Design Of Control Architecture Research Articles

Adaptive Mission Control Architecture with Flexible Levels of Autonomy

The future battlefield operation concept does not focus on advanced and complete weapon systems, but requires a new battlefield operation concept that can effectively demonstrate offensive power by combining a large number of low-cost, miniaturized weapons. Recently, research on the autonomous application of major technologies that make up the mission control system is actively underway. However, since the mission control system is still dependent on the operator's operating ability when operating multiple robots, there are limitations to simply applying the automation technology of the existing mission control system. Therefore, we understand how changes in operator capabilities affect multi-robot operation and propose an adaptive mission control architecture design method that supports multi-robot integrated operation by adjusting the level of autonomy of the mission control system according to changes in operator capability.

UML design for access control architecture in smart building application

SummaryCyber physical systems are complex systems to build and implement, electronic devices and concepts such as the energy saving, the user comfort and the privacy of sensitive data. In the physical world, buildings represent a major part of total energy consumption, that's why improving the energy efficiency levels of buildings is topical by which the emergence of smart buildings. Since, even if efforts are being made in normalizing the process of energy saving management while maintaining a high level of users' comfort, managing the access control in smart buildings systems remains an ad‐hoc process. This is why a number of researches focus on the design and implementation of solutions aimed at covering the process of access control management. In the context of developing a smart building application, already developed in our laboratory, we have set up an access control management system to manage users' access. We present the design of an access control architecture, using the Unified Modeling Language, upon the smart building application which is the subject of a maintenance work. The designed solution is implemented with the purpose of evolving the application to be used by multiple users. The implemented access control solution is an extended role‐based access control model.

Decoding transient sEMG data for intent motion recognition in transhumeral amputees

The use of surface electromyographic (sEMG) signals, alongside pattern recognition (PR) systems, is fundamental in the design and control of assistive technologies. Transient sEMG signal epochs at the early beginning of the movement provide important information for upper-limb intent of motion recognition. However, only few studies investigated the role of transient sEMG for myoelectric control architectures. Therefore, in this work, focus was given to transient sEMG signals of intact-limb (IL) subjects and transhumeral amputees (AMP), who performed a series of shoulder movements. The role of the window length for feature extraction was investigated by sub-windowing the transient epochs at 200, 150, 100, and 50 ms window length (WL). Gaussian kernel discriminant analysis (SRKDA) and support vector machine (SVM) were used for recognizing seven classes of motion at different hold-out percentage of training/testing data, i.e. 70%–30%, 60%–40% and 50%–50%. In all the latter conditions, the median classification accuracy and F1 score were greater than 80% for both IL and AMP groups when using SRKDA. Wilcoxon rank sum test was employed to verify possible differences between WL conditions. Although the latter did not show significant differences, 100 ms WL showed the best classification performances for both groups (classification accuracy greater than 90%, near that of a usable PR system). Results demonstrated that a reliable motion intent recognition of shoulder joint in transhumeral amputee patients can be obtained employing transient sEMG epochs. This can be used in a better design of myoelectric control architectures of assistive technologies, involving the upper-limb for clinical use.

EXPERIMENTAL IN HEAD TRACKING CONTROL OF A FOUR OMNI WHEELED MOBILE ROBOT SYSTEM

This article describes an experimental investigation into the head tracking and control of a four-wheeled Omni-Robot. This study described the control scheme of the omnidirectional mobile robot. Additionally, the kinematics of the mobile robot is presented., A mobile robot with four Omni wheels was also developed on real hardware to verify the controller architecture design. The robot system is modeled and then implemented with the Arduino Microcontroller. This robot has two rotary encoders for running on the x-axis and y-axis, respectively. The gyro sensor (MPU-6050) is placed in the robot's middle and tracks data obtained by yaw angle. MATLAB Simulink was used to find the PD controller based on manual adjustment. The control architecture was deployed to complete and run the experiment on the mobile robot to evaluate the outcomes. The experiment results show the robot's motion control improvement in various scenarios.

Adaptive speed and separation monitoring based on switching of safety zones for effective human robot collaboration

• Design of dynamically switched safety zones which are used to monitor human presence • Implementation of safety architecture using safety sensors, safety PLC and robot's controller • Use the status of the safety zones to adapt robot behaviour based on the signals received • Ensure safe co-existence and collaboration of human operators with industrial robots This paper presents the design and deployment of a system that enables the safe cooperation and interaction of human operators with industrial robots. Dynamically switched safety zones are used to monitor human presence and respectively adapt robot behavior, namely speed and movement status. An overhead safety camera system is used to identify moving objects within each zone and produce warning and stop signals which are used to regulate the behavior of the robot, slowing it down and stopping it respectively. Based on the real time position reporting of the robot, continuous switching between zone configurations is achieved. This leads to a more efficient speed and separation monitoring process, as defined by ISO/TS 15066, EN-ISO 10218-1 and EN ISO 10218-2, compared to a fixed fence solution. Unlike the case of virtual fences which are currently implemented using light barriers, this approach allows humans to use more workspace from the robot while ensuring separation. The control architecture design and the implementation of the system on a pilot cell inspired from the automotive industry are presented in this paper, as well..

Layered feedback control overcomes performance trade-off in synthetic biomolecular networks

Layered feedback is an optimization strategy in feedback control designs widely used in engineering. Control theory suggests that layering multiple feedbacks could overcome the robustness-speed performance trade-off limit. In natural biological networks, genes are often regulated in layers to adapt to environmental perturbations. It is hypothesized layering architecture could also overcome the robustness-speed performance trade-off in genetic networks. In this work, we validate this hypothesis with a synthetic biomolecular network in living E. coli cells. We start with system dynamics analysis using models of various complexities to guide the design of a layered control architecture in living cells. Experimentally, we interrogate system dynamics under three groups of perturbations. We consistently observe that the layered control improves system performance in the robustness-speed domain. This work confirms that layered control could be adopted in synthetic biomolecular networks for performance optimization. It also provides insights into understanding genetic feedback control architectures in nature.

Dynamic event-triggered trajectory tracking control for underactuated marine surface vessels with positive minimum inter-event time guarantees

This paper proposes a dynamic event-triggered trajectory tracking control scheme for underactuated marine surface vessels (MSVs) with positive minimum inter-event time (MIET) guarantees. Under the presented scheme, control inputs only need to transmit to actuators at the designed event triggering time. Additionally, the maximum signal transmission frequency can be prior known by designers. To facilitate the design of the above control architecture, an unified second-ordered tracking error dynamic system is firstly derived. Then, based on the transformed error dynamic system, an event-based adaptive control law is developed. To counteract external disturbances and unmodeled dynamics, the minimum-learning-parameter (MLP) based neural approximator is constructed to enhance system robustness. Finally, by introducing internal dynamic variables, a dynamic event-triggered mechanism (DETM) is established to manage communications between the control module and actuators. Compared with existing event-triggered methods, the proposed event-driven method is dynamic and more flexible to satisfy network bandwidth requirements. Besides, MIETs of the presented DETM are also proved to be strictly positive and computable from control parameters. Theoretical analysis and simulation results verify the validity and effectiveness of the proposed DETM based control scheme.

Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control

This research proposes a power system frequency control architecture which leverages a rising open protocol for charge rate control of electric vehicles: Open Charge Point Protocol. Unlike conventional research that focused on building a high-performance controller, this research puts emphasis on the architecture. Specifically, this research explores the design of the frequency control architecture around a basic functionality of an open protocol while allowing substantial performance to mitigate the need for a well-tuned specialized protocol. As the usage of open protocols cannot provide a quick response, the proposed architecture alleviates this limitation by (a) utilizing a hierarchical and asynchronous structure to emulate a faster control interval and (b) providing a model predictive controller with system integrity protection scheme behavior to have sufficient performance under both large and small disturbances. The overall architecture is tested against an aggregated power system frequency response model on Simulink for both large and small disturbances. Compared to a tuned proportional integral derivative controller on the same architecture, the proposed architecture observed an average reduction of 21.77% in nadir in the step disturbance test and an average reduction of 36.27% in standard deviation from the nominal frequency in the load variation test.

Designing a Pipeline for Predicting Power Grid Stability with Artificial Neural Network (ANN)

Renewable energy sources are becoming more popular, providing a much-needed alternative to traditional, limited, and climate-unfriendly energy sources. Wireless sensors, cloud computing, cyber security, and wide-area monitoring are basic communication and control technologies for smart grid applications. Design of communication and control architectures for the adoption of smart energy grids for rural loads and distributed energy, including energy storage solutions. In this work, a Machine Learning module called scikit-learn is used for pre-processing of labeled input data by using StandardScaler, KFold for cross-validation, and Confusion matrix for measuring performance. Also, the ML technique uses the binary classification method to divide the ‘stabf’ data into two parts as stable and unstable. Here deep learning-based Artificial Neural Network (ANN) has been used to evaluate the result and to predict new grid data to enhance stability. ANN takes 12 input nodes in the input layer and three hidden layers out of which two hidden layer takes 24 nodes and another one takes 12 nodes and an output layer consisting of a single node. Adam optimizer has been used for model compilation and loss function calculation ‘binary_crossentropy’ is used. Finally, after successful completion of the evaluation process, this model gives a test accuracy result of 98.33%.

Robust controller design for rotary inverted pendulum using H∞$H\infty$ and μ$\mu$‐synthesis techniques

An H ∞ $H\infty$ controller is designed to control a rotary inverted pendulum in its upright equilibrium position. The key contribution of this work is a robust controller architecture design to accommodate for uncertainty in actuator model. Robust stability and performance for a given degree of actuator and measurement uncertainty is achieved using the well established techniques of μ $\mu$ -synthesis and H ∞ $H\infty$ robust control methods. The design focuses on stabilizing an Inverted Pendulum in an upright position within a tolerable desired angle margin ( α $\alpha$ ). A dynamic plant is designed based on already established theories and published papers. It is observed that the plant is completely observable for the pendulum angle and the motor arm link angle. These two signals are also measurable via encoders and is used as an input for the controller. The output of the controller is voltage actuation which drives the motor to stabilize the pendulum in an upright position (= 0 with +/− 10 deg tolerance). A Robust Stability analysis is done along with Robust Performance, to study the stability and performance margins under modelled uncertainties. As a comparative study, a rudimentary pole placement method is also analyzed.

Design and Numerical Implementation of V2X Control Architecture for Autonomous Driving Vehicles

This paper is concerned with designing and numerically implementing a V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) control system architecture for a platoon of autonomous vehicles. The V2X control architecture integrates the well-known Intelligent Driver Model (IDM) for a platoon of Autonomous Driving Vehicles (ADVs) with Vehicle-to-Infrastructure (V2I) Communication. The main aim is to address practical implementation issues of such a system as well as the safety and security concerns for traffic environments. To this end, we first investigated a channel estimation model for V2I communication. We employed the IEEE 802.11p vehicular standard and calculated path loss, Packet Error Rate (PER), Signal-to-Noise Ratio (SNR), and throughput between transmitter and receiver end. Next, we carried out several case studies to evaluate the performance of the proposed control system with respect to its response to: (i) the communication infrastructure; (ii) its sensitivity to an emergency, inter-vehicular gap, and significant perturbation; and (iii) its performance under the loss of communication and changing driving environment. Simulation results show the effectiveness of the proposed control model. The model is collision-free for an infinite length of platoon string on a single lane road-driving environment. It also shows that it can work during a lack of communication, where the platoon vehicles can make their decision with the help of their own sensors. V2X Enabled Intelligent Driver Model (VX-IDM) performance is assessed and compared with the state-of-the-art models considering standard parameter settings and metrics.

Offset-Free Model Predictive Control for a cone-shaped active magnetic bearing system

Active Magnetic Bearings (AMB) are mechatronic systems that support a rotating shaft using magnetic levitation. The standard AMB architecture includes two radial actuators and one for the axial direction. An alternative geometry with cone-shaped magnetic cores allows for a more compact layout without a dedicated axial actuator. However, this configuration reduces the axial force generation capability and requires a more complex control architecture due to the inherent coupling of the axial and radial control actions. When using decentralized control, effective handling of the coil current limitations together with the axial disturbance rejection is difficult to achieve. In this context, the present paper demonstrates the benefits of applying Offset-Free Model Predictive Control (OF-MPC) for a cone-shaped AMB system. A procedure for the overall design is presented and supported by the experimental work conducted in a scaled machine that reproduces an on-board turbo-compressor unit for an aircraft. The modeling of the system is described together with the design of the OF-MPC in all its parts: general control architecture, disturbance model and observer design, target calculation and control problem formulation. An OF-MPC variant with reduced control horizon is proposed and implemented in real time. Experimental results demonstrate that the prototype is compliant with application-specific stability requirements from the ISO 14839-3:2006 standard. In addition, experiments show that OF-MPC outperforms decentralized PID controllers in terms of axial disturbance rejection. OF-MPC yields a favorable constrained optimal control technique for cone-shaped AMBs because intrinsic coupling and current saturation are optimally handled by the controller.

Autonomous Raman amplifiers in multi-band software-defined optical transport networks

A controller architecture for managing multi-band Raman amplification within software-defined optical transport networks is presented. In the perspective of optical fiber network softwarization and disaggregation, this work provides an operative description of a system capable of autonomously handling Raman amplification on a single fiber span, achieving the working point requested by the control plane in terms of mean gain and tilt. The developed architecture is composed of two software modules: the Raman design unit (RDU) and the Raman controller unit (RCU). First, the RDU defines the nominal optimal working point designing the power level configuration of the Raman card pumps according to the required amplification constraints without considering any channel spectral load. Then, due to the telemetry feedback, the RCU performs a tracking operation of the mean gain towards the target one, linearizing the problem at the nominal optimal working point. The fiber physical parameters needed by the controller for correct operation of the system are extracted through a conceived probing procedure. The proposal shows a high degree of adaptability of the defined Raman amplifier to the particular in-field scenario in which it is deployed, also counteracting spectral load modifications. The behavior of the described system is validated by means of an experimental session, confirming the effectiveness of the controller architecture design and the high accuracy achieved in terms of performance.

Non-centralised control strategies for energy-efficient and flexible manufacturing systems

The manufacturing industry is transforming towards smart, energy-efficient, and flexible manufacturing systems. In this regard, this work deals with the design of non-centralised control architectures to improve the energy efficiency of such systems and to promote their flexibility. Based on both the configuration of manufacturing systems and their coupling dynamics, these systems are divided into sub-systems, from which smaller control problems can be stated. Thus, control/management strategies can also be modularised to confer more flexibility to manufacturing systems. Then, by using suitable distributed optimisation techniques, and properly defining the consensus stages among the local controllers, the outputs from such controllers are optimally coordinated to minimise the total energy consumption of the whole system. The proposed control strategies are tested in simulation for a typical process line of automotive parts manufacturing industry, in which the main processing units are machine tools. Based on the obtained results, manufacturing systems and their control strategies could be suitably modularised using non-centralised control schemes, from which a closed-loop performance similar to its centralised counterpart can be achieved.

Adaptive control for linear parameter-varying systems with application to a VTOL aircraft

As a systematic method for gain-scheduling, the linear parameter-varying (LPV) system framework has been widely used for the design of aerospace control systems with large operating envelopes. This paper presents design and analysis of an adaptive control architecture for LPV systems subject to time-varying parametric uncertainties and external disturbances, with both transient and steady-state performance guarantees. We introduce new tools relying on parameter-dependent Lyapunov functions and linear matrix inequality techniques for stability and performance analysis. These tools – limited to linear systems – potentially yield less conservative results than the approach employed for this architecture in previous adaptive control literature based on the small-gain theorem. The transient and steady-state performance of the adaptive closed-loop system, in terms of input and output signals, is quantified with respect to a non-adaptive reference system that depends on the true values of the uncertainties and represents the best achievable performance. It is shown that the transient performance bounds can be made arbitrarily small in the case of zero initialization error for the state predictor and will include additional exponentially decaying terms in the presence of non-zero initialization error. The approach can be used to design an adaptive augmentation of a baseline LPV control system. A simulation example of the longitudinal dynamics of a conceptual Urban Air Mobility aircraft is used to illustrate the efficacy of the proposed framework.

Design and Experiment of Control Architecture and Adaptive Dual-Loop Controller for Brake-by-Wire System With an Electric Booster

Brake-by-wire (BBW) is a critical technology in modern automotive and lays a solid foundation for intelligent vehicles. A control strategy to take full advantage of this system both in the active brake and the conventional boosting brake is essential for the BBW system, which is a challenging issue because of its complex structure and high requirement for rapid dynamic response and control accuracy. To get satisfying performance and control effect, this article designs a new type of electric booster installing on the electrohydraulic brake (EHB) system that can realize active brake control and brake boosting simultaneously, and then, a synthetic control architecture special for this system is put forward. First, the system principle and detailed modeling are given. Then, an adaptive dual-loop brake pressure control approach is proposed where a modified PID controller is used as the outer control loop to track the desired pressure and an inner loop named adaptive current control is employed to guarantee the brushless direct electric motor (BLDC) performance of tracking current considering the parametric variation and system uncertainties. Besides, the stability of the inner loop control is proven. Meanwhile, a user-defined brake-boosting framework is designed to realize the electric boosting brake. Simulation and experimental validation are implemented to demonstrate the feasibility of the system and the effectiveness of the control strategy design eventually, manifesting that the proposed BBW system and its control strategy can obtain satisfying performance.

Nonlinear robust adaptive control of an airplane with structural damage

This article investigates the design of a novel nonlinear robust adaptive control architecture to stabilize and control an airplane in the presence of left-wing damage. Damage effect is modeled by considering the sudden mass and inertia changes, center of gravity, and aerodynamic variations. The novel nonlinear control algorithm applies a state predictor as well as the error between the real damaged dynamics and a virtual model based on the nominal aircraft dynamics in the control loop of the adaptive strategy. The projection operator is used for the purpose of robustness of the adaptive control algorithm. The stability of the proposed nonlinear robust adaptive controller is demonstrated applying the Lyapunov stability theory. The performance of the proposed controller is compared with two previous successful algorithms, which are implemented on the Generic Transport Model airplane to accommodate wing damage. Numerical simulations demonstrate the effectiveness and advantages of the proposed robust adaptive algorithm regarding two other algorithms of adaptive sliding mode and L 1 adaptive control.

Event-based state-space model predictive control of a renewable hydrogen-based microgrid for office power demand profiles

This paper focuses on the design and implementation of an event-based control architecture to manage a renewable-based microgrid. This microgrid has renewable-energy generation and a hybrid energy storage system that uses electricity and hydrogen. The main load of the microgrid is the energy demand of an office. The primary control objective is to satisfy this load using the available renewable generation and stored energy while reducing the amount of energy purchased from the Utility Power Grid and the degradation of the electromechanical storage devices. To do that, the control architecture defined within an event framework, makes use of a set of state-space model predictive controllers which are selected as a function of a variable sampling period. To evaluate the performance of the proposed architecture, simulation tests for a summer day as well as an analytical study is performed. The obtained results show that the use of the event-based control architecture allows a significant reduction of the number of changes in the control action at the expense of an acceptable deterioration of set-point tracking for a microgrid with several types of electrochemical storage.

Design and Development of a New Control Architecture for Elliptically Polarizing Undulators at the Taiwan Photon Source

During the phase-II beamline project at the Taiwan Photon Source (TPS), elliptically polarized undulators (EPU), called EPU66 and EPU168, will be installed in 2020. The new control system for the EPUs is based on the Experimental Physics and Industrial Control System (EPICS) and Ethernet Control Automation Technology (EtherCAT) framework. The EPU control elements include: motors with absolute optical encoders for gap and phase control, corrector magnets power supply control for trim coils, interlock safety systems to automatically stop motion based on encoder readings, limit switches, tilt sensors and emergency buttons. All control functionalities are coordinated by a fan-less embedded computer with three Ethernet ports. User interface for operators and beamline users are included to support the operation of the system, such as gap/phase control. Reliable operation of the EPU is important to users of beamlines. The most unpredictable fault is due to a soft error in the absolute optical encoders. There are several protection solutions to avoid faults, e.g., by increasing the distance of the encoder from the beam center, by a lead shield cover and finally by adopting an auxiliary position sensing device to cross check the position and perform the necessary procedure. Efforts to improve operational reliability of the EPU controls will be discussed. Features and benefits of the EPU66 and EPU168 control system will be summarized in this report.

Control Technology Needs for Electrified Aircraft Propulsion Systems

Abstract Electrified aircraft propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn, emissions, and noise. Currently, NASA and other organizations are actively working to identify and mature technologies necessary to bring EAP designs to reality. This paper specifically focuses on the envisioned control technology challenges associated with EAP designs that include gas turbine technology. Topics discussed include analytical tools for the dynamic modeling and analysis of EAP systems, and control design strategies at the propulsion and component levels. This includes integrated supervisory control facilitating the coordinated operation of turbine and electrical components, control strategies that seek to minimize fuel consumption and lessen the challenges associated with thermal management, and dynamic control to ensure engine operability during system transients. These dynamic control strategies include innovative control approaches that either extract or supply power to engine shafts dependent upon operating phase, which may improve performance and reduced gas turbine engine weight. Finally, a discussion of control architecture design considerations to help alleviate the propulsion/aircraft integration and certification challenges associated with EAP systems is provided.