Sensor Actuator Research Articles

Nonlinear Vibration Control Experimental System Design of a Flexible Arm Using Interactive Actuations from Shape Memory Alloy.

The flexible arm easily vibrates due to its thin structural characteristics, which affect the operation accuracy, so reducing the vibration of the flexible arm is a significant issue. Smart materials are very widely used in the research topic of vibration suppression. Considering the hysteresis characteristic of the smart materials, based on previous simulation research, this paper proposes an experimental system design of nonlinear vibration control by using the interactive actuation from shape memory alloy (SMA) for a flexible arm. The experiment system was an interactive actuator-sensor-controller combination. The vibration suppression strategy was integrated with an operator-based vibration controller, a designed integral compensator and the designed n-times feedback loop. In detail, a nonlinear vibration controller based on operator theory was designed to guarantee the robust stability of the flexible arm. An integral compensator based on an estimation mechanism was designed to optimally reduce the displacement of the flexible arm. Obtaining the desired tracking performance of the flexible arm was a further step, by increasing the n-times feedback loop. From the three experimental cases, when the vibration controller was integrated with the designed integral compensator, the vibration displacement of the flexible arm was much reduced compared to that without the integral compensator. Increasing the number of n-times feedback loops improves the tracking performance. The desired vibration control performance can be satisfied when n tends to infinity. The conventional PD controller stabilizes the vibration displacement after the 7th vibration waveform, while the vibration displacement approaches zero after the 4th vibration waveform using the proposed vibration control method, which is proved to be faster and more effective in controlling the flexible arm's vibration. The experimental cases verify the effectiveness of the proposed interactive actuation vibration control approach. It is observed from the experimental results that the vibration displacement of the flexible arm becomes almost zero within less time and with lower input power, compared with a traditional controller.

Sensor selection and controller design method with application to turbocharged stoichiometric spark-ignited engine controls with low pressure EGR

This paper describes and demonstrates a model-based sensor selection and controller design framework for robust control of air–fuel-ratio, air flow and EGR flow for turbocharged stoichiometric engines using low pressure EGR, waste-gate turbo-charging, intake throttling and variable valve timing. Model uncertainties, disturbances, transport delays, and sensor- and actuator-characteristics are considered in this framework. Based on the required control performance and candidate sensor sets, the framework synthesizes an H∞ feedback controller and evaluates the viability of the candidate sensor set through analysis of the singular structured value μ of the closed-loop system in the frequency domain. The framework can also be used to understand if relaxing the controller performance requirements enable the use of a simpler (less costly) sensor set. The sensor selection and controller co-design approach is applied here, for the first time, to turbo-charged engines using exhaust gas circulation. High fidelity GT-Power simulations are used to validate the approach. The computed optimal controllers were able to maintain the AFR within 14.7 ± 0.3, control the torque within 8.2% error and the EGR ratio within 1.2% error at different drive cycles with sensor inaccuracies and actuator dynamics.

Sensor/actuator colocation feasibility for distributed damping control using active power modulation

Multi-use distributed active power modulation devices, including energy storage, have the potential to transform the dynamic performance and resilience of modern power systems. Rapid response characteristics relative to traditional power delivery equipment paired with traditional uses (arbitrage, reserve, etc.) make storage an obvious choice for multi-use operation, adding value for asset owners while augmenting stability for reliable operation. Limitations to distributed power control are investigated to provide guidance for those interested in separated sensors and actuators. Substantive distance between the sensor/actuator pair results in non-minimum phase (NMP) which complicates the control design, reducing feedback system effectiveness. It is shown that wide-area control (WAC) is limited by the presence of NMP induced by closed right-half plane (CRHP) zeros - a consequence of sensors placed at locations separated from modulation bus(es). Such geographic separation may be driven by economics, asset owner jurisdiction, technology and/or policy, and is therefore unavoidable. This work suggests that system designers must perform a collocation study before control design and testing. A well-known WAC architecture using synchrophasors as sensors and energy storage devices for active power injection is presented as a detailed case study. • Collocated sensor–actuators pose difficulties which may force modest separation. • Closed right-half plane (CRHP) zeros may result due to such separation. • Noncollocated sensor–actuator pairs may reduce performance and threaten stability. • Bandwidth and performance limitations regarding collocation are determined.

Fault Diagnostics for Oscillatory Failure Case in Aircraft Elevator Servos

Oscillatory Failure Case (OFC) is a characteristic sinusoidal fault that propagates through control surfaces and actuator servo loops of commercial aircrafts that originates from spurious sensor measurements and actuator commands. The goal of this work is to detect such faults of unknown amplitudes and frequencies in the presence of turbulence. The fault detection scheme employs a graph-theoretic approach that uses a structural model of the aircraft's longitudinal dynamics and the servo actuators to determine residuals for OFC fault detection and isolation. A smooth controller reconfiguration strategy is proposed to switch between a nominal control law and a degraded alternate control law which utilizes sensor measurement feedback as well as virtual sensors from a digital model of longitudinal cruising dynamics without affecting the controller structure and feedback loops.

Sensors and actuators for the advanced LIGO A+ upgrade.

Advanced Laser Interferometer Gravitational-wave Observatory (LIGO A+) is a major upgrade to LIGO-the Laser Interferometer Gravitational-wave Observatory. For the A+ project, we have developed, produced, and characterized sensors and electronics to interrogate new optical suspensions designed to isolate optics from vibrations. The central element is a displacement sensor with an integrated electromagnetic actuator known as a BOSEM (Birmingham Optical Sensor and ElectroMagnetic actuator) and its readout and drive electronics required to integrate them into LIGO's control and data system. In this paper, we report on the improvements to the sensors and the testing procedures undertaken to meet the enhanced performance requirements set out by the A+ upgrade to the detectors. The best devices reach a noise level of 4.5 ×10-11m/Hz at a measurement frequency of 1Hz, an improvement of 6.7 times over standard devices.

Design of Resilient Supervisory Control for Autonomous Connected Vehicles Approaching Unsignalized Intersection in presence of Cyber-Attacks

The aim of this paper is to ensure safety in a distributed dynamical system, modeled as a Discrete Events Systems (DES), whose feedback control is compromised by a malicious attacker hijacking the system communication channel, being able to insert or remove sensor reading and/or actuation requests. Our focus is autonomous connected vehicle applications and the synthesis of a supervisor that is robust against a large class attacks. Specifically, we model DES supervisors for managing the interactions among self-driving cars when negotiating access to a traffic junction in the presence of an attacker who can manipulate the outputs from the sensors of the system before they can reach the supervisory controller itself. We propose different supervisor solutions to assess the resilience of the intersection crossing and we disclose the best suitable one for the appraised automotive application, as well as its effectiveness.

Reducing airplane cabin and fuselage noise using active and passive control techniques

The focus of this research is on making a wide discussion about the sources and control techniques of noise propagating to the passenger airplane cabin and fuselage. The first part of the document discusses the effects of vibration induced noise (vibro-acoustic) transmitted from airplane engines and aerodynamic impact on the main body of the aircraft besides to air-conditioning vibrations. These vibrations transmit noise to the cabin and fuselage causing discomfort to passengers. Finite element modelling technique is used to make this study. Two different solutions are suggested to control and get rid of these vibrations; passive control techniques using tuned mass dampers is one of the suggested solutions and the second solution is an active control technique using piezoelectric actuator and force sensor with integral force feedback compensator. The performance of the active control is much higher than that of the passive one but it is much more expensive.

Impact of Malfunction Load Cell and Mechanical actuator Sensor to Performance of Ship Stability General Cargo Simulator at Unit Laboratorium and Workshop STIP Jakarta

Ship Stability General Cargo Simulator (SSTS) is a laboratory to provide training on the configuration and procedures for maintaining ship stability as a training facility for cadets in the engineering field. The Ship Stability General Cargo Simulator configuration at STIP Marunda Jakarta describes a general cargo ship configuration in which it has equipment to simulate cargo loading and ship ballast filling, which serves to simulate ship conditions when loading cargo. Maintenance and repair are activities carried out to improve, maintain, and return equipment in good and ready-to-use condition. In relation to the maintenance of laboratory equipment, maintenance is intended as a preventive effort or prevention so that the equipment is not damaged or is maintained in good condition, ready to operate. Besides that, maintenance is also intended as an effort to adjust or repair laboratory equipment that has already been damaged or is not feasible so that it becomes ready to be used for practical activities for students or cadets. Some of the maintenance that needs to be done on this Ship Stability Simulator are: Electrical system, Filling System, Drain System, Actuator System, Measurement Level System. Research purposes: The research objectives of this paper that make this is to obtain solutions so that maintenance and repairs can operate properly, viability of laboratory facilities as training infrastructure in the STIP Marunda Jakarta environment, always in a state of optimal use.

A Review of Internet of Things (IoT) and Security Concerns

Wireless technology networks are particularly vulnerable to security attacks. Wireless communication networks are widely used in education, defense, industry, healthcare, retail, and transportation. These systems rely on wired and cellular networks. In society and industry, wireless sensor networks, actuation networks, and vehicle networks have garnered a lot of attention. The Internet of Things has gotten a lot of research attention in recent years. The Internet of Things is regarded as the internet's future. IoT will play an important role in the future, changing our lifestyles, standards, and business structures. The use of IoT in various applications is likely to skyrocket in the next years. The Internet of Things enables billions of devices, people, and services to communicate and exchange information. IoT networks are vulnerable to several security vulnerabilities as a result of the rising use of IoT devices. It is crucial to implement effective privacy and security protocols in IoT networks to guarantee, among other things, confidentiality, authentication, access control, and integrity. This paper provides a thorough analysis of the security and privacy challenges in IoT networks. Keywords: Internet of Things, Security, Security Concerns, Attacks, Networks, Internet

Image Classification-Based Defect Detection of Railway Tracks Using Fiber Bragg Grating Ultrasonic Sensors

Structural health monitoring (SHM) is vital to the maintenance of civil infrastructures. For rail transit systems, early defect detection of rail tracks can effectively prevent the occurrence of severe accidents like derailment. Non-destructive testing (NDT) has been implemented in railway online and offline monitoring systems using state-of-the-art sensing technologies. Data-driven methodologies, especially machine learning, have contributed significantly to modern NDT approaches. In this paper, an efficient and robust image classification model is proposed to achieve railway status identification using ultrasonic guided waves (UGWs). Experimental studies are conducted using a hybrid sensing system consisting of a lead–zirconate–titanate (PZT) actuator and fiber Bragg grating (FBG) sensors. Comparative studies have been firstly carried out to evaluate the performance of the UGW signals obtained by FBG sensors and high-resolution acoustic emission (AE) sensors. Three different rail web conditions are considered in this research, where the rail is: (1) intact without any defect; (2) damaged with an artificial crack; and (3) damaged with a bump on the surface made of blu-tack adhesives. The signals acquired by FBG sensors and AE sensors are compared in time and frequency domains. Then the research focuses on damage detection using a convolutional neural network (CNN) with the input of RGB spectrum images of the UGW signals acquired by FBG sensors, which are calculated using Short-time Fourier Transform (STFT). The proposed image classifier achieves high accuracy in predicting each railway condition. The visualization of the classifier indicates the high efficiency of the proposed paradigm, revealing the potential of the method to be applied to mass railway monitoring systems in the future.

Adjustable proportional-integral multivariable observer-based FDI attack dynamic reconstitution and secure control for cyber-physical systems

This paper investigates the false data injection (FDI) attack dynamic reconstitution and secure control problems for cyber-physical systems (CPSs) with disturbances. The FDI attacks on the actuator channel and sensor channel are considered simultaneously, and the attack signals acting on the system side are regarded as time-varying signals. Firstly, a novel adjustable proportional-integral multivariable observer (APIMO) scheme is designed to synchronously reconstitute the system states, actuator FDI attacks, and sensor FDI attacks. In particular, the impacts of instantaneous increment of attack signals are attenuated, which enables the proposed APIMO scheme more advantageous in reconstituting time-varying attack signals. Secondly, incorporating a robust attenuation technique, an APIMO-based security controller with corrective capability is designed, such that the discrete-time CPSs achieve asymptotic stability with H∞ performance index. Finally, the simulation example and experiment compared with existing results are realized to examine the feasibility and advantages of the developed strategy.

A single quasi-cubic test mass configuration for space-based gravitational wave detection

Two test masses per spacecraft configuration is the main scheme and exhibits a high level of maturity for space-based gravitational wave detection. However, the single test mass configuration is continuously discussed with different designs to reduce technical complexities such as spacecraft control. This paper proposes a new configuration with a single quasi-cubic test mass per spacecraft. The new configuration inherits the existing capacitance displacement sensor and electrostatic actuator. It has the advantage of the suppression of centrifugal force effect due to the coincidence of the center of mass between the spacecraft and test mass. In addition, it has the advantages of simplifying the self-gravity compensation strategy and the drag-free attitude and orbit control strategy due to using a single test mass.

Machine-learned control-oriented flow estimation for multi-actuator multi-sensor systems exemplified for the fluidic pinball

We propose the first machine-learned control-oriented flow estimation for multiple-input, multiple-output plants. The starting point is constant actuation with open-loop actuation commands leading to a database with simultaneously recorded actuation commands, sensor signals and flow fields. A key enabler is an estimator input vector comprising sensor signals and actuation commands. The mapping from the sensor signals and actuation commands to the flow fields is realized in an analytically simple, data-centric and general nonlinear approach. The analytically simple estimator generalizes linear stochastic estimation for actuation commands. The data-centric approach yields flow fields from estimator inputs by interpolating from the database – similar to Loiseau, Noack & Brunton (J. Fluid Mech., vol. 844, 2018, pp. 459–490) for unforced flow. The interpolation is performed with$k$nearest neighbours ($k$NN). The general global nonlinear mapping from inputs to flow fields is obtained from a deep neural network (DNN) via an iterative training approach. The estimator comparison is performed for the fluidic pinball plant, which is a multiple-input, multiple-output wake control benchmark (Denget al.,J. Fluid Mech., vol. 884, 2020, A37) featuring rich dynamics under steady controls. We conclude that the machine learning methods clearly outperform the linear model. The performance of$k$NN and DNN estimators are comparable for periodic dynamics. Yet the DNN performs consistently better when the flow is chaotic. Moreover, a thorough comparison regarding the complexity, computational cost and prediction accuracy is presented to demonstrate the relative merits of each estimator. The proposed method can be generalized for closed-loop flow control plants.

Multi-Access Edge Computing assisted ultra-low energy scheduling and harvesting in multi-hop Wireless Sensor and Actuator Network for energy neutral self-sustainable Next-gen Cyber-Physical System

Energy Neutrality is the need of the hour for future Cyber-physical infrastructure. Many past research works suggest low duty cycle networking for energy-efficient wireless sensor network; however, research problem still persist as these proposals have some practical deployment bottlenecks like sleep-latency and may trade-off with data-fidelity and Quality-of-Service (QoS) parameters. The research objective of this work is to propose a novel design for wireless sensor–actuator mote system to minimize energy consumption and compensate with harvesting to achieve energy neutral operation in multi-hop Wireless Sensor and Actuator Network (WSAN); A network scenario that is much needed for Internet of Thing (IoT) applications in future ready Next-gen Cyber Physical System (NG-CPS). In this paper, we have proposed a novel state-of-the-art Multi-Access/Mobile Edge Computing (MEC) assisted Low-Duty-Cycle Scheduling of Trans-Receiver for Store-Process-Then-Forward (LDCS-TR-SPTF) scheme in multi-hop WSAN for reducing the overall energy consumption. In addition to energy conservation, we have also proposed a hybrid harvesting to compensate energy to achieve energy neutral self-sustainable NG-CPS. The proposed novel LDCS-TR-SPTF has been implemented on multiple custom-made sensor–actuator motes equipped with ARM-based System-on-Chip (SoC) and IEEE 802.11 network interface. These motes are working both as end-nodes and relay nodes in a multi-hop WSAN testbed scenario for testing and validation of our proposed scheme. The results are promising with an overall energy conservation of 49.1% using our novel LDCS-TR-SPTF in comparison to stock IEEE 802.11. We have implemented solar energy harvester on wireless sensor–actuator motes to compensate the reduced energy consumption and achieved complete energy-neutrality. Motes are completely energy-autonomous in multi-hop WSAN scenario by eliminating the need of access to external power-grid for future cyber–physical system.

Robust Data-Driven Design for Fault Diagnosis of Industrial Drives

Due to the presence of actuator disturbances and sensor noise, increased false alarm rate and decreased fault detection rate in fault diagnosis systems have become major concerns. Various performance indexes are proposed to deal with such problems with certain limitations. This paper proposes a robust performance-index based fault diagnosis methodology using input–output data. That data is used to construct robust parity space using the subspace identification method and proposed performance index. Generated residual shows enhanced sensitivity towards faults and robustness against unknown disturbances simultaneously. The threshold for residual is designed using the Gaussian likelihood ratio, and the wavelet transformation is used for post-processing. The proposed performance index is further used to develop a fault isolation procedure. To specify the location of the fault, a modified fault isolation scheme based on perfect unknown input decoupling is proposed that makes actuator and sensor residuals robust against disturbances and noise. The proposed detection and isolation scheme is implemented on the induction motor in the experimental setup. The results have shown the percentage fault detection of 98.88%, which is superior among recent research.

A combination of large unipolar electrostrain and d33 in a non-ergodic relaxor ferroelectric

One of the important requirements for piezoelectric materials for use as high strain actuators is that they exhibit large unipolar electrostrain with minimum hysteresis. While large unipolar electrostrain >1% is generally achievable in good quality single crystals, most polycrystalline piezoelectric show low values < 0.4%. Unipolar electrostrain 0.5%–0.7% in polycrystalline piezoelectrics has often been reported in Na0.5Bi0.5TiO3-based compositions at the non-ergodic ergodic boundary. Not amenable to poling, such materials exhibit almost nearly zero direct piezoelectric coefficient (d33 ∼ 0 pC/N) and cannot be simultaneously used as a sensor. In this paper, we report a combination of large unipolar electrostrain of ∼0.6% with small strain hysteresis of 25% in a Sn-modified relaxor ferroelectric system PbTiO3–Bi(Ni1/2Zr1/2)O3. It exhibits d33 ∼ 340 pC/N, which is stable up to 130 °C, and large signal converse piezoelectric coefficient d33* ∼ 1200 pm/V. A combination of large d33 and d33* in the same material makes it an important candidate for simultaneous use as a sensor and high strain actuators. X-ray diffraction study in situ with the electric field suggests that large electrostrain with low strain hysteresis in this system is because of the increased reversible switching of the field stabilized tetragonal ferroelastic domains.

Dealing with sensor and actuator deception attacks in supervisory control

We consider feedback control systems where sensor readings and actuator commands may be compromised by an attacker intending to damage the system. We study this problem at the supervisory layer of the control system, using discrete event systems techniques. The attacker can edit the outputs from the sensors of the system before they reach the supervisory controller as well as it can edit actuator commands before they reach the system. In this context, we formulate the problem of synthesizing a supervisor that is robust against a large class of edit attacks on the sensor readings and actuator commands. Intuitively, we search for a supervisor that guarantees the safety of the system even when sensor readings and actuator commands are compromised. Given the similarities of the investigated problem to the standard supervisory control problem, our solution methodology reduces the problem of synthesizing a robust supervisor against deception attacks to a supervisory control problem. This new and intuitive solution methodology improves upon prior work on this topic.

Industrial Control Systems Security via Runtime Enforcement

With the advent of Industry 4.0 , industrial facilities and critical infrastructures are transforming into an ecosystem of heterogeneous physical and cyber components, such as programmable logic controllers , increasingly interconnected and therefore exposed to cyber-physical attacks , i.e., security breaches in cyberspace that may adversely affect the physical processes underlying industrial control systems . In this article, we propose a formal approach based on runtime enforcement to ensure specification compliance in networks of controllers, possibly compromised by colluding malware that may locally tamper with actuator commands, sensor readings, and inter-controller communications. Our approach relies on an ad-hoc sub-class of Ligatti et al.’s edit automata to enforce controllers represented in Hennessy and Regan’s Timed Process Language . We define a synthesis algorithm that, given an alphabet 𝒫 of observable actions and a timed correctness property e , returns a monitor that enforces the property e during the execution of any (potentially corrupted) controller with alphabet 𝒫, and complying with the property e . Our monitors do mitigation by correcting and suppressing incorrect actions of corrupted controllers and by generating actions in full autonomy when the controller under scrutiny is not able to do so in a correct manner. Besides classical requirements, such as transparency and soundness , the proposed enforcement enjoys deadlock- and diverge-freedom of monitored controllers, together with scalability when dealing with networks of controllers. Finally, we test the proposed enforcement mechanism on a non-trivial case study, taken from the context of industrial water treatment systems, in which the controllers are injected with different malware with different malicious goals.

Stabilization by switching of parabolic PDEs with spatially scheduled actuators and sensors

This paper addresses a switched sampled-data control design for stabilization of Kuramoto-Sivashinsky equation under the Dirichlet/periodic boundary conditions with spatially scheduled actuators. It is supposed that discrete-time point-like or averaged measurements are available. The system is known to be stabilizable by static output-feedback employing several distributed in space actuators and sensors, but is not stabilizable by only one of the actuator–sensor pairs. Does there exist a switching stabilizing static output-feedback such that at all times, only one actuator–sensor pair is active? We give a positive answer and find the appropriate switching sampled-data control law. The proposed switching controller can be implemented either by N actuators and sensors placed in each subdomain (here switching control may reduce the energy that the system spends) or by using one actuator–sensor pair that can move to the active subdomain. For implementation of the control law by moving actuators and sensors, we take into account a moving time by treating it as an additional switching between the open-loop system and the closed-loop switched system. The guidance of active (or mobile) actuators and sensors is provided by using output-dependent switching. Constructive conditions are derived to ensure that the resulting closed-loop system is regionally stable by means of the Lyapunov approach. Numerical example illustrates the efficiency of the method.

Robust sliding‐mode observer‐based multiple‐fault diagnosis scheme

AbstractIn this study, we simultaneously evaluate the multiple‐fault diagnosis problem of a class of Lipschitz nonlinear systems with actuator and sensor faults and unknown input disturbances. A nonsingular system transformation is used to transform the original system into two subsystems for multiple‐fault diagnosis: subsystems 1 and 2. At the system level, two robust sliding‐mode observers (RSMOs) are proposed. An RSMO is designed for subsystem 1 to detect actuator faults subjected to unknown input disturbances, and another RSMO is designed for subsystem 2 to detect sensor faults subjected to actuator faults. At the component level, a bank of RSMOs is proposed to detect and isolate actuators (sensors) with faults using a dedicated observer scheme. The reachability of RSMOs is comprehensively investigated in the estimation error space. Accordingly, the proposed observer parameters are designed as an optimization problem and solved using the linear matrix inequality (LMI) optimization technique. The effectiveness of the proposed multiple‐fault diagnosis scheme was validated through simulations of a modified seventh‐order aircraft system.