Active Structural Control Research Articles

A force-density framework for flexible multi-body dynamic analysis of clustered tensegrity structures

This paper develops a versatile and effective force-density framework for the flexible multi-body dynamic analysis of clustered tensegrity structures. In this framework, the force density is selected as the basic variable instead of force, and the clustered tensegrity structure is mathematically described in a vector and matrix form, encompassing topology, geometry, material, and force properties. A non-negative variable is defined as an indicator of the member stress state, and a complementary function is constructed to address the discontinuity issues that arise from the unidirectional axial stiffness of cables. Dynamic formulas are established within this force-density framework, with nodal coordinates selected as generalized parameters and formulations constructed in a matrix form. A complementary framework is established as an alternative for solving the dynamic equations, transforming the isolated steps of Newton’s iteration and cable state judgment (slack or tension) into a unified one, bringing more potential for improving solving efficiency. Numerical simulations are carried out to validate the approach, demonstrating that it effectively reveals the dynamic oscillation, tension changes, and cable slack behavior of clustered tensegrity structures during shape control. Comparative studies highlight the advantage of computational efficiency. The method proposed in this paper provides a robust mathematical model for studying clustered tensegrity structures, particularly regarding the shape control of deployable, active, and intelligent structures, aiding in understanding dynamic oscillation, tension changes, and cable slack behavior during their deformation. The methods can also be applied to cable net structures and other prestressed pin-jointed systems.

Active Vibration Control of Flexible Structures Based on Piezoelectric Materials

With the rapid development of China's space industry, flexible structures are more and more widely used in spacecraft development, and vibration control has become the main challenge of spacecraft stability. In this paper, the vibration control of spacecraft flexible structure is taken as the research goal, the basic characteristics and piezoelectric equations of piezoelectric materials are systematically introduced, the modeling and active vibration control of piezoelectric flexible structure are studied, and the vibration control of piezoelectric flexible structure is established. In this paper, an experimental platform for active control is built, and vibration measurement and control experiments are carried out on the experimental platform, which verifies the effectiveness of PID control algorithm based on BP neural network for vibration control, provides theoretical data support for active vibration control of engineering piezoelectric structures, and also provides reference for the research of similar systems with engineering practicability in the future.

Design and Implementation of a MIMO Integral Resonant Control for Active Vibration Control of Pedestrian Structures

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the integral resonant control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective by proposing the implementation of a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. This application of MIMO IRC for AVC represents a novel advancement in the field, offering a new solution to address vibration issues in lightweight and slender structures. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller undergoes rigorous testing and is implemented on a laboratory floor structure to validate its efficacy. The outcomes of this study demonstrate the effectiveness of the proposed MIMO IRC scheme in actively damping vibrations, thereby enhancing the serviceability and comfort levels of lightweight and slender structures subjected to human-induced excitations.

Vibration control of membrane structures by piezoelectric actuators considering piezoelectric nonlinearity under strong electric fields

Membrane structures, which are widely used in aerospace and civil engineering, are susceptible to large amplitude vibrations due to their low structural damping and high flexibility, leading to the degradation of their working performance. Strong electric fields are commonly needed for piezoelectric actuators to control larger amplitude vibration of membrane structures. However, the effect of piezoelectric nonlinearity due to strong electric fields on the control performance of membrane structures is still underexplored. Given the importance of piezoelectric nonlinearity due to strong electric fields, the present study aims to investigate the vibration control performance of piezoelectric actuators for membrane structures. First, based on the piezoelectric nonlinear constitutive equation, the actuation equation of the piezoelectric actuator is generated. Then, following D′Alembert's principle, a nonlinear dynamic control model of membrane structure containing actuation force is derived. Finally, active vibration control based on velocity feedback algorithms is realized. The results show that the predicted strain without considering the piezoelectric nonlinearity is 80 % smaller than the finite element structure at 500 V. Meanwhile, the errors of Root Mean Squared (RMS) control displacement without considering the piezoelectric nonlinearity are more than 24 % when vibration amplitudes achieve 10 % of the membrane thickness. The developed model provides theoretical implications for active vibration control of flexible structures with piezoelectric actuators in strong electric field environments.

Active Vibration Control of Frame Structure by using Piezoelectric Actuation.

Active Vibration Control of Frame Structure by using Piezoelectric Actuation.

Geophysical delineation of the newly identified Gulmarg fault in the Kashmir Basin, NW Himalaya. Implications for active structural control

The Kashmir Basin, shaped by the collision of the Indian and Eurasian tectonic plates, features prominent faults, including the Balapur fault and other fault zones. This study focuses on the Gulmarg fault within the Northwestern Himalaya, using advanced geomagnetic techniques for delineation. Geomagnetic measurements reveal the characteristics of the newly identified Gulmarg fault. Ground magnetic surveys with Proton Precession Magnetometers along linear profiles and a magnetic grid highlight fault-related anomalies. The results indicate a fault running through the Gulmarg meadows, approximately 1.6 ​km from the Balapur fault, suggesting a potential coupling between the two. Three profiles across the fault exhibit distinctive magnetic variations, highlighting the intricate nature of the fault structure. Gridding methods also reveal anomalies associated with subsurface water and hydraulic activities, underscoring the importance of advanced geophysical techniques. This study emphasizes the significance of detailed investigations to unravel the complex geological processes shaping the Kashmir Basin. The study provides valuable insights into the tectonic activity in the Gulmarg region, underscoring the role of geophysical studies in enhancing our understanding of dynamic geological structures like the Gulmarg fault zone.

Metaheuristic Airflow control for vibration mitigation of a hybrid oscillating water Column-Floating offshore wind turbine system

Unlike the fixed wind turbines, the structure of Floating Offshore Wind Turbines (FOWT) have the added motions of six degrees of freedom induced by the wind, wave and tidal loads. These motions lead to vibration and the degradation of the structure. This paper presents a novel approach to model and stabilize the FOWT by employing the Oscillating Water Columns (OWC) as active structural control system. The innovative concept involves designing a new floating barge-type platform with integrated OWCs on opposite sides of the platform to mitigate undesired oscillations of the system. These OWCs counteract the bending forces caused by wind on the tower and waves on the barge platform. To synchronize the opposing forces with the system’s tilting, a proposed Particle Swarm Optimization with Decreasing Inertia-based Adaptive Neuro-Fuzzy Inference System (PSODI-ANFIS) airflow control strategy is employed. Through manipulation of the barge platform’s pitch angle, the PSODI-ANFIS airflow control system adjusts the valves on either side, opening one and closing the other accordingly. Simulation results, compared with the standard FOWT as well as the Fuzzy-based airflow control system, demonstrate the effectiveness of the PSODI-ANFIS airflow control. It is shown to be superior in reducing platform pitching and the fore-aft translation of the top tower.

Bidirectional active vibration control of two-dimensional structure inspired by automotive engine mounting system

Bidirectional active vibration control of two-dimensional structure inspired by automotive engine mounting system

Continuous control of structural vibrations using hybrid deep reinforcement learning policy

An efficient active structural control scheme by utilizing the collective concepts of data-driven and physics-inspired reinforcement learning (RL) approaches is being introduced here. The controller is designed to deliver optimal feedback forces based on the full-state information, wherein the training process involves the use of deep neural networks (NNs) and a specially designed gradient descent-based sequence within the RL framework. This integration of algorithms results in a unique active control policy that accelerates the learning process, thereby demands considerably less computational resources to develop an optimal and stable controller as compared to existing data-driven approaches. Most importantly, the mentioned data-driven and physics-inspired approaches encompass deep deterministic policy gradient (DDPG) and an iterative gradient-based state feedback control (SFSC) algorithms, respectively, to establish the architecture of the hybrid control policy, referred to as hybrid RL-controller. Additional advantage of the hybrid RL-controller is its ability to operate in continuous state–action spaces, which allows the designed controller to address diverse structural control problems. The staggered performance of the hybrid RL-controller, both in continuous and discrete time, is evaluated in three case studies that involve structures in linear and nonlinear regimes. The outcomes include a detailed comparison of the hybrid RL-controller with the individually designed DDPG and SFSC RL control strategies, as well as the uncontrolled scenario. Furthermore, this study thoroughly investigates the real-life implementation concerns of control strategies, such as perturbations in model parameters and input forces, and time delays in the feedback loop. Finally, the results from this study corroborate that the designed RL-controller showcases superior performance and faster execution time in the feedback loop, making it suitable for the vibration control of multidimensional complex structures.

Experimental study and numerical simulation of morphing characteristics of bistable laminates embedded with 3D printed shape memory polymers

Bistable laminates have potential applications in areas such as buffer and soft robotics due to their two stable states and ability to deform through both snap-through and snap-back processes. However, conventional orthotropic bistable laminates with two stable state configurations and snap loads are similar in magnitude. There is a problem that the deformation cannot be easily driven when the laminate stiffness is high. To solve this problem, a clever design is needed to reduce the snap-back load and increase the snap-through load so that the driven deformation can be realized more easily. In this paper, we propose a design method to suppress and control the deformation of bistable laminates by utilizing the shape memory of 3D-printed shape memory polymers (SMP), which enables the laminates to increase the stiffness while reducing the driving force. First, a numerical model of viscoelasticity of the laminate is established to study its deformation characteristics, and the numerical results are compared with experimental results with good agreement. The effect of SMPs on the snap load and principal curvature of bistable laminates is also investigated. Finally, the interlayer interface bonding of the bistable laminates is examined in microscopic perspective. The results demonstrate that 3D printed SMPs can effectively enhance the snap-through load and reduce the snap-back load of bistable laminates, achieving deformation suppression and control while maintaining good interlaminar bonding with carbon fiber composites. This study provides new insights and practical significance for the deformation suppression and active control of bistable structures.

Predictive active control of building structures using LQR and artificial intelligence

Predictive active control of building structures using LQR and artificial intelligence

Linear parameter-varying output-feedback for active vibration control of an elastic kinetic roof structure with experimental validation

Elastic kinetics are an approach to design transformable lightweight structures with a stable transformation process. The transformation is realized through elastic bending of structural members by exploiting the compliant material behavior. This lightweight and flexible design comes at the cost of increased sensitivity to static and dynamic disturbances. However, most of the current research focuses on the principles of elastic kinetic transformation instead of effective disturbance mitigation. This work focuses on dynamic disturbance mitigation for such transformable lightweight structures using active control. Modeling and controller synthesis are performed in the linear parameter-varying (LPV) framework, since the dynamics of elastic kinetic structures are transformation-state dependent due to geometric nonlinearities. Based on an LPV model in a grid-based representation, an LPV output-feedback control can be designed and synthesized via a gridding approach. This methodology is experimentally tested and validated for the example of an active hybrid roof structure prototype.

Gust Factor Approach for Estimating Maximum Response and Control Force in High-Rise Base-Isolated Buildings with Active Structural Control

This paper devises a new method for estimating the maximum response and maximum control force for high-rise base-isolated buildings with active structural control (active base isolation) to simplify the conventional complex design procedure. While active base isolation has emerged as a prominent solution for achieving high control performance, its design process is inherently complex, particularly when applied to high-rise buildings where wind loads become prominent. To address this problem, we propose a streamlined method inspired by the gust factor methodology widely used in conventional passive wind-resistant designs. This method estimates the maximum response and maximum control force without the need for numerical simulations. We first construct an equivalent passive model of a multi-degree-of-freedom control system to theoretically compute the dynamics of the system. Based on the constructed equivalent passive model and then propose a method to calculate the mean displacement and mean control force using only the static equilibrium of this model. Furthermore, we extend the conventional gust factor approach to active base isolation to estimate the maximum displacement and maximum control force for active base isolation without the need for numerical simulations. We validate our methods through a series of numerical examples, incorporating key parameters such as feedback gain, aspect ratio of building, return period of wind force, and stiffness of isolation. Numerical verifications show that the mean response and mean control force are estimated by the static equilibrium of the proposed equivalent passive model. Moreover, the maximum response and maximum control force can be estimated by the proposed gust factors. Our methods can be applied for feedback control systems using a given feedback gain.

Cooperative control strategy of trajectory tracking and driving stability for distributed-drive vehicles under extreme conditions

Active chassis dynamics control has become increasingly important in recent years for achieving high-level automated driving of intelligent electric vehicles. To improve tracking performance of the commonly-used model predictive control (MPC) in extreme scenarios, such as emergency lane changing, an improved MPC motion stability controller (MPC_ISMC) based on sliding mode variable structure active steering control and differential torque yaw control is proposed. Firstly, an MPC-based trajectory tracking controller is designed to track the desired trajectory. Subsequently, active front-wheel steering (AFS) and direct yaw moment (DYC) controllers are designed by using the backstepping sliding mode variable structure and the adaptive super-twisting sliding mode variable structure, respectively. Moreover, a cooperative control law for the AFS and the DYC is formulated by the smooth switching function and intervention intensity factor with respect to vehicle stable state and trajectory tracking error. After that, a torque distribution scheme of four wheels is optimized to achieve the additional yaw moment target. Finally, the effectiveness of the proposed cooperative control strategy is validated using a hardware-in-the-loop platform. The results indicate that the proposed controller has better performance in trajectory tracking and vehicle stability under extreme conditions compared with traditional MPC and other methods.

A Study of a Cryogenic CuAlMn Shape Memory Alloy

In extreme temperature environments, a newly emerging engineering application involves both the active and passive control of structures using cryogenic shape memory alloys, which are smart materials able to recover high deformation below the freezing point. With the objective of carrying out new advances in this area, the present work aims to investigate the Cu-7.5Al-13.5Mn (wt.%) shape memory alloy. Thermal, microstructural, and thermomechanical analyses of as-cast and hot-rolled specimens were performed, taking into account the effects of annealing and solubilization. It was observed that the phase transition occurs at temperatures below 120 K and changes according to the thermo-mechanical path. Specifically, hot-rolling lowers the phase transition temperature range with respect to the as-cast condition–from 34 K to 23 K for Mf, and from 89 K to 80 K for Af. Additionally, when the annealing temperature rises, the phase transformation temperature increases as well, and the alloy loses its cryogenic features when heat treated above 473 K. Finally, loss factors of 0.06 and 0.088, which were respectively found in dynamic and static settings, validate the material’s good damping response.

Linear active disturbance rejection control algorithm for active vibration control of piezo-actuated beams: Theoretical and experimental studies

The active vibration control (AVC) of lightweight thin-walled structures on spacecraft has been a proven solution for vibration suppression. In this study, a linear active disturbance rejection control (LADRC) algorithm is presented for vibration suppression of piezo-actuated beams. Firstly, the governing equation of a piezo-actuated beam is obtained by using the Euler–Bernoulli beam theory and the Lagrange equation. The LADRC algorithm is designed for the piezo-actuated beam based on the governing equation. Then, the accuracy of the piezo-actuated beam model is confirmed by comparison with ANSYS and experiments. Finally, numerical simulations and experiments are carried out on the active vibration suppression of the piezo-actuated beam under the fixed harmonic excitation, variable harmonic excitation, and fixed harmonic excitation with measuring noise, respectively. The results show that the LADRC algorithm has an excellent control effect on structural vibration suppression, strong adaptability to various external excitations, and anti-noise ability.

Active control of earthquake-excited structure using a torsional servomotor active mass driver system

Servomotor system has advantages of low cost, small size, good controllability, and less maintenance in driving mass movement. In this study, a torsional servomotor active mass driver (AMD) system is developed to actively control an earthquake-excited structure. A relation between the mass inertial force and servomotor rotational speed is established as the transfer function of an uncontrolled AMD. A control algorithm consisting of the linear quadratic regulator (LQR) and Kalman filter is designed to control the transfer function in real time only using acceleration measurements. With the help of LabVIEW platform, a user-programmable AMD controller including data acquisition, data processing, and motor control is developed. Finally, shaking table tests of a three-story steel frame equipped with developed AMD system subjected to earthquake excitations are conducted. The results show that the torsional servomotor AMD system performs quite well in reducing the displacement and acceleration responses of the earthquake-excited steel frame. The root-mean-square displacement and absolute acceleration of the top floor greatly decrease with nearly 70%. The damping ratio of the steel frame is greatly improved from 0.17%∼0.29% to 1.25%∼2.25% after implementing the torsional servomotor AMD control. Besides, a phenomenon of good control in both first-mode and second-mode vibrations is observed to validate the active control superiority.

Analytical parameter tuning for a class of extended disturbance observers and sliding mode control

This paper studies the parameter tuning problem for a class of extended disturbance observers (EDO) and the EDO-based sliding mode control (SMC). Based on a H2 optimization technique, analytical solutions for the parameter tuning of the EDO and the EDO-based SMC are obtained. The conditions under which higher-order EDOs are strictly better than lower-order EDOs are derived analytically. Furthermore, the steady-state performance of the EDO-based SMC is analyzed, where it is shown that the improvement of the tracking accuracy of the EDO can reduce the sensitivity of the state variables and the control input with respect to the controller parameters. This implies that the SMC parameter tuning requirement can be reduced if a high tracking accuracy of the EDO is guaranteed. Finally, the application to the active structural control problem of an offshore wind turbine is studied and the effectiveness of the obtained results is demonstrated based on a National Renewable Energy Laboratory (NREL) 5MW baseline offshore wind turbine.

Data-driven model reduction approach for active vibration control of cable-strut structures

The cable-strut structures have the features of low stiffness and weak damping, resulting in large vibration response under dynamic excitation. The vibration response of the cable-strut structures can be reduced by active control methods. However, many traditional active control methods need to build a state-space model (SSM) based on finite element model (FEM), and solving the active control force for the high-dimensional SSM is time-consuming. In this paper, the dynamic mode decomposition with control (DMDc) method is proposed to achieve a data-driven reduced-order SSM for active vibration control of cable-strut structures. This proposed method only uses the data of structural response and control force input to build reduced-order SSM and does not rely on the FEM. Linear quadratic regulator (LQR) design using the DMDc-based reduced-order SSM (DMDc-LQR) is more computationally efficient than that using the FEM-based SSM (FEM-LQR). The relationship between the design parameters of the DMDc-LQR controller and the FEM-LQR controller is established, which ensures that the control performance indexes of the DMDc-LQR controller and the FEM-LQR controller are equal. The effectiveness of the proposed DMDc-LQR method is validated using numerical Kiewitt cable dome and tensegrity grid under wind and seismic loads. The results show that the DMDc-LQR controller maintains similar control effect to that of the FEM-LQR controller and has advantage of high computing efficiency as well. In addition, the influence of critical parameters (i.e., data noise and model order) on vibration control effect is comprehensively explored. It is found that increasing the model order is effective to mitigate the noise influence on the DMDc-based reduced-order SSM and ensures the effectiveness of the DMDc-LQR controller.

Reliable Model Predictive Vibration Control for Structures with Nonprobabilistic Uncertainties

This paper proposes a novel reliable model predictive control (MPC) method for active vibration control of structure with nonprobabilistic uncertainties. First, the framework of reliable MPC is established by integrating nonprobabilistic reliability constraints into nominal MPC. Based on the first‐order Taylor expansion and first‐passage theory, an efficient nonprobabilistic reliability analysis method that is suitable for online computation is proposed. A nonprobabilistic Kalman filter is further proposed for determine system states and their uncertain region. Unlike most robust MPC approaches, the proposed reliable MPC focuses on the satisfaction of state constraints in terms of structural reliability and is more suitable for structures with stringent safety requirements. Compared to existing reliability‐based vibration control methods, reliable MPC requires no knowledge of disturbance and exhibits greater adaptability to load environments. The effectiveness and superiority of the proposed reliable MPC are validated through a numerical example and an engineering case study.