Reconfigurable Control System Research Articles

Full cycle on-line autonomous reconfiguration of MIMO control system based on REGA pairing principle for heat exchanger networks

This study presents a novel autonomous reconfiguration strategy to achieve full cycle optimal control of the heat exchanger networks. The proposed method aims to select the optimal control structure online to solve the problem of slow time-varying process transition caused by the inevitable fouling accumulation. An auxiliary variable is introduced to increase the degree of control freedom, and a flexible control structure is studied to provide appropriate pairings dynamically between variables. Subsequently, the nonparametric Relative Energy Gain Array (REGA) is considered to form the switching mechanism that determines the switching instants and variable pairing modes between control loops. Furthermore, the online optimization of switching regions ensures the optimal control performance. Finally, one typical experiment for the heat exchanger network in crude distillation unit was conducted and the results illustrated the effectiveness of the proposed control method. Compared with the conventional control system, the available service time is extended by nearly 18 months, and there is still room for further adjustment.

Reconfiguration Incremental Control Allocation for Tailless Aerial Vehicle with Control Surface Faults

To address the faults of the tailless aerial vehicle control surface with nonlinear control effectiveness, a reconfiguration incremental control allocation method is proposed. Under the framework of incremental control allocation, four types of typical control surface faults, such as floating, jamming, damaged, and median offset, are modeled. The isolation of faulty control surfaces and the reconfiguration of the flight control system is realized by adjusting the control surface deflection increment limit and changing the local control effectiveness matrix. The results show that the method can effectively take advantage of the redundant configuration of the control surface, prevent the system from losing control caused by the fault of the control surface, and enhance the safety and reliability of the system.

Real-Time Sensor Fault Identification and Remediation for Single-Phase Grid-Connected Converters Using Hybrid Observers With Unknown Input Adaptation

Unexpected faults that occur in the sensors of the single-phase grid-connected converter (SGC) may deteriorate the control performance ofthe grid current and dc-link voltage and pose risks to the connected distributed generation system. This article proposes an unknown input sliding mode observer (UI-SMO) based sensor fault identification and remediation strategy. Therein, an UI-SMO is established that integrates the observations of the grid current and dc-link voltage with the reconstruction of the unknown input (i.e., load condition of the SGC). Such an observer-based analytical redundancy generates the residuals that indicate the abnormalities of the sensors for fault identification. An adaptive fault-tolerant control (AFTC) strategy for the SGC is developed, where an automated control system reconfiguration with unknown input adaptation is seamlessly implemented by substituting the data reported by the faulty sensors with their observed values. Extensive simulation and experimental studies validate the effectiveness of the proposed UI-SMO-based sensor fault identification and AFTC strategy of the SGC.

RLReC: Towards Reinforcement Learning-based Dynamic Design of Reconfiguration Control

The design of Reconfigurable Control Systems (RCS) is a tremendous task since that their increasing need for reconfiguration imposes the anticipation of all potential runtime changes at design time, which is in most cases infeasible. To deal with the high dynamicity of RCS at design-time we propose a novel design approach, RLReC (Reinforcement Learning-based Reconfiguration Control) allowing for the improvement of reconfiguration knowledge through online (runtime) exploration. This approach combines the benefits of meta-modelling with Reinforcement Learning (RL) principals for reconfiguration knowledge modelling in order to handle early and effective exploration of various design choices. In this work, the reconfiguration controller is an autonomous software agent designed as a RL agent (RLRA) that handles both offline (exploitation) and online (exploration) learning through interactions with the controlled system at runtime. In particular, the RLRA has to select reconfiguration rules that were not selected before, which is known as exploration. The main aim of this proposal is to cope with design-time unplanned changes by giving the RLRA the ability of improving its knowledge through online learning feedback. We illustrate the use of our contributions with a running example from the manufacturing domain.

Online control system reconfiguration towards long period energy-saving optimization of heat exchanger networks

For the long period operation of a heat exchanger network, the slow time-varying fouling problem is one of the most critical problems, which seriously affects the sustainable energy saving and continuous controllability. Although the control systems are designed to maintain the varied operation requirements, the conventional designed control systems based on the given operation requirements might result in the control system unsustainable due to the lack of freedom. In this work, a long period optimization based on online control system reconfiguration is proposed. Firstly, to keep control during the long period, a reconfiguration control structure is studied. Secondly, the design of online reconfiguration optimization is proposed to ensure the control and optimization process is continuously adjusted. At the same time, the relationship between manipulated variables is studied and the margin is fully utilized. In addition, an optimal control structure is designed to guarantee the implementation of the method. Consequently, the results demonstrated that the proposed method can not only realize long period energy saving, but also meet the requirements of continuous controllability. Meanwhile, the cumulative consumption of fluid flow in Light Vacuum Circle Oil steam is reduced by 4.24×106kg. The robustness of the system was also verified.

Real-Time Vision-Based Aircraft Vertical Tail Damage Detection and Parameter Estimation

The need for reliable, fast, and accurate detection of fault is the key to fault-tolerant control reconfiguration of any flight control system. It is known that faults such as structural damage greatly modify the aerodynamic characteristics, often represented by stability and control derivatives. They also result in abrupt deterioration of flight performance and handling quality, which impairs safety. Since no detection technique is as reliable and fast as the Human Visual System (HVS), this paper demonstrates how popular vision algorithms such as edge detection and structural similarity index can be used for real-time detection of vertical tail damage of a fighter aircraft. A novel geometric method is proposed for fault identification using traditional mathematical geometry. Empirical techniques are used for the estimation of stability and control derivatives to generate a mathematical model of damaged aircraft instead of relying on expensive wind tunnel data. Flight mechanics analysis of the data generated confirms the effects of vertical damage in terms of reduction of static and dynamic directional stability and its control effectiveness. The parametrized state matrix thus obtained for the given flight condition thus leads to efficient real-time control reconfiguration of a damaged aircraft for safe recovery. The importance of this paper lies in using the established techniques of image processing for fault detection of damaged aircraft and parametrization for subsequent control reconfiguration, which is a novel application.

Integrated design of fault-tolerant control for flight control systems using observer and fuzzy logic

PurposeFault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated approach for aircraft fault-tolerant control.Design/methodology/approachThe integrated structure includes a Kalman filter to obtain without noise, a full order observer for sensor fault detection, a GOS (generalized observer scheme) for sensor fault isolation and a fuzzy controller to reconfigure of the healthy sensor. This combination is simulated using the state space model of a lateral flight control system in case of disturbance and under sensor fault scenario.FindingsUsing a dedicated observer scheme, the detection and time of sensor fault are correct, but the sensor fault isolation is evaluated incorrectly while the faulty sensor is isolated correctly using GOS. The simulation results show that the suggested approach works affectively for sensor faults with disturbance.Originality/valueThis paper proposes an integrated approach for aircraft fault-tolerant control. Under this framework, three units are designed, one is Kalman filter for filtering and the other is GOS for sensor fault isolation and another is fuzzy logic for reconfiguration. An integrated approach is sensitive to faults that have disturbances. The simulation results show the proposed integrated approach can be used for any linear system.

Реконфигурация системы регулирования температуры газосырьевой смеси на выходе печи установки каталитического риформинга по данным эксплуатации технологического объекта

Представлены подход и результаты эксперимента по реконфигурации системы автоматического управления и расчета комбинированной системы управления на основе предложенной концептуальной модели идентификации технологических объектов по данным их эксплуатации. Приведены результаты исследования подхода для системы автоматического управления температурой потока газосырьевой смеси установки каталитического риформинга.

МОДЕЛИ И МЕТОДЫ ПРОЕКТИРОВАНИЯ ДИНАМИЧЕСКИ РЕКОНФИГУРИРУЕМОЙ СИСТЕМЫ ГРУППОВОГО УПРАВЛЕНИЯ МОБИЛЬНЫМИ РОБОТАМИ

High adaptability is an important requirement for the control system over a group of mobile robots operating in a nondeterministic changing environment. The group control system must ensure that the group task is completed when the structure of the group or the environment changes. Such adaptability can be achieved through dynamic reconfiguration of the control system. The article discusses the mathematical models of a dynamically reconfigurable system from the standpoint of computer-aided design. A review of mathematical models of variable structure system, reconfigurable control systems and their design methods is presented. The paper deals with set-theoretic, analytical, discrete-event models of variable structure systems and methodologies of designing reconfigurable systems. It is shown that the existing design methods do not fully provide the required adaptability of designed group control system. The paper compares the group control system and the reconfigurable multiprocessor computing system and shows how to increase adaptability and autonomy of designed control system using principles of reconfigurable computing systems designing.

Algorithmic Support of Adaptive Automatic Control Systems with Data Compression

Introduction. The exponential growth of measurement information caused by ongoing complication of technical and production facilities necessitates the development of improved or brand new information and measurement systems, including those performing adaptive automatic control functions. Automatic criteria-based selection and reduction of measurement information continuously supplied by multi-parameter sources characterizing the objects under study require algorithms ensuring reconfiguration of automatic control systems during operation. In comparison with automatic control systems based on time-division channelling, the considered adaptive systems provide timely information on the pre-emergency and emergency operation of a facility.Aim. To develop an algorithmic support for adaptive automatic control systems using asynchronous-cyclic and parallel-sequential operating algorithms, as well as to compare the proposed algorithms in terms of their, control reliability, compression ratio, operation speed and the error associated with multi-channelling.Materials and methods. The algorithms proposed for supporting the operation of adaptive systems were developed on the basis of queuing theory and simulation modelling using the MatLab/Simulink programming languages, C++.Results. The developed algorithmic support for automatic control systems based on asynchronous-cyclic analysis of deviations allows the amount of redundant information to be reduced by more than 4 times and the operation speed to be increased by 1.5 times. The developed algorithmic support for automatic control systems based on parallel-sequential analysis of deviations allows the error associated with multi-channelling to be reduced by 1.4 times, thereby bringing the control reliability of such systems closer to that of continuous-control systems. An analysis of the graphs of the error associated with multi-channelling showed that the automatic control systems based on parallel-sequential operational algorithms are invariant to the law of distribution of input quantities, compared to the systems based on asynchronous-cyclic operational algorithms.Conclusions. The proposed algorithmic support can significantly decrease the redundancy of information and improve the metrological characteristics of automatic control systems. The use of the developed algorithms in automatic control systems based on time-division channelling render their control reliability comparable with that of continuous-control systems.

Approach to Reconfiguration of a Motion Control System for an Autonomous Underwater Vehicle

Reconfiguration of a motion control system (MCS) for an autonomous underwater vehicle (AUV) in case of failure of some of the controls or actuators that provide the vehicle propulsion and maneuvering is discussed. The features of actuators operating on different physical principles are analyzed. A nonlinear mathematical model of the vehicle motion is formed taking into account the features of the seawater medium due to higher viscosity. Nonlinearity does not allow traditional approaches to reconfiguration of aircraft motion control system to be used for the purposes described in this paper. The approach proposed for reconfiguration of the AUV MCS consists in the preliminary analysis of the conditions for using different kinds of actuators depending on the vehicle speed and maneuver. The choice of alternative efficient actuators is dictated by the need to compensate for the forces and moments generated by the failed equipment or the actuator to the maximum extent possible. The results of the AUV MCS reconfiguration are obtained for a failure of a bow rudders gear during the diving maneuver on the acceleration section of the path. Vertical thrusters are taken as backups capable of compensating for the forces and moments of the jammed bow rudders gear. The comparative quantitative estimates of the AUV MCS reconfiguration were obtained by mathematical simulation of the AUV diving maneuver. Further research is needed to extend the proposed approach to other AUV systems.

Подход к реконфигурации системы управления движением автономного необитаемого подводного аппарата

Подход к реконфигурации системы управления движением автономного необитаемого подводного аппарата

Postcapture Attitude Takeover Control of a Partially Failed Spacecraft With Parametric Uncertainties

The postcapture of a partially failed spacecraft by space manipulators will bring a mutation in the dynamics of the combination. Both the inertia properties and the thruster configuration matrix will change significantly. The unknown dynamics of the partially failed spacecraft also cause a tremendous technical challenge for attitude takeover control. Accordingly, this paper describes a novel reconfigurable control system for postcapture attitude takeover of a partially failed spacecraft with parametric uncertainties, whose fuel has been exhausted or whose actuators have partial malfunctions. First, the reconfigurable control law is designed by command filtering adaptive back-stepping control to guarantee the system performance and global asymptotic stability considering inertia parametric uncertainties. Second, the thrusters are reconstituted, without changing the thruster physical configuration. Finally, the thrusters' forces can be redistributed by the dynamic control reallocation method based on constrained quadratic programing. Numerical simulations validate the feasibility of the proposed approach for postcapture attitude takeover control of a partially failed spacecraft with parametric uncertainties. Note to Practitioners-This paper presents a methodology for a partially failed spacecraft with parametric uncertainties. It focuses on solving the attitude takeover control of the partially failed spacecraft perfectly, while considering the position and speed constraints of the actuator and avoiding the plume impact to the spacecraft. The proposed command filtering adaptive back-stepping control can be used for spacecraft's thruster reconfiguration considering the parametric uncertainties. Furthermore, the dynamic control reallocation method is particularly useful for future applications that include spacecraft with redundant actuators.

On-orbit Reconfiguration Using Adaptive Dynamic Programming for Multi-mission-constrained Spacecraft Attitude Control System

For the on-orbit reconfiguration problem of spacecraft attitude control systems under multi-mission constraints, the idea of a reinforcement-learning algorithm is adopted, and an adaptive dynamic programming algorithm for on-orbit reconfiguration decision-making that is based on a dual optimization index is proposed. Two optimization objectives, total mission reward and total control cost (energy consumption), are defined to obtain the optimal reconfiguration policy of the spacecraft attitude control system reconfiguration, and the on-orbit reconfiguration model for multi-mission constraints is established. Then, based on the Bellman optimality principle, the optimal reconfiguration policy formulated by the discrete HJB equation is obtained. Since the HJB equation is difficult to solve accurately, a method of bi-objective adaptive dynamic programming is proposed to obtain the optimal reconfiguration policy. This method constructs a mission network and an energy network. The method then adopts a Q-learning-based algorithm to train the networks to estimate the values of total mission reward and total control cost to achieve the on-orbit optimal reconfiguration decision under multi-mission constraints. Simulation results for different cases demonstrate the validity and rationality of the proposed method.

Ontology-based Manufacturing Control Systems (MCS)

Programmable Logic Controller (PLC) is a typical control kernel for manufacturing automation, especially in the era of Industry 3.0. Centralized control architecture of PLC with an ease of maintenance has been widely applied in many arenas for automation. However, PLC’s centralized structure is becoming incapable to handle the control requirements of smart factories in Industry 4.0, within which are full of diverse sensors and actuators, not to mention its incapability of expansion and flexibility.OWL (Ontology Web Language) is a language representing knowledge in the format of ontology, whereas ontology is formal way to describe taxonomies and classification networks. Compared to the traditional program control system, system with OWL is ease of modification and expansion. By taking advantages of OWL into manufacturing control system, this research develops a manufacturing ontological knowledge model. Because of the system is built based on Jena package, SPARQL as a knowledge query language will be easily deployed to demonstrate the flexibility, robustness, and re-configurability of an ontology-based manufacturing control system to the environmental disturbances.

RECONFIGURATION OF THE AIRCRAFT INTEGRATED CONTROL SYSTEM REGARDING CONTROL CONSTRAINTS UNDER ACTUATOR FAILURES

The aircraft integrated control system reconfiguration laws under failures of actuators, calculated disregarding physical constraints on control surfaces saturation, can lead to a complete loss of aircraft controllability and stability. Despite the large number of scientific publications in this field, practical systematic results have been obtained only for SISO (single input – single output) systems. Problems of the convergence of iterative algorithms restricting the set of admissible solutions and the conservatism of the reconfiguration laws designed using weight matrices do not allow solving this problem in general. For complex MIMO (multi input – multi output) systems there is still no widely accepted universal approach. In this work, control surfaces constraints are regarded in terms of the power of reconfiguration control. It is shown that by slight modification of pseudoinverse (optimal) solution it is possible to obtain approximate pseudoinverse (suboptimal) solutions with priory known minimum power (compensation matrix norm) and error (residual matrix norm) of the reconfiguration for a given degree of approximation. This allows for a multistep consistent reduction in power and increasing in error of reconfiguration, until an acceptable solution is obtained. By providing the greater reconfiguration error at each step we have additional freedom in reducing the reconfiguration power. This leads to a decrease in the amplitude of the deviations of the control surfaces, to which the signals from the failed control channels are redistributed. The simulation example of the aircraft integrated control system reconfiguration under the stabilizer’s actuator failure is presented. It is shown that the pseudoinverse reconfiguration problem solution leads to the significant ailerons’ constraints violation and the loss of aircraft controllability. Regarding control constraints solution reduces several times the deviation of the control surfaces and provides an effective problem solution in the permissible power and error reconfiguration range.

Design and Characterization of a Trailer-Based Horizontal-Axis Wind Turbine Test Rig

This paper presents a mobile testing rig developed for small wind turbine (SWT) experimental work to orchestrate, cost-effectively, turbine performance characterization in both controlled wind inflow speeds and turbulent ambient flows. It facilitates off-grid testing of up to a 1 kW wind turbine. It is a dual-purpose machine that can be towed behind a vehicle to conduct steady-state tests (track testing) or be parked to collect unsteady field data (field testing), all with the same rotor and instrumentation. Its mechanical design included computational fluid dynamics (CFD) analysis to gauge the potential impact of towing vehicle disturbance on the free stream available to the rotor. To provide a compelling platform for full rotor speed control, a reconfigurable control system coupled to an electric vehicle controller with regenerative braking technology has been modeled and implemented into its electrical design. Uncertainty analysis has also been rigorously conducted to project the error bounds pertaining to both precision and bias components of the testing results. The rig has been tested in a towed scenario and blade element momentum (BEM) simulations have been compared with the actual aggregate performance curves obtained experimentally. Future work involves testing in unsteady winds, for which the rig was ultimately designed in order to better understand unsteady rotor performance and adaptive design.

Combining Semi-Formal and Formal Methods for the Development of Distributed Reconfigurable Control Systems

This research paper deals with combining semi-formal and formal methods to develop distributed reconfigurable control systems. The reconfiguration consists in modifying the system behavior to adapt it to the changes in its related environment caused by user needs and operating constraints. A DRCS which consists of networked reconfigurable control systems (RCSs), is a set of functional operations such that only a subset is executed by adding or removing operations after a well-defined reconfiguration scenario. To dynamically handle reconfiguration scenarios at run-time, a defined multi-agent architecture is proposed and affects a reconfiguration agent (RA) for the local reconfiguration of each RCS and a global coordination agent to harmonize the different RCSs for a required coherence. To provide a documented and safe reconfigurable system, we propose a new methodology called DRec-UML-B that covers all software development phases from modeling and verification to code generation using UML and B. The DRec-UML-B development process consists of two complementary phases: UML specification and B specification. In the first phase, we model the different agents with UML to specify the static and dynamic aspects of the DRCS. The second phase translates the UML specification to obtain the B abstract model using defined DRec-rules and reduces the number of operations to be transformed from a UML class diagram to B ones. Then, we apply successive refinements to obtain the C code and we check the system using Atelier B and Check R-B tools for the consistency and accuracy of the specification, refinement, and code generation levels to avoid the redundant control of B machines that share similar sequences of operations. We apply all the proposed contributions to two benchmark production systems FESTO and EnAS to discuss the benefits of DRec-UML-B methodology in terms of the number of generated B operations.

Dynamic Partial Reconfiguration of Concurrent Control Systems Specified by Petri Nets and Implemented in Xilinx FPGA Devices

This paper proposes a novel design concept of concurrent control systems specified by interpreted Petri nets and implemented in Xilinx FPGA devices. The technique is oriented on further dynamic partial reconfiguration of the system. An adequate splitting algorithm of the system into the dynamic (reconfigurable) and static (non-reconfigurable) partitions is proposed. The main advantage of the presented idea is the possibility of the dynamic reconfiguration of the already implemented system. It means that the functionality of the selected component (module) of the controller can be changed, while the rest of the system is still running. The presented technique is illustrated by a real-life case-study example, and it has been verified experimentally with the application of Xilinx FPGA device.

Distributed Sensor and Actuator Reconfiguration for Fault-Tolerant Networked Control Systems

In this paper, we address the problem of distributed reconfiguration of networked control systems upon the removal of misbehaving sensors and actuators. In particular, we consider systems with redundant sensors and actuators cooperating to recover from faults. Reconfiguration is performed while minimizing a steady-state estimation error covariance and quadratic control cost. A model-matching condition is imposed on the reconfiguration scheme. It is shown that the reconfiguration and its underlying computation can be distributed. Using an average dwell-time approach, the stability of the distributed reconfiguration scheme under finite-time termination is analyzed. The approach is illustrated in a numerical example.