Stable Control Research Articles

Downwash Reduction Drone With Adaptive Rotors and Its 3D Aerodynamic Analysis and Stabilization Control

Downwash Reduction Drone With Adaptive Rotors and Its 3D Aerodynamic Analysis and Stabilization Control

An Investigation of Manifold-Based Direct Control for a Brain-to-Body Neural Bypass.

Objective: Brain-body interfaces (BBIs) have emerged as a very promising solution for restoring voluntary hand control in people with upper-limb paralysis. The BBI module decoding motor commands from brain signals should provide the user with intuitive, accurate, and stable control. Here, we present a preliminary investigation in a monkey of a brain decoding strategy based on the direct coupling between the activity of intrinsic neural ensembles and output variables, aiming at achieving ease of learning and long-term robustness. Results: We identified an intrinsic low-dimensional space (called manifold) capturing the co-variation patterns of the monkey's neural activity associated to reach-to-grasp movements. We then tested the animal's ability to directly control a computer cursor using cortical activation along the manifold axes. By daily recalibrating only scaling factors, we achieved rapid learning and stable high performance in simple, incremental 2D tasks over more than 12 weeks of experiments. Finally, we showed that this brain decoding strategy can be effectively coupled to peripheral nerve stimulation to trigger voluntary hand movements. Conclusions: These results represent a proof of concept of manifold-based direct control for BBI applications.

Finite-Time Disturbance Rejection Control for Rigid Spacecraft Attitude Set Stabilization with Actuator Saturation

Finite-Time Disturbance Rejection Control for Rigid Spacecraft Attitude Set Stabilization with Actuator Saturation

Model-Free Predictive Current Controller for Common Mode Voltage Stabilization by Finite odd Virtual Vector set

Model-Free Predictive Current Controller for Common Mode Voltage Stabilization by Finite odd Virtual Vector set

Boundary control for prescribed-time stabilisation of delayed parabolic reaction-diffusion systems

Boundary control for prescribed-time stabilisation of delayed parabolic reaction-diffusion systems

Fruit Fly Algorithm Optimised Degree of Freedom Controller for the Dynamical Stability of the Renewable Energy Penetrated Multi Area Power System

The stability and maintenance of the renewable energy penetrated multi-area power system (REPMAPS) are so complex. To ensure the optimal functioning of the complex interconnected power system (IPS), an automatic controller is necessary for the proper load frequency control (LFC) actions. For this, a three-degree-of-freedom proportional-integral-derivative (3DOFPID) controller is suggested in this work for simultaneous frequency regulation. However, the parameters of the 3DOFPID controller are to be ascertained using soft computing algorithms to obtain better performance. The fruit fly algorithm (FFA) is implemented in this paper for the fine-tuning of the 3DOFPID controller, and the efficacy of the FFA is demonstrated with other algorithms in the literature. Besides, the analysis of REPMAPS is deliberated with communication time delays (CTDs) as the practical constraint, and their effect on the system’s dynamic performance is showcased. Further, the REPMAPS is operated with the territory strategy of capacitive energy storage (CES) and the static synchronous series compensator (SSSC) to improve the system performance. The simulation study confirmed the enhancement in REPMAPS performance with the CES-SSSC strategy.

Event-Triggered Finite-Time Stabilization of Fuzzy Neural Networks With Infinite Time Delays and Discontinuous Activations

This paper unifies the stability criteria of asymptotic, exponential and finite-time control within a single framework for fuzzy neural networks (FNNs) with infinite time delays. First, the boundedness and differentiability for time delays are removed. Then, Lipschitz condition for activation function is relaxed, which is allowed to have jumping discontinuous points. To stabilize FNNs, the analytical method is established by comparison principle, contradiction method and inequality techniques. Moreover, different from the traditional Lyapunov method and finite-time stability theorem, several sufficient conditions are deduced and the suppression functions are designed to guarantee asymptotic, exponential and finite-time stabilization for FNNs by adjusting the parameters of the same controller. There is not necessary to construct the complex integral-type Lyapunov functional to deal with infinite time delays and to design power function in controller for finite-time stabilization. In addition, the designed event-triggered mechanism (ETM) has the inherent advantages of saving communication resources and indirectly eliminates the chattering caused by signum function. Finally, simulations are presented to illustrate the feasibility and effectiveness of the theoretical results.

Hierarchical Model-Based Irrigation Control for Vertical Farms

As high energy costs and water scarcity remain major problems in the context of vertical farming, we present a hierarchical control system developed for the optimization of irrigation processes in these farms. The main objective is to minimize the energy cost and water consumption associated with the operation of a vertical farm, with special emphasis on irrigation in a soil-based environment. At a higher level, an optimal control problem based on a dynamic crop growth model and the FAO Penman-Monteith equations is solved offline to determine the optimal daily inputs, considering temperature, radiation, and plant available water as decision variables. At a lower level, strategically placed Proportional-Integral-Derivative (PID) controllers are used to track these irrigation set-points online. These controllers are designed using a dynamic drip irrigation and soil model that simulates the movement of water through soil. In a simulation study, this integration of set-points and subordinate PID controllers shows a robust control system that effectively stabilizes the irrigation process. The results also show a uniform moisture distribution in the soil after a short time, which contributes to uniform plant growth in the farm. The proposed hierarchical control system combines computationally intensive offline open-loop optimization for daily input determination with fast and simple online PID control for real-time stabilization.

Stabilization and Optimal Control for Markov Jump Linear System With Two Controllers Over Multiple Erasure Channels

Stabilization and Optimal Control for Markov Jump Linear System With Two Controllers Over Multiple Erasure Channels

Secure Event-Triggered Sliding Control for Path Following of Autonomous Vehicles Under Sensor and Actuator Attacks

Sensor and actuator attacks, which propagate the injected false data through CAN bus, make real threats to the security of the control of autonomous vehicles. This paper attempts to solve the secure event-triggered path following control problem of autonomous vehicles subject to both sensor and actuator attacks. Firstly, a more general physical security model is established to characterize the impacts of sensor and actuator attacks on measurements and control actions. Then, feedback linearization method based on Lie derivative is exploited to linearize the established nonlinear attacked model. Thus, the nonlinear path following control is transformed into a linear case which will facilitate to the following networked-based analysis and design. Based on the established secure model, the event-triggered control scheme is utilized to alleviate communication burden under sampled-data control framework. Furthermore, the sliding control design is augmented to mitigate the malicious impacts caused by such false data injection attacks due to its inherent robustness to abnormal attack signal. Remarkably, the proposed secure sliding control can be plugged into the original control scheme rather than changing its existing control structure. Criteria for formal stability analysis and controller design are also provided and expressed in terms of some numerically tractable linear matrix inequalities. Finally, both simulation and experimental verification cases are shown to verify the composite control scheme.

Stability Analysis and Controller Synthesis Using Single-Hidden-Layer ReLU Neural Networks

This paper presents algorithms to solve analysis and controller synthesis problems for dynamical systems modeled as a recurrent single-hidden-layer rectified linear unit neural network (ReLU NN), or equivalently, a piecewise affine dynamical system. Such models are interesting since they may arise through the use of modern machine learning methods for system identification, or as closed-loop solutions in certain classes of model predictive control (MPC) problems. A key idea in the proposed approach is to use piecewise affine Lyapunov functions parametrized as ReLU neural networks, and similarly parametrized controllers. This compatible representation between the Lyapunov function and the dynamics simplifies the automation of analysis of and controller synthesis for learned models. Our method of verifying a candidate Lyapunov function is faster than methods based on mixed integer programming. We ‘learn’ controllers and Lyapunov functions using both weight updates and network architecture search, without gradients. We demonstrate the proposed algorithm on examples involving learned models, explicit MPC controllers, and constrained controller synthesis.

Stabilization and Optimal Control of Interconnected SDE -Scalar PDE System

Stabilization and Optimal Control of Interconnected SDE -Scalar PDE System

Single Center Experience With Sodium-Glucose Co-Transporter-2 Inhibitors (SGLT2i) in Kidney Transplant Recipients With Diabetes.

Sodium-glucose co-tranporter-2 inhibitors have been shown to be safe and effective in patients with type 2 diabetes for improving glycemia. Furthermore large, randomized control trials have shown cardiovascular and renal benefits. However, limited safety and efficacy data is available in kidney transplant patients with diabetes. To investigate the safety and efficacy of SGLT2i use on stability of renal function in adult kidney transplant recipients (KTR) with type 2 diabetes mellitus (DM2) or New Onset Diabetes After Transplantation (NODAT). We performed a single center, retrospective cohort study pre- and post-SGLT2i exposure. Adults with DM2 or NODAT who received a living or deceased kidney transplant (Tx) and started on an SGLT2i post-Tx were reviewed. Patients who had type 1 diabetes were excluded. The baseline was the SGLT2i start date. We reviewed available data from 24 months (M) before and after SGLT2i initiation. The primary endpoints were the effects of SGLT2i use on stability of renal function using serum creatinine and eGFR, change in urine albumin excretion(uACR), and glycosylated hemoglobin (A1C). Secondary endpoints compared blood pressure, body mass index and adverse reactions at baseline and quarterly after SGLT2i initiation. 125 KTRs were included in cohort: NODAT (52, 42%), DM2 (73, 58%); female (33, 27%); mean age at Tx 55 years (25-75); LD (56, 45%), DD (69, 55%); mean duration of Tx (6.8 years, 0.1-42.5); study follow-up (1.8 years, 0.3-4.9).The mean eGFR remained stable pre-SGLT2i at 64.6 mL/min/1.73m2, vs post at 64.3 mL/min/1.73m2. There was no difference in mean A1C after SGLT2i initiation. The slope of uACR using natural log transformation pre-SGLT2i compared with post-SGLT2i slope reduced from +0.7 (0.03, 0.11) to -0.04 (-0.01, -0.35) mg/mmol/3mths (P = .002). The risk of developing new genital mycotic infections among all patients was 4% (95% CI 1.3%-9.1%) While there was no significant difference in UTI before (13.6%) and after (12%) SGLT2i use (P = .68), there was a higher risk of UTI seen in patients with a previous history of UTI (23.5%) vs no previous history (10.2%) post initiation. There was no significant increase in AKI pre 8%, post 10.4%, P = .51. There was a single DKA event pre- and post-SGLT2. The limitations of this study include its retrospective nonrandomized nature. In this retrospective analysis, SGLT2i use in KTR appears to be safe and efficacious with stable renal function and glycemic control, alongside improvements in uACR. There was a low risk of new genital yeast infections after SGLT2i start. UTI occurrence was higher in patients with a previous history of UTI compared with those with no previous history.

Effects of microplastics on granular sludge: A review

Biogranules are recently regarded as promising methods with intensive density and satisfying settleability for waste treatment and resource recovery. Wastewater treatment plants (WWTP) were regarded as “sinks” for Microplastics (MPs) and amount of MPs entrapped in the sludge. MPs have been reported to harm the granular characteristics and wastewater treatment efficiency. Previous research stated that the harmful effect on granular sludge is closely associated with the sizes and concentrations of MPs. However, there is still a lack of a comprehensive summary of granular characteristics variation and further investigation of its influential mechanisms for treatment capability. This work gives informative clues for the regulation mechanisms, especially the microorganisms’ response after the exposure of MPs, and provides fundamentals for stable operation and risk control strategies using granular sludge in treating microplastics containing wastewater.

Observer-based event triggering security load frequency control for power systems involving air conditioning loads

<p>This paper presents a power system frequency control strategy that integrates an observer-based event-triggered mechanism (ETM) to defend against denial-of-service (DoS) attacks and accommodates the integration of renewable energy sources. The proposed strategy incorporates demand response by enabling air conditioning loads (ACs) to participate in frequency regulation, thereby enhancing system flexibility and stability. To address the challenges posed by limited network bandwidth and potential message blocking, the ETM minimizes communication while defending against DoS attacks. The stability of the closed-loop system is guaranteed by deriving an $ H_{\infty} $ stability criterion using the Lyapunov–Krasovskii function method, with controller parameters determined through linear matrix inequalities (LMIs). A two-area power system simulation is conducted to validate the feasibility and effectiveness of the proposed approach, demonstrating its ability to maintain stable frequency control under cyber-attack scenarios and varying renewable energy contributions.</p>

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.

Edge Removal and Q -Learning for Stabilizability of Boolean Networks.

This article develops a new edge removal mechanism for the global stabilizability of Boolean networks (BNs). In order to achieve the edge removal control, several control variables are properly placed into the dynamics of BNs based on the fundamental logical operators. On the basis of the new edge removal mechanism, several necessary and sufficient conditions are obtained for the global stabilizability and set stabilizability of BNs. Furthermore, a kind of stable edge removal control is proposed and achieved via the Q -learning algorithm to optimize the edge removal mechanism. As an application, the edge removal control is used to verify whether or not the mammalian cortical area development model can be made stabilizable to the expected stable states.

Generation, control, and application of stable bubbles in a hypersonic acoustic system.

Bubble-based microfluidics has been applied in many fields. However, there remains a need for a facile and flexible method for stable bubble generation and control in a microchannel. This paper reports a hypersonic acoustic system that can generate and release functional stable bubbles in a microchannel in an on-demand manner. It was found that the hypersonic frequency in this system played a vital role in the generation and control of bubbles. Specifically, a nanostructurally enhanced acoustic resonator was used to generate highly localized ultrahigh-frequency acoustic waves that ensured the feasibility and rapidity of bubble generation. Simultaneously, the acoustothermal effect of hypersound was harnessed to effectuate precise control over the bubble size. In addition, high-throughput droplet splitting was performed to confirm the stability of bubbles and their functionality in micromanipulation. The results showed that a mother droplet could be split controllably into a desired number of daughter droplets with specific volume ratios. In summary, the hypersonic acoustic system was demonstrated to be capable of on-demand-generation of stable bubbles in a microfluidic context and thus may extend the bubble-based applications.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

Revisiting Walking-in-Place by Introducing Step-Height Control, Elastic Input, and Pseudo-Haptic Feedback.

Walking-in-place (WIP) is a locomotion technique that enables users to "walk infinitely" through vast virtual environments using walking-like gestures within a limited physical space. This article investigates alternative interaction schemes for WIP, addressing successively the control, input, and output of WIP. First, we introduce a novel height-based control to increase advanced speed. Second, we introduce a novel input system for WIP based on elastic and passive strips. Third, we introduce the use of pseudo-haptic feedback as a novel output for WIP meant to alter walking sensations. The results of a series of user studies show that height and frequency based control of WIP can facilitate higher virtual speed with greater efficacy and ease than in frequency-based WIP. Second, using an upward elastic input system can result in a stable virtual speed control, although excessively strong elastic forces may impact the usability and user experience. Finally, using a pseudo-haptic approach can improve the perceived realism of virtual slopes. Taken together, our results suggest that, for future VR applications, there is value in further research into the use of alternative interaction schemes for walking-in-place.