Control Design Approach Research Articles

Adaptive robust control for fuzzy underactuated mechanical systems: A Stackelberg game-theoretic optimization approach

This article proposes a Stackelberg game-theoretic optimization approach for adaptive robust controller design of fuzzy underactuated mechanical systems (UMSs). As a commonly encountered challenge, several factors render it difficult to further improve the control performance of these UMSs, such as the coupling effects and nonlinearities resulting from the underactuated structure. Meanwhile, various sources of unexpected time-varying uncertainties can further add to the difficulty in the controller design procedure pipeline. To overcome the above-mentioned issues and further enhance the system performance, a dual-parameter optimization framework is presented here for adaptive robust controller design, leveraging fuzzy set theory and Stackelberg game. In this development, the time-varying uncertainty is characterized via suitable membership functions; and thus the appropriate fuzzy UMS is established. Then, an adaptive robust controller with a leakage-type adaptation law is presented to tackle the uncertainty appropriately. To further improve the system performance considering the trade-off among the transient performance; the steady-state performance; and the control cost; a Stackelberg game-based dual-parameter optimization method is proposed to determine the Stackelberg strategy. It is rigorously proved in the developments here that the proposed controller design and parameters optimization method guarantees the desired deterministic system performance, i.e., uniform boundedness (UB) and uniform ultimate boundedness (UUB). Moreover, a series of numerical simulations based on a flywheel inverted pendulum (FIP) are performed, which illustrate the effectiveness and superiority of the proposed method.

Anti-biofilm properties of clover honey against <i>Candida albicans</i>

Candida albicans grows rapidly when the microflora becomes imbalanced due to a variety of factors. Its ability to infect a host is aided by its virulence factors, such as biofilm. This study aimed to evaluate the activity of clover honey in inhibiting and degrading the biofilm formation of C. albicans in vitro. This study used a true experimental design with an in vitro post-test-only control group design approach. The microtiter plate assay was used to grow planktonic cells and biofilm. This method was carried out to obtain the Optical Density (OD) value for each test, measured by a Microplate Reader. Cell viability was measured using the MTS Assay kit, the biofilm matrix was measured using the Crystal Violet Assay, and the morphology of C. albicans biofilms was observed by scanning electron microscopy (SEM). Probit and One-way ANOVA tests were applied to determine the MIC50 of both planktonic and biofilm, as well as statistical analysis. The results showed that clover honey exerted inhibitory activity against C. albicans planktonic cells at a MIC50value of 31.60% w/v. At the highest concentration, clover honey exhibited antibiofilm activity by lowering the extracellular matrix and viability of C. albicans cells by 64.59% and 72.09%, respectively. Based on SEM observation, clover honey changed the cell morphology of C. albicans and reduced the thickness of the biofilm. Overall, our findings concluded that clover honey exhibited antifungal properties against C. albicans by inhibiting biofilm formation and degrading mature biofilm.

Integrated Control Design for a Partially Turboelectric Aircraft Propulsion System

Abstract Electrified Aircraft Propulsion (EAP) holds great potential for reducing aviation emissions and fuel burn. A variety of EAP architectures have been proposed including partially turbo-electric configurations that combine turbofan engines with motor-driven propulsors. Such architectures exhibit coupling between subsystems and thus require an integrated control solution. To address this need, this paper presents an integrated control design strategy for a commercial single-aisle partially turbo-electric aircraft concept consisting of two wing-mounted turbofan engines and an electric motor driven tailfan propulsor. Within this architecture the turbofans serve the dual purpose of generating thrust and supplying mechanical offtake power used to generate electricity for the tailfan motor. The propulsion control system is tasked with coordinating turbofan and tailfan operation under both steady-state and transient scenarios. The paper introduces a linear state-space representation of the architecture reflecting the coupling between the turbofan and tailfan subsystems along with loop transfer functions reflecting open- and closed-loop system dynamics. Also discussed is an applied strategy for scheduling the tailfan setpoint command based on the average sensed fan speed of the two turbofans. This approach ensures synchronized operation of the turbofan and tailfan subsystems while also allowing the turbofan fuel control design to be simplified. Performance of the integrated control design is assessed through a real-time hardware-in-the-loop test conducted at the NASA Electric Aircraft Testbed. During this test a scaled version of the electrical system and turbomachinery shaft dynamics were implemented in electrical machine hardware and evaluated under closed-loop control. Results from this facility test are presented to illustrate the efficacy of the applied integrated control design approach under steady-state and transient scenarios including a full-flight mission profile.

Linear Parameter-Varying Polytopic Modeling and Control Design for Guided Projectiles

In this paper, a linear parameter varying (LPV) modeling and control design approach is applied to a new class of guided projectiles, aiming to exploit the advantages of the LPV framework in terms of guaranteed stability and performance. The investigated concept consists of a planar symmetric 155 mm fin-stabilized projectile equipped with a reduced amount of control actuators and characterized by a predominantly unstable behavior across the analyzed flight envelope. A dedicated modeling procedure allows reformulating the nonlinear projectile dynamics as a LPV polytopic system, employed for the controller design. The procedure intends to reduce the computational complexity and the conservativeness affecting the overall controller synthesis. A trajectory-tracking simulation scenario is performed in a realistic simulator environment to assess the performance of the resulting LPV polytopic autopilot across the entire flight envelope.

Identification for Feedforward Control of Wiener Systems

This paper presents an identification approach for feedforward controller design dedicated to nonlinear systems when their structure is known. We propose a model-based approach, leveraging Block-Oriented models, which allows a fast identification of the system when its structure is known. The controller is then designed based on the identified model using a criterion close to traditional identification criteria. Additionally, a costless iterative model identification and controller design approach is also proposed to improve the performance of the controller if necessary. The effectiveness of the approach is demonstrated through the design of a feedforward controller for a Wiener system.

Active Disturbance Rejection Control for 3D Crane Systems

Active Disturbance Rejection Control (ADRC) is a data-driven algorithm that offers a promising approach for robust control design. This paper investigates the effectiveness of first-order and second-order ADRC for 3D cranes. To compare the results fairly and reduce the heuristics in parameter tuning, the ADRC parameters were optimally computed via the African Vultures Optimization Algorithm. Both controllers based on ADRC are validated using experiments on a 3D crane laboratory system and their design and performance evaluation are done by minimizing the sum of squared errors. The results demonstrate the robustness of the ADRCs. This comparative analysis highlights the advantages and limitations of both control strategies, providing valuable insights for selecting the appropriate ADRC order for specific applications.

A Practical Design Approach for Complex Path Tracking Control of a Tailless Fixed-Wing Unmanned Aerial Vehicle With a Single Pair of Elevons

A Practical Design Approach for Complex Path Tracking Control of a Tailless Fixed-Wing Unmanned Aerial Vehicle With a Single Pair of Elevons

A unified design approach for control integrating processes with time delay.

The article presents a unified control system designing scheme to obtain enhanced performance for processes including integrator and dead time. A simple control structure including two controllers is proposed. Servo performance and disturbance rejection performance can be adjusted independently by introducing a desired transfer function model in the control structure. Servo controller is designed according to the direct synthesis principle and disturbance rejection controller is derived adopting the internal model control (IMC) theory. Simulations have been conducted on four kinds of integrating plants with dead time. The simulation results exhibit that noteworthy enhancement can be achieved by the presented scheme in comparation with the other methods even though there are perturbed dynamics.

Enhancing Stability and Performance of DC Microgrid: A Coordinated Impedance Reshaping Controller Design Approach

Enhancing Stability and Performance of DC Microgrid: A Coordinated Impedance Reshaping Controller Design Approach

Gain Scheduled PI controller design using Multi-Objective Reinforcement Learning

Gain scheduling, a widely adopted control design approach, performs tasks by decomposing into sub-problems. It has found successful applications across diverse fields, including aerospace and industrial process control (Leith and Leithead (2000)). Reinforcement Learning (RL) has become increasingly significant in process control applications, thanks to the advancement of sophisticated algorithms and the rise in computational speeds. An attempt has been made to enhance the performance of a Proportional-Integral (PI) controller by integrating the benefits of both gain scheduling and RL. The manuscript focuses on designing a Gain Scheduled PI controller using Multi-Objective RL (GS-MORL). Proposing the training of multiple RL-based PI controllers with distinct objectives with customized reward functions to derive tuning parameters for each goal. The switching between these parameter sets is facilitated by a gain schedule variable. The controller parameters are adjusted based on the error between actual and desired responses. The aim is to enhance overall performance across various performance indices, including the integral of absolute error and time response specifications. The performance improvement from the proposed work has been demonstrated using two simulation case studies, one involving an underdamped second-order system and an integrating type steam turbine system. Comparative analysis against existing literature revealed superior performance across all indices.

Iterative PID Control Design Approach for Maximizing Proportional Gain

Iterative PID Control Design Approach for Maximizing Proportional Gain

Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems.

In this study, we investigate the event-triggering time-varying trajectory bipartite formation tracking problem for a class of unknown nonaffine nonlinear discrete-time multiagent systems (MASs). We first obtain an equivalent linear data model with a dynamic parameter of each agent by employing the pseudo-partial-derivative technique. Then, we propose an event-triggered distributed model-free adaptive iterative learning bipartite formation control scheme by using the input/output data of MASs without employing either the plant structure or any knowledge of the dynamics. To improve the flexibility and network communication resource utilization, we construct an observer-based event-triggering mechanism with a dead-zone operator. Furthermore, we rigorously prove the convergence of the proposed algorithm, where each agent's time-varying trajectory bipartite formation tracking error is reduced to a small range around zero. Finally, four simulation studies further validate the designed control approach's effectiveness, demonstrating that the proposed scheme is also suitable for the homogeneous MASs to achieve time-varying trajectory bipartite formation tracking.

A new Takagi-Sugeno fuzzy system approach for fuzzy state feedback controller design and its application to malware propagation on heterogeneous complex network

Abstract— Nowadays, digital transformation has brought many great changes and is becoming an essential part of real life, however, it also goes along with a considerable likelihood of being targeted in cyberattack. Indeed, the more businesses embrace digital transformation or use online services, the more opportunities hackers have to expand their cyberattacks. Hence, there is an essential need on analyzing and predicting of cyberattack on network systems. For this aim, we propose to study a controlled fractional network-based SCIRS (Susceptible - Carrier - Infectious - Recovered - Susceptible) malware propagation model and its stabilization problem based on fractional interconnected Takagi-Sugeno fuzzy system. A fuzzy state feedback controller is proposed to asymptotically stabilize the unstable malware-free equilibrium of the proposed malware propagation model and then, we establish sufficient conditions in terms of linear matrix inequalities. The effectiveness of proposed approach is illustrated by a case study of SCIRS malware propagation model on heterogeneous complex network.

Penambahan Bubuk Ekstrak Ikan Haruan (Channa Striata) terhadap Kekuatan Tekan dan Perubahan Warna Glass Ionomer Cement (GIC) Tipe II Secara In Vitro

This study aims to prove the effect of adding haruan fish extract powder (Channa striata) on increasing the strength of type II Glass Ionomer Cement (GIC) filling materials. The method used is a laboratory experimental method with a post-test-only control group design approach. There are 6 treatment groups, namely the addition of 10mg, 20mg, 30mg, 40mg, 50mg, and without addition (pure). This research was conducted at the Dental Materials Laboratory, Faculty of Medicine, Dentistry Study Program, Mulawarman University and PT. Sucofindo Samarinda. The study was conducted from August 2022 to March 2023. The results showed that the greatest compressive strength of glass ionomer cement (GIC) was found in pure glass ionomer cement (GIC) without the addition of haruan fish extract which showed a compressive strength value of 37.0 MPa. The more amount of haruan fish extract powder added, the lower the strength of the glass ionomer cement will be. There is a difference in compressive strength between pure glass ionomer cement (GIC) without haruan fish extract powder and glass ionomer cement (GIC) with haruan fish extract. In conclusion, Glass Ionomer Cement (GIC) type II without the addition of fish extract powder must have the greatest compressive strength compared to the addition of 10 mg, 20 mg, 30 mg, 40 mg, and 50 mg. The addition of haruan fish extract powder decreased the strength of the glass ionomer cement and no color change occurred. 
 
 Keywords: Haruan Fish Extract Powder, Glass Ionomer Cement, Compressive Strength

Integrated process design and self-optimizing control: A probabilistic approach

This work introduces a probabilistic-based integrated process design and self-optimizing control approach grounded in a steady-state model, aiming to strike a balance between solution reliability and optimality. The proposed approach offers a practical and cost-effective solution by considering disturbances as random variables with known probability distribution functions. To propagate these disturbances to process outputs, the unscented transform method is utilized alongside rigorous first-principles process models. Additionally, probability levels are assigned to process constraints based on user-defined specifications, providing flexibility to tailor the design to desired risk confidence levels. The effectiveness and benefits of the approach are demonstrated through an application on an extractive distillation process with pre-concentration.

FEASIBILITY AND ACCEPTABILITY OF A LOVING-KINDNESS MEDITATION AMONG SOCIO-ECONOMICALLY DIVERSE OLDER ADULTS

Abstract It has been established that contemplative practices such as meditation can aid in stress management and the prevention of mental health issues. However, whether one of these techniques, such as loving-kindness meditation (LKM), is feasible for promoting later-life self-compassion, reducing loneliness, and maintaining mental health is unclear. This study examined the feasibility and acceptability of a LKM intervention among socioeconomically diverse older adults. We employed a waiting list control design and mixed methods approach to randomize the participants (n = 59) into two groups. The same intervention was administered to the second group at a later time. We oriented and instructed the older adults on how to meditate and perform the LKM intervention. It contained phrases for the self, immediate family, others, and humanity. We gathered outcome data at baseline, post-intervention, four weeks following journaling, and four weeks without journaling. The intervention was feasible and acceptable (n = 54). One hundred percent of participants rated this meditation practice as either good or better. The range for acceptability was between 4 and 20, while the range for feasibility was between 3 and 15. The participants reported that they accepted (M = 16.8, SD = 2.9) and found this meditative practice feasible (M = 12.9, SD = 1.8). Participants who engaged in this intervention daily reported that this meditative practice helped them reduce anxiety and enhance self-awareness. Our findings highlight the need for large-scale contemplative interventions (including more music and silence) that can promote self-compassion and reduce loneliness in older adults.

Design of a decentralized control law for variable area coupled tank systems using H∞complimentary sensitivity function

AbstractThis paper proposes a novel graphical approach to control the liquid levels of the different variable area coupled tank systems using a decentralized controller. The coupled tank systems are common benchmark systems that consist of two tanks interconnected with each other. The primary goal is to maintain the liquid level in the tank at the desired set point by controlling the flow rate. This is attained with a decentralized method wherein the controller values are obtained from the plane. Besides, the robust criteria is enforced to guarantee the robustness. The proposed controller design approach aims to improve the performance of the system in terms of disturbance rejection and tracking. The decentralized control structure uses a distributed control strategy, thereby reducing the computational load which leads to improving the control performance. The loop interactions are minimized with decouplers. Furthermore, first‐order plus dead‐time (FOPDT) models are derived for each of the decoupled subsystems. Besides, the servo and regulatory responses of the controller are verified with input and output disturbances. Additionally, the response of the controller to system uncertainties and parameter variations is also studied. The simulation results demonstrate the effectiveness and robustness of the proposed approach.

Revisiting Classical Controller Design and Tuning with Genetic Programming.

This paper introduces the application of a genetic programming (GP)-based method for the automated design and tuning of process controllers, representing a noteworthy advancement in artificial intelligence (AI) within the realm of control engineering. In contrast to already existing work, our GP-based approach operates exclusively in the time domain, incorporating differential operations such as derivatives and integrals without necessitating intermediate inverse Laplace transformations. This unique feature not only simplifies the design process but also ensures the practical implementability of the generated controllers within physical systems. Notably, the GP's functional set extends beyond basic arithmetic operators to include a rich repertoire of mathematical operations, encompassing trigonometric, exponential, and logarithmic functions. This broad set of operations enhances the flexibility and adaptability of the GP-based approach in controller design. To rigorously assess the efficacy of our GP-based approach, we conducted an extensive series of tests to determine its limits and capabilities. In summary, our research establishes the GP-based approach as a promising solution for automating the controller design process, offering a transformative tool to address a spectrum of control problems across various engineering applications.

Solving the Zero-Sum Control Problem for Tidal Turbine System: An Online Reinforcement Learning Approach.

A novel completely mode-free integral reinforcement learning (CMFIRL)-based iteration algorithm is proposed in this article to compute the two-player zero-sum games and the Nash equilibrium problems, that is, the optimal control policy pairs, for tidal turbine system based on continuous-time Markov jump linear model with exact transition probability and completely unknown dynamics. First, the tidal turbine system is modeled into Markov jump linear systems, followed by a designed subsystem transformation technique to decouple the jumping modes. Then, a completely mode-free reinforcement learning algorithm is employed to address the game-coupled algebraic Riccati equations without using the information of the system dynamics, in order to reach the Nash equilibrium. The learning algorithm includes one iteration loop by updating the control policy and the disturbance policy simultaneously. Also, the exploration signal is added for motivating the system, and the convergence of the CMFIRL iteration algorithm is rigorously proved. Finally, a simulation example is given to illustrate the effectiveness and applicability of the control design approach.

Collision avoidance and connectivity preservation using asymmetric barrier Lyapunov function with time-varying distance-constraints

Collision avoidance and connectivity preservation are two contrasting issues in multi-agent formation control problems. This paper proposes a distributed control design methodology to stabilize a desired formation shape in a multi-agent system while incorporating these two factors simultaneously. Contrary to a simplifying point mass assumption, we consider that agents in the group are characterized by a circular disk-type structure of different radii. Collision avoidance and connectivity preservation in the group are handled by applying time-varying constraints on the inter-center distances among neighboring agents. The concept of asymmetric time-varying barrier Lyapunov function is exploited to derive the stabilizing distributed control law, under a mild assumption on the initial conditions and a feasibility condition relating dimensions of the desired formation with the lower and upper limits of the barrier functions. We also obtain analytical bounds on the various post-design signals and illustrate the results through a simulation example. Finally, the effect of input saturation is discussed, and a comparison with the sensing-region-dependent potential function-based control design approach from the existing literature is provided.