Robust Closed-loop Control Research Articles

Optimizing domestic energy management with a wild Mice colony-inspired algorithm: Enhancing efficiency and coordination in smart grids through dynamic distributed energy storage

Energy management (EM) is a critical strategy that spans the production and consumption of electricity, enhancing the stability of the electricity network. Smart grid technology significantly improves the electrical system's energy efficiency (EE), facilitating a transformation from a conventional power grid (PG) to a smart PG. This paper presents a key strategy for modeling the EE of the smart grid tailored to domestic demand, establishing smart coordination between domestic demand, energy production, and storage to reduce energy waste and costs. Our model integrates various energy sources, including renewable energy (RE), photovoltaic (PV) systems, wind power, and an energy storage system (ESS), interconnected with the PG. The model's structure ensures the coordinated flow of electricity in a residential house through an optimal control method (OCM). To develop a robust closed-loop control model, we employ Demand Response (DR) schemes within the Real-Time Electricity Pricing (RTEP) framework. We construct a dynamic model of the ESS to compute the System Performance Index (SPI), corresponding to energy costs. To enhance our model, we introduce a Dynamic Distributed Energy Storage Strategy (DDESS). Additionally, we introduce a novel optimization algorithm inspired by the behavioral patterns of wild mice, called the Wild Mice Colony (WMC). By analyzing the targeted and advantageous behaviors of wild mice in colonies, we propose that these behaviors can serve as a model for addressing complex, uncertain problems. This strategy is highly advantageous, capable of reducing total energy consumption (EC) from the main grid by over 100 % of the load demand, optimizing the energy system, and ensuring synchronization. The performance of DDESS optimizes energy flow (EF) during the repayment plan, leading to minimized EC costs from the PG.

A Robust Switching Control Strategy for Three-Phase Voltage Source Converters with Uncertain Circuit Parameters

This study proposes a novel double closed-loop robust control strategy based on a power switching affine model of three-phase voltage source converters (VSCs). The aim is to overcome the challenges posed by inaccurate mathematical models, complex controller configurations, indirect switching control, and performance degradation under circuit parameters uncertainty or load variation in conventional methods. These conventional methods rely on linearization models, duty ratio regulation, and pulse width modulation (PWM) technologies. The contributions of work are the following: (1) A two-dimensional (2D) power switching affine model is constructed without any approximation or averaging. (2) The proposed approach achieves direct switching control of three-phase VSCs, eliminating the need for complex rotation coordinate transformation, PWM, and phase locking loop (PLL), which are utilized in traditional control methods. (3) The rigor of the system stability analysis is enhanced based on the 2D power switching model compared to the existing three-dimensional (3D) current switching model. (4) A simple control structure with only two control parameters is employed to address circuit parameter uncertainties. The effectiveness and superiority of the proposed method is validated through simulation and experimental comparison results.

Series-Hybrid Powertrains: Advancing Mobility Control in Electric Tracked Vehicle Technology

This work focuses on developing a mobility control system for high-speed series-hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of this research includes modeling a series-hybrid powertrain specific to military tracked vehicles and conducting an in-depth analysis of its dynamic behavior. Subsequently, this study conducts a critical review of mobility control approaches sourced from the literature, identifying key techniques relevant to high-inertia vehicular applications. Building on foundational models, this study proposes a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system’s resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are conducted in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system’s capacity to improve the vehicular response and highlight its potential impact on future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.

Immrax: A Parallelizable and Differentiable Toolbox for Interval Analysis and Mixed Monotone Reachability in JAX

We present an implementation of interval analysis and mixed monotone interval reachability analysis as function transforms in Python, fully composable with the computational framework JAX. The resulting toolbox inherits several key features from JAX, including computational efficiency through Just-In-Time Compilation, GPU acceleration for quick parallelized computations, and Automatic Differentiability We demonstrate the toolbox’s performance on several case studies, including a reachability problem on a vehicle model controlled by a neural network, and a robust closed-loop optimal control problem for a swinging pendulum.

Robust output-feedback control of fluid resuscitation with absolute stability guarantee against uncertain physiology and therapeutic responsiveness

This paper presents a robust closed-loop control approach to fluid resuscitation in patients with hemorrhagic blood loss. A unique strength of the proposed approach is its robustness against uncertain and time-varying patient physiology and therapeutic effectiveness. First, we adopted an observer-based control architecture that can fulfill set point tracking and disturbance rejection objectives. Second, we determined the control gains to achieve adequate transient response performance using the linear quadratic regulator design. Third, we determined the observer gains as a solution to a set of linear matrix inequalities so that the overall closed-loop fluid resuscitation control system is (i) robust against the variability in patient physiology and (ii) absolutely stable against unknown therapeutic effectiveness. We demonstrated the initial proof-of-concept of the proposed approach by conducting rigorous in silico testing using a large number of physiologically plausible virtual patients, while ascertaining the absolute stability via the circle criterion analysis. The results suggested that the proposed approach to closed-loop control of fluid resuscitation is a promising option to advance automation of fluid resuscitation armed with stability against a large variability in patient physiology and therapeutic effectiveness as well as adequate performance in set point tracking and disturbance rejection.

Robust closed-loop control of systemic oxygenation in acute lung injury

Tight control of systemic oxygenation is a key component of mechanical ventilation of critically ill patients. Yet, closed-loop control remains challenging due to the non-linear, uncertain, and time-varying relationship between the inspired oxygen and the resulting patient’s oxygen saturation, especially in cases of acute lung injury. This paper uses a Hammerstein model to combine a clinically validated static model incorporating ventilation-to-perfusion mismatch with uncertain linear dynamics to synthesize a robust closed-loop controller for regulating systemic oxygenation in subjects with acute lung injury. Data from an experimental lung injury model in five pigs, in combination with data augmentation, allowed modeling of the uncertainty in the system. Subsequently, gain-scheduled proportional–integral controllers were designed using the mixed-sensitivity H∞ approach. The resulting closed-loop systems were analyzed for robust stability, and the performance was evaluated in a thousand synthetically generated subjects spanning the overall parameter space in various combinations. A mean rise time of less than three minutes was achieved for recovering from the severely hypoxemic state for simulated subjects with a range of ventilation-to-perfusion mismatch and arterial acid–base status. Furthermore, the results from a pilot animal experiment matched the simulated results well, and the system could respond to significant disturbances. The system was safe and reliable in both simulations and the pilot animal experiment. The methodological approach for uncertainty modeling and controller synthesis is an essential step toward the practical deployment of closed-loop control of systemic oxygenation in the acutely injured lung.

Closed-loop robust control of robotic flexible endoscopy with neural network-based lumen segmentation

Accurate positioning of the flexible endoscope during clinical procedures is critical for the visualization and success of surgical interventions. However, manual operation of the endoscope is challenging, especially for less-experienced users, due to visual reasoning and hand-eye coordination requirements. To achieve automatic steering of the endoscope, this work proposes a closed-loop robust control method that allows the endoscope to smoothly travel along the upper respiratory tract. First, an attention neural network is introduced to segment the lumen region in endoscopic images, which indicates the moving direction of the endoscope. The segmentation results are optimized by convolutional conditional random field (ConvCRF). In addition, to steer the flexible endoscope, an active disturbance rejection control (ADRC) strategy is proposed to adjust the orientation of the endoscope tip. An external state observer (ESO) is designed to estimate environmental disturbances, enabling the controller to compensate for the positioning error. Finally, the segmentation method achieved the mIOU, accuracy, and Dice values of 85.4%, 97.5%, and 91.4%, respectively, outperforming state-of-the-art methods. The performance of the controller was validated on a real robot showing the ability to automatically steer the flexible endoscope along the upper respiratory tract.

AeCoM: An Aerial Continuum Manipulator With IMU-Based Kinematic Modeling and Tendon-Slacking Prevention

This article presents a novel aerial manipulator (AM) system called the aerial continuum manipulator (AeCoM). The system is comprised of a quadrotor and a tendon-driven continuum robotic manipulator. Compared to current AMs, the AeCoM has the advantages of being lightweight and having high dexterity. The continuum manipulator has two contributions: 1) the development of an IMU-based kinematic model to obtain the precise end-effector pose under external loading and 2) the design of a robust closed-loop kinematic controller that implements fast shape-deformation control and prevents tendon slacking by providing feedback of the configuration space and torque applied on tendons. The article provides a detailed mechanical design of the system and extensive experiments were conducted to validate the system’s performance.

Discrete Cosserat Static Model-Based Control of Soft Manipulator

In this letter, the continuous Cosserat static model is re-formulated by employing the piecewise linear strain (PLS) approach, which can obtain the analytic formula of the model to facilitate the controller design. The robust closed-loop control architecture based on the PLSCosserat static model for the soft arm around its workspace is then established. To validate the performance of the proposed model-based control scheme, the point-to-point and time-varying trajectory tracking experiments under external disturbances have been conducted on the soft manipulator actuated by cables.

Robust Stabilization of Underactuated TORA System Based on Disturbance Observer and Fixed-Time Sliding Mode Control Method

A translational oscillator with a rotational actuator (TORA) is an underactuated nonlinear mechanical system with two degrees of freedom (DOF). This paper concerns the robust stabilization control problem for the system with multiple external disturbances. First, a disturbance observer is constructed based on the internal nonlinear dynamic behavior of the system. Second, a robust stabilization controller is designed by the estimated disturbances and the fixed-time sliding mode control method. The controller realizes the global robust stabilization control objective of the TORA system, and the stability of both disturbance observer and robust closed-loop control system are analyzed using the Lyapunov theorem. Finally, the effectiveness of the theoretical results are verified by numerical experiments.

High-precision Closed-loop Robust Control of Industrial Robots Based on Disturbance Observer

High-precision Closed-loop Robust Control of Industrial Robots Based on Disturbance Observer

Experimental model-based closed-loop control of a separated boundary layer at high Reynolds number

Experimental robust closed-loop control of a two-dimensional turbulent boundary layer with substantial separation is investigated. An array of 22 round fluidic jets located upstream of the separation location is used as actuation to reattach the flow. Measurements of phase-averaged velocity with 2D2C Particle Image Velocimetry (PIV) and wall friction using hot-film anemometry are performed to characterize the flow dynamics under open-loop actuation to elaborate models of the flow transient. Different feedback model-based controllers (Proportional Integral, linear–quadratic, linear–quadratic-gaussian and H∞ regulators) are then designed and implemented experimentally. The performances in term of precision, reactivity and control cost of each of the controllers are presented and discussed. Only the H∞ controller is found to maintain high performances despite large upstream unsteady perturbations.

A compact system for simultaneous stimulation and recording for closed-loop myoelectric control

BackgroundDespite important advancements in control and mechatronics of myoelectric prostheses, the communication between the user and his/her bionic limb is still unidirectional, as these systems do not provide somatosensory feedback. Electrotactile stimulation is an attractive technology to close the control loop since it allows flexible modulation of multiple parameters and compact interface design via multi-pad electrodes. However, the stimulation interferes with the recording of myoelectric signals and this can be detrimental to control.MethodsWe present a novel compact solution for simultaneous recording and stimulation through dynamic blanking of stimulation artefacts. To test the system, a feedback coding scheme communicating wrist rotation and hand aperture was developed specifically to stress the myoelectric control while still providing meaningful information to the subjects. Ten subjects participated in an experiment, where the quality of closed-loop myoelectric control was assessed by controlling a cursor in a two degrees of freedom target-reaching task. The benchmark performance with visual feedback was compared to that achieved by combining visual feedback and electrotactile stimulation as well as by using electrotactile feedback only.ResultsThere was no significant difference in performance between visual and combined feedback condition with regards to successfully reached targets, time to reach a target, path efficiency and the number of overshoots. Therefore, the quality of myoelectric control was preserved in spite of the stimulation. As expected, the tactile condition was significantly poorer in completion rate (100/4% and 78/25% for combined and tactile condition, respectively) and time to reach a target (9/2 s and 13/4 s for combined and tactile condition, respectively). However, the performance in the tactile condition was still good, with no significant difference in path efficiency (38/8%) and the number of overshoots (0.5/0.4 overshoots), indicating that the stimulation was meaningful for the subjects and useful for closed-loop control.ConclusionsOverall, the results demonstrated that the developed system can provide robust closed-loop control using electrotactile stimulation. The system supports different encoding schemes and allows placing the recording and stimulation electrodes next to each other. This is an important step towards an integrated solution where the developed unit will be embedded into a prosthetic socket.

An Interactive Software Tool to Learn/Teach Robust Closed-Loop Shaping Control Systems Design

Models are always subject to uncertainty. This can come mainly from parameter uncertainty, reduced order dynamics, or unmodelled dynamics. The model uncertainty is a concept that is difficult to introduce in automatic control introductory courses. The mathematical formalization of many of the ideas necessary to introduce students to robust control is complex for most students, causing many students to get lost in the mathematics and do not understand the important control concepts. The closed-loop shaping control design methodology allows introducing the model uncertainty in a simple way. It has some very interesting characteristics from a teaching point of view, since it allows concentrating on shaping the closed-loop frequency response in order to obtain the desired performance and robustness. This paper presents the main features and functionality of RCLSD an interactive software tool developed by the authors for learning and teaching the robust closed-loop shaping control design methodology.

Robust tracking control in the inertia phase for generalised disturbance

To solve the problem of shift shock during the inertia phase caused by generalized disturbances in wheel loaders and other construction instruments, a robust double closed-loop tracking control method based on an improved disturbance observer (DOB) has been proposed. In this method, the inner loop robustly suppresses disturbance and the outer loop realizes trajectory tracking. The improved DOB based on a nominal disturbance value (NDV) can enhance the disturbance suppression ability of the inner loop when a large part of the generalized disturbance is determinable. The model matching method transforms the outer loop into a transfer function to meet the expected performance. A disturbance compensation controller eliminates the nominal disturbance in the system. A feedforward compensation controller eliminates the influence of reference inputs in the system. Considering the inertia phase of a fixed-axis automatic transmission of a wheel loader, the proposed method was applied to the driveline simulation platform of a specific type of wheel loader. Random loads under actual working conditions were considered as the input load of the simulation platform. The simulation results indicated that the DOB based on the NDV method has better disturbance suppression capability, more accurate tracking capability and smaller shift shock than the conventional DOB method. The proposed control method exhibits robustness under 10%, 50% and 90% of the maximum load. The highest shift shock is 4.94% of the manual shift shock and it is effectively reduced. Thus, robust and smooth inertia phase shift control of the automatic transmission can be realized. This study presents an effective method for solving robust disturbance suppression control problems and tracking control problem under large generalized disturbances.

Experimental Validation of a Robust H∞ Control Method on Miniaturized Optical Image Stabilizer Prototypes

Abstract This paper validates a robust H∞ controller design method, experimentally, on miniaturized prototypes of the magnetically actuated lens-tilting optical image stabilizers (OISs) with product variabilities. Five small-scale OIS prototypes with product variations are constructed by three-dimensional (3D) printing. For the prototypes, the model parameters are identified based on experimental frequency response data of the prototypes. Using the identified model, a robust H∞ controller is designed to guarantee the robust stability of the closed-loop system and to optimize the closed-loop performance. The experimental results reveal larger and more complex uncertainties in miniaturized OISs with mass-produced parts compared to large-scale prototypes. Despite the increased amount of uncertainties, it is demonstrated that the robust H∞ controller still outperforms the conventional controllers in terms of robust closed-loop stability, performance, and controller order for practical implementation on a mobile phone device.

Novel algebraic meal disturbance estimation based adaptive robust control design for blood glucose regulation in type 1 diabetes patients.

This study designs a robust closed-loop control algorithm for elevated blood glucose level stabilisation in type 1 diabetic patients. The control algorithm is based on a novel control action resulting from integrating algebraic meal disturbance estimator with back-stepping integral sliding mode control (BISMC) technique. The estimator shows finite time convergence leading to accurate and fast estimation of meal disturbance. Moreover, compensation of the estimated disturbance in controller provides significant reduction in chattering phenomenon, which is inherent drawback of sliding mode control (SMC). The controller is applied to one of the most reliable models of type 1 diabetic patients, named Bergman's minimal model. The effectiveness and superiority of the designed controller is shown by comparing it to classical SMC and super-twisting sliding mode control. The designed controller is subject to three different cases for detailed analysis of the controller's robustness against meal disturbance. The three cases considered are hyperglycaemia, hyperglycaemia combined with meal disturbance and three meal disturbance. The simulation results confirm superior performance of algebraic disturbance estimator based BISMC controller for all the cases mentioned above.

Dynamics and control of COVID-19 pandemic with nonlinear incidence rates

World Health Organization (WHO) has declared COVID-19 a pandemic on March 11, 2020. As of May 23, 2020, according to WHO, there are 213 countries, areas or territories with COVID-19 positive cases. To effectively address this situation, it is imperative to have a clear understanding of the COVID-19 transmission dynamics and to concoct efficient control measures to mitigate/contain the spread. In this work, the COVID-19 dynamics is modelled using susceptible–exposed–infectious–removed model with a nonlinear incidence rate. In order to control the transmission, the coefficient of nonlinear incidence function is adopted as the Governmental control input. To adequately understand the COVID-19 dynamics, bifurcation analysis is performed and the effect of varying reproduction number on the COVID-19 transmission is studied. The inadequacy of an open-loop approach in controlling the disease spread is validated via numerical simulations and a robust closed-loop control methodology using sliding mode control is also presented. The proposed SMC strategy could bring the basic reproduction number closer to 1 from an initial value of 2.5, thus limiting the exposed and infected individuals to a controllable threshold value. The model and the proposed control strategy are then compared with real-time data in order to verify its efficacy.

A new robust closed-loop control system for electrosurgical generators

Commercially available electrosurgical generator (ESG) depends on circuit topologies that are responsive to changes in resistance of the tissue. This change in resistance varies the amount of power delivered, especially amid arcing. Changes in resistance along the body make it even harder to keep the power delivery and voltage in limits. An important property of ESG is to be able to keep the output power constant in the constant power region. In this work, a closed-loop control system is designed and tested for ESG to improve its performance in the nonlinear constant power region. A quantitative study of a buck converter and boost inverter is presented along with the closed-loop response for the ESG unit. A comparative analysis of two control methods, i.e., proportional integral derivative (PID) and proportional integral derivative sliding mode control (PIDSMC), is presented for the ESG unit. Results confirm that the presented closed-loop system can highly improve the performance of the ESG system and PIDSMC is found to be a more suitable choice.

Decoupled nonlinear adaptive control of position and stiffness for pneumatic soft robots

This article addresses the problem of simultaneous and robust closed-loop control of joint stiffness and position, for a class of antagonistically actuated pneumatic soft robots with rigid links and compliant joints. By introducing a first-order dynamic equation for the stiffness variable and using the additional control degree of freedom, embedded in the null space of the pneumatic actuator matrix, an innovative control approach is introduced comprising an adaptive compensator and a dynamic decoupler. The proposed solution builds upon existing adaptive control theory and provides a technique for closing the loop on joint stiffness in pneumatic variable stiffness actuators. Under a very mild assumption involving the inertia and actuator matrices, the solution is able to cope with uncertainties of the model and, when the desired stiffness is constant or slowly varying, also of the pneumatic actuator. Position and stiffness decoupling is achieved by the introduction of a first-order differential equation for an internal state variable of the controller, which takes into account the time derivative of pressure in the stiffness dynamics. A formal proof of the stability of the position and stiffness tracking errors is provided. An appealing property of the approach is that it does not require higher derivatives of position or any derivatives of stiffness. The solution is validated with respect to several use-cases, first in simulation and then via a real pneumatic soft robot with McKibben muscles. A comparison with respect to existing techniques reveals a more robust position and stiffness tracking skill.