Time Systems.

In this article, a model-free Q-learning algorithm is proposed to solve the tracking problem of linear discrete-time systems with completely unknown system dynamics. To eliminate tracking errors, a performance index of the Q-learning approach is formulated, which can transform the tracking problem into a regulation one. Compared with the existing adaptive dynamic programming (ADP) methods and Q-learning approaches, the proposed performance index adds a product term composed of a gain matrix and the reference tracking trajectory to the control input quadratic form. In addition, without requiring any prior knowledge of the dynamics of the original controlled system and command generator, the control policy obtained by the proposed approach can be deduced by an iterative technique relying on the online information of the system state, the control input, and the reference tracking trajectory. In each iteration of the proposed method, the desired control input can be updated by the iterative criteria derived from a precondition of the controlled system and the reference tracking trajectory, which ensures that the obtained control policy can eliminate tracking errors in theory. Moreover, to effectively use less data to obtain the optimal control policy, the off-policy approach is introduced into the proposed algorithm. Finally, the effectiveness of the proposed algorithm is verified by a numerical simulation.

On Torque Vectoring Control: Review and Comparison of State-of-the-Art Approaches

Torque vectoring is a widely known technique to improve vehicle handling and to increase stability in limit conditions. With the advent of electric vehicles, this is becoming a key topic since it is possible to have distributed powertrains, i.e., multiple motors are adopted, in which each motor is controlled separately from the others. Moreover, electric motors deliver the torque required by the controller faster and more precisely than internal combustion engines, active differentials and conventional hydraulic brakes. The state of the art of Direct Yaw Moment Control (DYC) techniques, ranging from classical to modern control theories, are analyzed and discussed in this paper. The aim is to give an overview of the currently available approaches while identifying their drawbacks regarding performances and robustness when dealing with common issues like model uncertainties, external disturbances, friction limit and common state estimation problems. This contribution analyzes all the steps from the lateral dynamics reference generation to the desired control action computation and allocation to the available actuators. In addition, some of the presented control logic is evaluated in a simulation environment for a passenger car. Results of both open-loop and closed-loop maneuvers allow the comparison and clarification of each control strategy’s key advantages.

Energy management of electric vehicle using a new strategy based on slap swarm optimization and differential flatness control

Optimal energy management of electric vehicles using slap swarm optimization and differential flatness control has been proposed. A battery–supercapacitor power system is adopted. Each source is connected in parallel to the DC-bus using DC–DC bidirectional converters and supplies a synchronous reluctance motor (SynRM) based drive. The proposed EMS fundamental forces lie in using a combination of complementary proprieties of two approaches, a Slap Swarm optimization Algorithm and Differential Flatness (DF). With a fast optimization mechanism, the Slap Swarm optimization algorithm allows adapting in real-time conditions the DF gains to optimize the system performances. On its side, DF uses predefined trajectories respecting the physical proprieties of the system, which is a powerful tool to guarantee the dynamic constraints of the sources when ensuring desired robust control proprieties. To check the feasibility and performance of the suggested EMS, comprehensive processor-in-the-loop co-simulations of the electric vehicle were carried out using the C2000 launchxl-f28379d DSP board. The main goal of the proposed EMS is to guarantee the DC-bus stabilization, reducing the DC-bus voltage ripples (Δv = 5 V) and the voltage overshoots 15 V (3.2%), respect the source dynamics, and satisfy the SynRM motor power demand. Furthermore, the algorithm minimizes induced harmonics by the drive (10.49%), reducing the battery current ripple by 17.15A, thereby enhancing the battery lifecycle.

Deep reinforcement learning‐based active mass driver decoupled control framework considering control–structure interaction effects

AbstractControl–structure interaction (CSI) plays a significant role in active control systems. Popular methods incorporate actuator dynamics into an integrated control system to account for CSI, leading to a situation where existing structural control algorithms that ignore CSI cannot be applied directly. To address this issue, this study proposes a deep reinforcement learning (DRL) based active mass driver (AMD) decoupled control framework, in which a structural control algorithm is employed to generate the control force command without consideration of CSI, while a DRL agent is utilized to attenuate the CSI effects of AMD systems and achieve a desired control force. The DRL‐based AMD control framework is verified through a series of numerical experiments. Furthermore, the applicability of the control framework is confirmed in a wind‐excited 76‐story benchmark building. Comprehensive analysis indicates that the proposed control framework can effectively eliminate the CSI effects and apply accurate control force to the structure in various scenarios, which allows for an ideal structural response control.

Biphasic control strategy of polymers and nanoparticles for viscous oil removal and molecular release: Synthesis, mechanism and applications

Responsive Pickering emulsions are an excellent platform to control the interfacial properties of oil–water systems. However, the removal of viscous crude oil from oily waste by external stimuli is still a challenge. Here, a dual-stimuli supramolecular assembly of the polymer and silica particles (PS) was designed to achieve desirable control of oil–water interfaces for viscous oil removal and controlled molecular release. The β-cyclodextrin-based polymer was fabricated through the atom transfer radical polymerization (ATRP) method for the host molecules responsive to UV light and amine-modified silica particles for the guest molecules responsive to pH. Utilizing their responsive properties, the PS system was demonstrated in this study to significantly enhance the oil washing efficiency (from 18.3% to 74.2%). Moreover, as the acidic condition was replaced by CO2 injection, it was further enhanced from 74.2% to 88.5%, which is beneficial to greener remediation and production. The responsive PS assembly was also applied for dye release with a slower or faster release of methyl red by tuning the stimuli (pH & UV light). The molecular mechanism was revealed via the molecular dynamics (MD) simulation, which articulates the interaction and motion of the PS system under various stimulations. More importantly, this novel assembly of the cyclodextrin-based polymer and amine-modified silica particles affords a simple and efficient route to enhance the removal of viscous oil waste and precisely control the molecular release. The findings of the molecular self-assembly in this work offer unique opportunities to integrate functional polymers and particles into the liquid–liquid interface, opening an avenue for applications in Pickering emulsions.

Data-driven design of model-free control for reference model tracking based on an ultra-local model: Application to vehicle yaw rate control

Lateral vehicle dynamics control is important for autonomous driving. This paper presents a data-driven design of model-referenced model-free control (DD-MR-MFC) based on an ultra-local model for vehicle yaw rate control. The characteristics of lateral vehicle dynamics systems depend on vehicle velocities and weights. For this system, fixed proportional–integral–derivative (PID) controllers cannot provide the desired control performance. Additionally, although model-based control can be applied to lateral vehicle dynamics, the modeling process is time-consuming. To efficiently design controllers that can realize the desired performance, we adopt a model-free approach. In this study, the control law of practical MR-MFC is derived by extending the traditional MFC based on an ultra-local model and using a data-driven design method. The MFC approach can be applied to nonlinear systems with few parameters, and the data-driven method provides optimized parameters from single-experiment time-series data without the need for repeated experiments and system model to be controlled. Additionally, the processing cost is considerably low because the controller parameter can be obtained using least-square methods. The effectiveness of the proposed method is verified using a multibody vehicle simulator. The yaw rate tracking performance is examined under different velocities and loads. Results showed that the root-mean-square error of the proposed method is approximately 1/100th of that when using a fixed PID controller optimized using a data-driven method.

Output-constrained fixed-time coordinated control for multi-agent systems with event-triggered and delayed communication

In this study, we propose a fixed-time coordinated controller for high-order multi-agent systems dealing with output constraints and switching digraphs while considering event-triggered and delayed communication. To tackle the scenario where only a subset of agents have direct access to the leader, a novel event-triggered fixed-time observer is first devised. This observer effectively estimates the state of the leader, considering the influence of communication delays. Subsequently, a neural network-based fixed-time controller is formulated under output constraints, utilizing the estimated leader commands to achieve the desired control objectives. Finally, practical experiments are conducted using omni-mecanum-wheeled robots to demonstrate the practical feasibility and superior performance of the theoretical findings. This study contributes significantly by tackling the challenging problem of output-constrained fixed-time coordinated control in event-triggered and delayed communication within switching digraphs. This area has yet to be previously explored.

Research on Political Ethical Alienation in the Space of the Other Starting from Adolf Eichmann

Modern anthropology and spatial politics advocate understanding and studying the other, reflecting on oneself through the other. Great eras demand both theoretical and practical innovation, and political ethics should never be metaphysical in the ivory tower. This article takes the relevant events of Adolf Eichmann, a high-ranking Nazi official during World War II, who indiscriminately massacred numerous Jews, as an example. It reflects and analyzes the breakdown of value rationality and the disregard and trampling of moral ethics under fascist authoritarianism during World War II. Combining relevant behavioral experiments, the study explores the causes of alienation from the perspectives of alienated subjects, motives, and opportunities. This leads to a discussion of solutions to ethical alienation in the process of social development, proposing ideas for overcoming potential political ethical dislocation through emphasis on quality education, balancing social systems and ethical morals, and calling for collective reflection and nurturing a sense of responsibility for others. Maintaining a clear self-awareness under the control of desires in the high-tech era is conducive to avoiding the quagmire of alienation and provides warnings and development ideas for the long-term development of our countrys politics.

CBe4H6: a molecular rotor with a built-in on-off switch.

It is highly challenging to control (stop and resume as needed) molecular rotors because their intramolecular rotations are electronically enabled by delocalized σ bonding, and the desired control needs to be able to destroy and restore such σ bonding, which usually means difficult chemical manipulation (substitution or doping atom). In this work, we report CBe4H6, a molecular rotor that can be controlled independently of chemical manipulation. This molecule exhibited the uninterrupted free rotation of Be and H atoms around the central carbon in first-principles molecular dynamics simulations at high temperatures (600 and 1000 K), but the rotation cannot be witnessed in the simulation at room temperature (298 K). Specifically, when a C-H bond in the CBe4H6 molecule adopts the equatorial configuration at 298 K, it destroys the central delocalized σ bonding and blocks the intramolecular rotation (the rotor is turned "OFF"); when it can adopt the axial configuration at 600 and 1000 K, the central delocalized σ bonding can be restored and the intramolecular rotation can be resumed (the rotor is turned "ON"). Neutral CBe4H6 is thermodynamically favorable and electronically stable, as reflected by a wide HOMO-LUMO gap of 7.99 eV, a high vertical detachment energy of 9.79 eV, and a positive electron affinity of 0.24 eV, so it may be stable enough for the synthesis, not only in the gas phase, but also in the condensed phase.

A Computational Modeling Approach for the Design of Genetic Control Systems that Respond to Transcriptional Activity.

Recent progress in synthetic biology has enabled the design of complex genetic circuits that interface with innate cellular functions, such as gene transcription, and control user-defined outputs. Implementing these genetic networks in mammalian cells, however, is a cumbersome process that requires several steps of optimization and benefits from the use of predictive modeling. Combining deterministic mathematical models with software-based numerical computing platforms allows researchers to quickly design, evaluate, and optimize multiple circuit topologies to establish experimental constraints that generate the desired control systems. In this chapter, we present a systematic approach based on predictive mathematical modeling to guide the design and construction of gene activity-based sensors. This approach enables user-driven circuit optimization through iterations of sensitivity analyses and parameter scans, providing a universal method to engineer sense and respond cells for diverse applications.

Estimated-State Feedback Fuzzy Compensator Design via a Decentralized Approach for Nonlinear-State-Unmeasured Interconnected Descriptor Systems

This paper investigates the decentralized fuzzy control problems for nonlinear-state-unmeasured interconnected descriptor systems (IDSs) that utilize the observer-based-feedback approach and the proportional–derivative feedback control (PDFC) method. First of all, the IDS is represented as interconnected Takagi–Sugeno (T–S) fuzzy subsystems. These subsystems can effectively capture the dynamic behavior of the system through fuzzy rules. For the stability analysis of the system, this paper uses the free-weighing Lyapunov function (FWLF), which allows the designer to set the weight matrix, to achieve the desired control performance and design the controller more easily. Furthermore, the control problem can be transformed into a set of linear matrix inequalities (LMIs) through the Schur complement, which can be solved using convex optimization methods. Simulation results confirm the effectiveness of the proposed method in achieving the desired control objectives and ensuring system stability.

Balancing Fuzzy Control Performance and Reachable-Set-Dependent Event-Triggered Communication.

This work investigates the control design and reachable set estimation problem for T-S fuzzy systems under bounded external disturbances. By designing a fuzzy controller, the reachable set of the closed-loop fuzzy system can be bounded by an ellipsoid that is minimized via two optimization algorithms. When the fuzzy control scheme is implemented under an event-triggered framework, the limited information availability may degrade desired control performance due to only the triggered state being available for the fuzzy controller. To alleviate this problem, a novel reachable-set-dependent event-triggering condition is proposed such that satisfactory control performance can still be ensured by the above fuzzy controller. Meanwhile, the bounding ellipsoid of the reachable set is explicitly given, and a relationship is established between control performance and communication cost under the event-triggered scheme. In addition, under the condition that the reachable set remains within a specified safe area, the communication rate can be reduced while still achieving optimal control performance. The proposed strategies are verified via a simulation example.

(Invited) Ultrafast Electrodeposition of Faceted Li Metal

Electrochemical deposition of metals with precise morphological and chemical control is of fundamental importance to a broad range of electrochemical systems, including energy storage, large scale manufacturing, electronics, and electrocatalysis. For non-reactive metals (e.g. Ni, Pt), electroplating is a commercially established process that gives the desired control of deposition morphology and chemistry. However, deposition of reactive metals (e.g. Li, Na) critical for enabling next-generation batteries is complicated by metal surface corrosion that occurs concurrently with metal deposition, making such electrodeposition processes neither well-understood nor well-controlled. This work highlights the electrodeposition of lithium (Li), a reactive metal anode plagued with uncontrolled dendritic morphologies and surface corrosion, both of which are intimately linked and occur simultaneously. Despite tremendous research efforts to mitigate these issues, common literature descriptions of Li metal deposits (e.g. “chunky”, “pancake”) and their corrosion films (e.g. “strong”, “stable”) are ill-defined and often qualitative, highlighting our incomplete understanding of the deposition process and hindering the practical application of high energy battery chemistries enabled by Li metal. Our work seeks to bridge this critical gap in understanding by solving the fundamental challenge of (1) decoupling simultaneous electrodeposition from surface corrosion of reactive metals and (2) observing their reactive nanoscale interface.

ПІДБІР ОПТИМАЛЬНИХ ЗЕРНОВИХ СКЛАДІВ АСФАЛЬТОБЕТОННИХ СУМІШЕЙ У СЕРЕДОВИЩІ MS EXCEL

Introduction. The composition of the grading of the mineral part of the asphalt mixture significantly affects the properties of road asphalt, namely its strength, roughness, durability, stability, reliability, quality, etc., especially when using secondary industrial waste. The designing of asphalt mixture grading (hereinafter referred to as AM) involves the calculation of its parameters that, among other things, meet the requirements of Tables 6 and 7 of DSTU B V.2.7-119:2011 [1]. Designing the aggregate composition and binder content of an AM that meets the specification requirements is a lengthy trial-and-error procedure, and success in designing an AM largely depends on the designer’s experience. This difficulty can be overcome by the development and implementation of computer software for designing the optimal AM parameters to obtain the desired properties and control them. In general, three main approaches have been proposed to computerize the computations for processing laboratory test results and optimizing the parameters of the AM: 1) Excel spreadsheets for performing a volumetric analysis of AM (Asphalt Mix Design Tools), for example, according to the methodology of Part 5 of the manual [3]; 2) optimization of the process of designing the optimal AM using artificial neural networks (hereinafter referred to as ANN) and genetic algorithm (hereinafter referred to as GA), for example, [4];

Dynamic event‐triggered asynchronous security load frequency control for semi‐Markov jump multi‐area power systems against deception attacks

AbstractThis paper focuses on the issue of dynamic event‐triggered (DET) asynchronous security load frequency control (LFC) for uncertain semi‐Markov jump interconnected multi‐area power systems (IMAPSs). Initially, the semi‐Markov process which in the presence of partially unknown transition rates (TRs) is exactly introduced to model the switching behaviors of the IMAPSs. Subsequently, the DET mechanism is scheduled to alleviate the transmission frequency and guarantee the desired control performance. Furthermore, the probabilistic deception attacks are taken into consideration, which is much more apt for the practical engineering background. Additionally, a hidden Markov model (HMM) is borrowed to depict the modes asynchronous phenomenon between the security controller and the semi‐Markov jump IMAPSs. Afterwards, on the basis of Lyapunov‐Krasovskii functional method and stochastic analysis technique, sufficient conditions with two cases are derived in the form of linear matrix inequalities (LMIs) to guarantee the stochastic stability with an performance of the semi‐Markov jump IMAPSs. Ultimately, a numerical example is exhibited to verify the solvability and practicability of the proposed control strategy.

Optimal tracking control of an Autonomous Underwater Vehicle: A PMP approach

This paper addresses the optimal tracking control problem of an Autonomous Underwater Vehicle (AUV) using Pontryagin’s Minimum Principle (PMP). The formulation uses a choice of Hamiltonian function using the desired control objective with AUV dynamics acting as dynamic constraints. We first develop PMP based on AUV kinematics and then extend it to the dynamics to arrive at optimal thrusts and moments. Necessary conditions for optimality are derived for both the models using PMP, which results in optimal trajectories that simultaneously minimize the tracking error as well as the control cost, thereby arriving at energy optimality. It was observed that the adjoint variables (costates) are indeed the momenta in the inertial and body-fixed frames. At the kinematic level, this forms a stable solution. The developed methodology is applied to both 2D and 3D AUV model with disturbances due to inputs and ocean currents. Numerical simulations are carried out with the derived control laws for a given trajectory tracking target. Quantitative evaluation of the performance and comparison of the controller is done using Mean Square Error(MSE) and Total Variation(TV) measures. The proposed control laws are found to achieve the desired control objectives.