Reconfigurable Control Research Articles

Adaptive Fault-Tolerant Control and Performance Recovery Against Actuator Failures With Deferred Actuator Replacement

In this article, an adaptive fault-tolerant control (FTC) scheme is proposed for a class of uncertain nonlinear systems with actuator failures, in which a backup actuator is available. Different from existing FTC methods applying dynamic redundant actuators, a situation of deferred actuator replacement is firstly taken into account, i.e., the backup one cannot connect to plant right after failure detection. To recover the tracking error into prescribed performance within a specified time, an error transformation is introduced to render tangent barrier Lyapunov functions valid at the replacement instant, by which reconfigurable controller can be designed for the backup actuator. Simulation results on a flight control system are presented to illustrate the effectiveness of the FTC scheme.

Online Reconfiguration of Distributed Robot Control Systems for Modular Robot Behavior Implementation

The use of autonomous robots in areas that require executing a broad range of different tasks is currently hampered by the high complexity of the software that adapts the robot controller to different situations the robot would face. Current robot software frameworks facilitate implementing controllers for individual tasks with some variability, however, their possibilities for adapting the controllers at runtime are very limited and don’t scale with the requirements of a highly versatile autonomous robot. With the software presented in this paper, the behavior of robots is implemented modularly by composing individual controllers, between which it is possible to switch freely at runtime, since the required transitions are calculated automatically. Thereby the software developer is relieved of the task to manually implement and maintain the transitions between different operational modes of the robot, what largely reduces software complexity for larger amounts of different robot behaviors. The software is realized by a model-based development approach. We will present the metamodels enabling the modeling of the controllers as well as the runtime architecture for the management of the controllers on distributed computation hardware. Furthermore, this paper introduces an algorithm that calculates the transitions between two controllers. A series of technical experiments verifies the choice of the underlying middleware and the performance of online controller reconfiguration. A further experiment demonstrates the applicability of the approach to real robotics applications.

Multi-objective optimal formation reconfiguration with scalarization and stochastic boundaries

Abstract A new method is proposed for multi-objective optimal control of satellite formation reconfiguration. First, necessary optimality conditions of single-objective fuel-optimal reconfiguration are studied. Problem of initial guess of the costate and control discontinuity are addressed by using a new developed stochastic based method. Terminal conditions of Two Point Boundary Value Problem (TPBVP) of the optimal control equations are relaxed using augmented Gaussian. Variances or bandwidths of the terminal conditions are set to decision variables to be optimized. Responses of varied initial costate are modeled and propagated using Riccati equation. Using quadratic convolution of relaxed terminal conditions, objective function of the fuel-optimal problem is reformulated into a quadratic equation, and a gradient based optimizer is used to search the optimal initial guess. In the second part of the paper, optimal control of format flying reconfiguration with two competitive objectives:fuel and time of flight (ToF) is studied. With Pascoletti-Serafini scalarization, the Multi-objective Optimal Control Problem (MOCP) is scalarized into a set of weighted Single-objective Optimal Control Problems (SOCP). Hamiltonian and switch function for the weighted SOCP are developed and constructed. New developed stochastic based approach is then used to search the optimal Pareto solutions. Verification and performances of proposed algorithms are demonstrated through numerical simulations of single-objective and multi-objective optimal control of low-thrust elliptical orbit formation reconfiguration. Potential applications of the algorithms to some other preliminary space mission designs are also discussed.

A Neural Adaptive Approach for Active Fault-Tolerant Control Design in UAV

Faults in aircraft actuators can cause serious issues in safety. Due to the autonomous nature of the unmanned aerial vehicles (UAVs), faults can lead to more serious problems in these systems. In this paper, a new active fault tolerant control (FTC) system design for an UAV is presented. The proposed design uses a neural network adaptive structure for fault detection and isolation (FDI), then, the FDI signal combined with a nonlinear dynamic inversion technique is used to compensate for the faults in the actuators. The proposed scheme detects and isolates faults in the actuators of the system in real-time without the need of controller reconfiguration in presence of faults in the actuators. The simulation results of the designed FTC system when it is applied to WVU YF-22 UAV show that the proposed design can successfully detect and isolate the faults and compensate for their effect.

Fault tolerant-based virtual actuator design for wide-area damping control in power system

The objective of this article is to enhance the wide-area damping control of a large power system against actuator faults. In specific, damping of low-frequency system oscillations is carried out through centralized MIMO-based dynamic feedback controller (DFC). This particular approach requires multiple actuators, failure of which deteriorates dynamic response of the system. The problem of actuator faults is resolved using online reconfigurable control (RC). A reconfiguration component called virtual actuator (VA) is designed such that it reconfigures the system input and output signals and hides actuator fault from DFC. The process of control reconfiguration on actuator fault is automated without any additional control action. The effectiveness of the control methodology is verified by evaluating the dynamic system response of standard test systems using (1) multiple output DFC in damping control, and (2) online RC in design of fault tolerant wide-area damping controller.

Large virtual voltage vectors for direct controllers in six-phase electric drives

The appearance of virtual voltage vectors (VVs) has simultaneously provided two attractive features for multiphase drives: a simple and effective regulation of the x-y currents and a natural fault tolerance that avoids any control reconfiguration after an open-phase fault occurrence. VVs in six-phase drives were initially constructed using large and medium-large voltage vectors, and all subsequent works adopted this procedure without contemplating other alternatives. The use of medium-large vectors limits however the utilization of the dc-link voltage and brings undesired switching harmonics. This work goes back to the initial definition of the VVs and suggests using exclusively large (adjacent) voltage vectors to create the newly proposed large virtual voltage vectors (LVVs). Experimental results confirm that LVVs provide better current quality, lower switching frequency and better dc-link voltage utilization than standard VVs.

Anti-windup reconfigurable control for dynamic positioning vessel with thruster faults

In this study, an anti-windup reconfigurable control method is developed for dynamic positioning vessel in the presence of thruster faults and input saturation. The designed reconfiguration block acting as a virtual thruster aims at hiding the faults from the nominal controller. Also, it is added into the closed-loop system between the nominal controller and the dynamic positioning system. A thruster saturation-failure fault matrix technique is proposed to regard the thruster saturation as thruster fault, meanwhile an auxiliary system is constructed to achieve extra compensation for the adverse effects induced by input saturation. Furthermore, an integral sliding mode control method is presented to accommodate the nonlinear items in the reconfiguration block. An adaptive technique is also employed to preserve robustness against the unknown uncertainties. Finally, a vessel dynamic positioning control process is adopted to evaluate the effectiveness of the proposed method.

Automatic Supervisory Controller for Deadlock Control in Reconfigurable Manufacturing Systems with Dynamic Changes

In reconfigurable manufacturing systems (RMSs), the architecture of a system can be modified during its operation. This reconfiguration can be caused by many motivations: processing rework and failures, adding new products, adding new machines, etc. In RMSs, sharing of resources may lead to deadlocks, and some operations can therefore remain incomplete. The objective of this article is to develop a novel two-step solution for quick and accurate reconfiguration of supervisory controllers for deadlock control in RMSs with dynamic changes. In the first step, the net rewriting system (NRS) is used to design a reconfigurable Petri net model under dynamic configurations. The obtained model guarantees boundedness behavioral property but may lose the other properties of a Petri net model (i.e., liveness and reversibility). The second step develops an automatic deadlock prevention policy for the reconfigurable Petri net using the siphon control method based on a place invariant to solve the deadlock problem with dynamic structure changes in RMSs and achieve liveness and reversibility behavioral properties for the system. The proposed approach is tested using examples in the literature and the results highlight the ability of the automatic deadlock prevention policy to adapt to RMSs configuration changes.

Multiple Open-Switch Fault Diagnosis for Five-Phase Permanent Magnet Machine Utilizing Currents in Stationary Reference Frame

Apart from the passive fault-tolerant control strategies, any active fault-tolerant strategy requires a timely fault diagnosis signal to trigger the control reconfiguration under asymmetric condition. This article proposes a fault diagnosis method where the inherent relationship between fundamental and third harmonic stationary reference currents is established by declaring two new groups of current-based variables. Then two distinct fault characteristics of current performance in the transient conversion from healthy to faulty operation are derived. Based on the fault characteristics, a fast, robust and easy-implemented diagnosis algorithm is proposed based on currents in stationary reference frame to address the multiple open-switch fault diagnosis in five-phase permanent magnet machines. In order to verify the effectiveness of the proposed algorithm, a series of experiments have been conducted and the results indicate the strong robustness even under load variation and the valid diagnosis to each type of faults are performed. Moreover, the proposed method possesses favorable generality and can be extended to other multiphase machines.

A nonlinear model predictive control scheme for sensor fault tolerance in observation processes

SummaryThis article addresses the problem of designing a sensor fault‐tolerant controller for an observation process where a primary, controlled system observes, through a set of measurements, an exogenous system to estimate the state of this system. We consider sensor faults captured by a change in a set of sensor parameters affecting the measurements. Using this parametrization, we present a nonlinear model predictive control (NMPC) scheme to control the observation process and actively detect and estimate possible sensor faults, with adaptive controller reconfiguration to optimize the use of the remaining sensing capabilities. A key feature of the proposed scheme is the design of observability indices for the NMPC stage cost to improve the observability of both the state of the exogenous system and the sensor fault parameters. The effectiveness of the proposed scheme is illustrated through numerical simulations.

ReCoFused partial reconfiguration for secure moving-target countermeasures on FPGAs

Partial reconfiguration is a versatile technique to modify the functionality of field programmable gate arrays (FPGAs) at run time. When performing partial reconfiguration a dedicated intellectual property (IP) component of the FPGA vendor, i.e., the partial reconfiguration controller (PRC), among a wide range of IP components has to be used. While ensuring the functional safety of FPGA designs is well understood, ensuring hardware security still remains challenging. This applies in particular to reconfiguration-based countermeasures which are intensively used to create a moving target for an attacker. Reconfiguration-based countermeasures against side-channel attacks or differential power analysis (DPA) attacks were implemented. However, from the system security perspective, the above mentioned PRC is a critical component as was noticed by many papers before. In this work, we extend a previously proposed safety mechanism which creates a container around an IP, to encapsulate and thereby to protect and observe the PRC of a FPGA. The proposed encapsulation scheme results in an architecture comprising so-called ReCoFuses (RCFs), each capturing a specific protective goal which have to be fulfilled at any time during PRC operation. The terminology follows the classical electric installation including a fuse box. In our scheme we employ formal verification to guarantee the correctness in detecting a security violation. Only after successful verification, the RCFs are integrated into the ReCoFuse Container. Experimental results demonstrate the advantage of our approach by preventing attacks on the PRC of a system secured by partial reconfiguration.

A Reconfigurable and Extendable Single-Inductor Single-Path Three-Switch Converter for Indoor Photovoltaic Energy Harvesting

This article proposes a single-path three-switch (1P3S) single-inductor dual-input dual-output (SIDIDO) converter to manage power among a photovoltaic (PV) module, battery, and load for indoor PV energy harvesting. For low duty-cycle applications, the 1P3S converter increases efficiency in the PV-to-battery-to-load path by eliminating inductor-sharing power switches. This article also proposes a reconfigurable controller to achieve reconfigurability and extendibility that the 1P3S converter can be reconfigured as a dual-path three-switch (2P3S) SIDIDO converter, combined as a dual-path six-switch (2P6S) SIDIDO converter, or extended as a paralleled-1P3S converter for high energy efficiency in various applications with different PV and load power profiles. To identify each converter’s advantageous applications, the efficiencies of the 1P3S, reconfigured 2P3S, and combined 2P6S converters were analyzed under dynamic PV and load powers. The chip is fabricated in the 0.5- $\mu \text{m}$ CMOS process with a 1.24-mm2 chip area. The measured peak efficiencies for the 1P3S, 2P3S, and 2P6S converters are 95.0%, 95.2%, and 90.0%, respectively, while the measured quiescent currents are 210, 130, and 140 nA, respectively. Compared with the state-of-the-art 2P3S and 2P6S converters, the reconfigured 2P3S and combined 2P6S converters with the proposed IC, respectively, achieve higher efficiency through appropriate switch sizes and ON-time optimizations.

Batch-Constrained Reinforcement Learning for Dynamic Distribution Network Reconfiguration

Dynamic distribution network reconfiguration (DNR) algorithms perform hourly status changes of remotely controllable switches to improve distribution system performance. The problem is typically solved by physical model-based control algorithms, which not only rely on accurate network parameters but also lack scalability. To address these limitations, this paper develops a data-driven batch-constrained reinforcement learning (RL) algorithm for the dynamic DNR problem. The proposed RL algorithm learns the network reconfiguration control policy from a finite historical operational dataset without interacting with the distribution network. The numerical study results on three distribution networks show that the proposed algorithm not only outperforms state-of-the-art RL algorithms but also improves the behavior control policy, which generated the historical operational data. The proposed algorithm is also very scalable and can find a desirable network reconfiguration solution in real-time.

Active Fault-Tolerant Control for Electro-Hydraulic Systems With an Independent Metering Valve Against Valve Faults

Aiming at the tough requirements for safety and maintainability in mobile hydraulic systems, in this article, an active fault-tolerant control (FTC) system is proposed against the valve faults of an independent metering valve. Not only moderate faults of activated valves, but also significant faults and unactivated valve faults are considered. Without additional hardware redundancy, analytical redundancy is derived by the coordinate control of other fault-free valves. Accordingly, an FTC system in parallel with a normal controller is designed based on the pressure feedback. It consists of a set of reconfigurable controllers and a decision mechanism. The control signals, control loops, and operating modes can all be precisely reconfigured to adaptively match unmodeled fault dynamics. A bumpless transfer controller based on a latent tracking loop is designed to smooth the switching between the normal controller and FTC. Consequently, random valve faults can be tolerated with minor degradations in motion tracking and energy-saving performance. The feasibility of the FTC system is evaluated by a 2-ton excavator.

Self‐synchronising virtual induction generator without phase‐locked loop and proportional–integral regulators

This study presents a virtual induction generator (VIG) concept-based microgrid with multifunctional objectives such as seamless transition capabilities, secondary frequency regulation, adaptive with variation in grid frequency and phase. The secondary frequency regulation scheme is presented to improve the system dynamics bereft of any using proportional-integral-derivative controller. Furthermore, the VIG provides auto-synchronization with the distribution grid even without direct knowledge of the phase and frequency of the grid. Moreover, the presented controller eliminates the requirement of a dedicated synchronising unit such as a phase-locked loop and proportional–integral regulators, and an additional unintentional islanding detection scheme, which provides a robust feasible solution for practical implementation. In contrast to the state-of-art techniques, the controller has been formulated such a way that VIG does not require the control reconfiguration even under mode transition enabling unintentional islanding detection. Simulation results validate the effectiveness of the self-synchronising VIG under various operating conditions. The comparative performances are analysed with the state-of art techniques for dynamic operation conditions to validate the effectiveness of the self-synchronising VIG. Test results demonstrate satisfactory performance of VIG under various dynamic operating conditions.

Inverter fault diagnosis of an electrical series‐connected two sinusoidal six‐phase permanent magnet machines drive

This study investigates a real-time fault diagnostic of a transportation system which needs two drives with fault-tolerance capabilities. Owing to the constraints on the mass of the system and on the cost of the voltage source inverter, a drive with two six-phase permanent magnet synchronous machines in series-connection supplied by two six-leg inverters is chosen. Despite the serial connection, independent control of the two machines and fault-tolerance to open-switch fault is ensured. Nevertheless, a fault detection identification (FDI) process is required for analysis and/or control reconfiguration. The proposed FDI is based on the combination of different criteria obtained from the two zero-sequence currents and from the normalised currents mapped into two frames defined by the concordia transformation. Results obtained from simulation and experimental tests show the effectiveness of the proposal.

Cyclic Pursuit-Fuzzy PD Control Method for Multi-agent Formation Control in 3D Space

This paper proposes a novel cooperative control method based on cyclic pursuit algorithm and fuzzy control idea, to accomplish reconfiguration of multi-agent formation in 3D space. The idea is to use nonlinear cyclic pursuit control within the formation’s longitudinal motion plane, and use fuzzy control-based piecewise proportional derivative (PD) controller for cooperative control in the normal direction of motion. It is called cyclic pursuit-fuzzy PD control method. The control process is divided into different fuzzy sets, for which different control coefficients are set. The paper will present two control strategies to comparatively analyze the performances of control method. As the results demonstrate, the proposed method improves the performance and accuracy of formation reconfiguration control, avoids the inter-member collisions and enhances the system stability.

Automatic Fault-Tolerant Control of Multiphase Induction Machines: A Game Changer

Until very recently, the fault tolerance in multiphase electric drives could only be achieved after fault localization and a subsequent modification of the control scheme. This scenario was profoundly shaken with the appearance of the natural fault tolerance, as the control reconfiguration was not required anymore. Even though the control strategy was highly simplified, it was still necessary to detect the open-phase fault (OPF) in order to derate the electric drive and safeguard its integrity. This work goes one step beyond and suggests the use of an automatic fault-tolerant control (AFTC) that also avoids the detection of the OPF. The AFTC combines the natural fault-tolerant capability with a self-derating technique, finally obtaining a hardware-free software-free fault tolerance. This achievement changes completely the rules of the game in the design of fault-tolerant drives, easing at the same time their industrial application. Experimental results confirm in a six-phase induction motor (IM) drive that the proposed AFTC provides a simple and safe manner to add further reliability to multiphase electric drives.

Distributed MPC for Reconfigurable Architecture Systems via Alternating Direction Method of Multipliers

This paper investigates the distributed model predictive control (MPC) problem of linear systems where the network topology is changeable by the way of inserting new subsystems, disconnecting existing subsystems, or merely modifying the couplings between different subsystems. To equip live systems with a quick response ability when modifying network topology, while keeping a satisfactory dynamic performance, a novel reconfiguration control scheme based on the alternating direction method of multipliers (ADMM) is presented. In this scheme, the local controllers directly influenced by the structure realignment are redesigned in the reconfiguration control. Meanwhile, by employing the powerful ADMM algorithm, the iterative formulas for solving the reconfigured optimization problem are obtained, which significantly accelerate the computation speed and ensure a timely output of the reconfigured optimal control response. Ultimately, the presented reconfiguration scheme is applied to the level control of a benchmark four-tank plant to illustrate its effectiveness and main characteristics.

Multiphase current imbalance localisation method applied to natural fault‐tolerant strategies

Multiphase machines are interesting options for high-reliability applications due to their inherent fault tolerance against open-circuit faults (OCFs). Moreover, if the regulation of the x–y currents is realised in open-loop mode using virtual voltage vectors (VVs), the mandatory post-fault control reconfiguration is avoided. The new reconfigurationless approach was recently defined as a natural/passive fault-tolerant strategy, offering good prospects for industry applications. This work extends the idea to the fault detection procedure and suggests new settings for the current imbalance localisation method. The proposal is based on the vector space decomposition approach that allows the joint detection of OCFs and stator resistances dissymmetry. Experimental results in a five-phase induction motor drive using VVs confirm the viability of the technique.