Semi-active Control Algorithm Research Articles

Adaptive semiactive control of structure with magnetorheological dampers using wavelet packet transform

Conventional active controllers generally adopt initial dynamic properties of intact structures to calculate optimal control force for magnetorheological damper, which eventually leads to ideal damping force of the device. Also, they cannot assure trade-off between damping force and response reduction under non-stationary excitations. To this end, an adaptive semiactive control algorithm for magnetorheological damper is proposed. Using wavelet packet transform, an improved control law determines optimal control forces in terms of resonant and non-resonant frequency bands in time interval. Both frequency bands are established based on natural frequency(ies) of structures, making damping force rely on actual structural properties and achieving trade-off under non-stationary disturbances. A refined clipped-optimal control algorithm is then deployed to convert optimal control force to the device’s voltage. A numerical study of a six-degree-of-freedom structure under four near- and far-fault ground accelerations reveals that the scheme outperforms existing controllers while attaining cost-effectiveness of damping force versus response alleviations.

Research on Inertial Force Attenuation Structure and Semi-Active Control of Regenerative Suspension

To improve the energy recovery ability of the energy-regenerative suspension, a transmission is generally used to increase the motor speed, but this results in a significant increase in the equivalent inertial mass of the suspension. The research on energy-regenerative suspension has been ongoing for more than 20 years, but there have been few product applications, mainly due to the failure to solve the problem of the deterioration of suspension performance caused by equivalent inertial mass. This paper proposes a new suspension configuration with the suspension shock absorber connected to a high-frequency vibration reduction structure and establishes a vibration transmission model. Through frequency domain analysis, it has been conclusively proven that the new-configuration can significantly reduce both the sprung mass acceleration and relative dynamic load of the energy regenerative suspension. On the basis of frequency domain analysis, a scheme based on PWM control of the dissipation resistance value of the energy regenerative suspension is proposed, and through bench comparison experiments, it has been verified that the new-configuration suspension can eliminate the oscillation of the damping force curve of the shock absorber and significantly improve the suspension performance. Further experiments show that using the skyhook semi-active control algorithm the new-configuration suspension can further reduce the sprung mass acceleration and relative dynamic load.

Magnetorheological Fluid Dampers: A Close Look at Efficient Parametric Models

The reasonable efficiency, high reliability, and minimal maintenance requirements of the semiactive control algorithms make this form of structural control the most successful method from a practical point of view. In addition, significant progress has been made in structural control devices. Magnetorheological (MR) dampers have been the subject of extensive research. In order to develop and implement a successful structural control algorithm, a deep understanding of their operation is required. Therefore, many efforts have been made to classify MR dampers as efficient tools; however, their complicated behavior has also been noted. Various relations have been proposed to describe the highly nonlinear behavior of MR dampers. To develop an efficient control algorithm, one must first properly understand the seismic behavior of the structure and the control device as well as its handling. The handling of the device will be efficient if there is a description for its control, a so-called inverse model. This model is an answer to the question of whether the proposed device model can be written in a form that practically brings the generated damping force as close as possible to the desired force. In the identification process, the selection of a basic mathematical model is critical. In this review article, we have compiled successful parametric models that accurately replicate the behavior of MR dampers. Since the primary functionality of the device is crucial for the development of a competent control algorithm, we have endeavored to investigate and present the reversibility of the proposed models. We also delved at the characteristics of the parameters that enable precise communication between the central control unit and the device. These parameters, which enable the dialog between the processing unit and the control devices, will play an important role in the development of the inverse model in its simplicity and efficiency.

Seismic control of adaptive variable stiffness intelligent structures using fuzzy control strategy combined with LSTM

A novel semi-active control algorithm for adaptive variable stiffness intelligent structures that combines the fuzzy control strategy with Long Short-Term Memory (LSTM) is proposed in this study, with the aim of mitigating structural responses under earthquake excitations. The combined Fuzzy-LSTM strategy utilizes an LSTM neural network to predict the displacement and velocity responses of the structure at the next moment, and uses the predicted results as input for fuzzy control to obtain active control forces. Due to the difference between the displacement-velocity response and the fuzzy control domain, the genetic algorithm is used to optimize scaling factors of displacement and velocity responses and the control force, which is implemented by exploiting stiffness variability and structural inter-shift. The Fuzzy-LSTM strategy can compensate for the time delay effect on active control caused by stiffness variations, algorithmic computations and sensor measurements, and therefore achieves a better control effect through prediction. The semi-active independently variable stiffness (SAIVS) device is used to implement the presented control algorithm, which is a diamond device consisting of four linear springs and an electromagnetic actuator. The SAIVS device can achieve a continuous and smooth stiffness variation and meet the application requirements of the developed algorithm. Therefore, active control forces can be obtained through structural stiffness variations and interlayer displacements under seismic excitation, to achieve an approximate active control effect through a semi-active method. A 10-story building is presented as a case study for numerical simulations. Results show that the Fuzzy-LSTM strategy can significantly improve the control effect compared to the conventional fuzzy control strategy, and therefore achieve a better seismic response mitigation performance.

Optimal Control of Semi-Active Suspension for Agricultural Tractors Using Linear Quadratic Gaussian Control.

In this study, a semi-active suspension based on a hydro-pneumatic mechanism was designed to minimize the ride vibration using a suspension control algorithm. The performance of the algorithm was critical for controlling the characteristics of the target tractor. A linear-quadratic-Gaussian (LQG) optimal control algorithm was designed as a semi-active suspension control algorithm. The plant model for developing this algorithm was based on the parameters of an actual tractor. The rear suspension deflection was represented by a Kalman-filter-based state observer feedback to estimate the state variables that were difficult to measure. The designed state observer of the LQG controller was validated in terms of an accuracy index. The estimated vertical velocity and acceleration accuracies of the cabin were 83% and 79%, respectively. The performance of the designed controller was validated in terms of a performance index by comparing the performance of a tractor equipped with a rear rubber mount with that of one equipped with a semi-active suspension. The peak and root-mean-square values of the vertical acceleration of the cabin were reduced by up to 48.97% and 47.06%, respectively. This study could serve as a basis for the application of the control algorithm to systems with similar characteristics, thereby reducing system costs.

Seismic Response Control for Bridge Piers with Semi-Active MR Damper Based on Displacement Feedback

ABSTRACT This study investigates the semi-active control of railway bridges using an MR damper to reduce the excessive displacement in the bearings of isolated bridges under severe earthquakes. Within the study context, the variable-oval-control (VOC) rule based on structural response displacement feedback is applied to the MR damper and compared with a passive control and clipped optimal semi-active control algorithm. The simulation results show that the dynamic response of railway bridge piers can be effectively reduced, and seismic safety can be significantly improved using MR dampers based on a variable ellipse control strategy. MR damper, based on the VOC rule, directly adopts structural response displacement to perform control force state change. The VOC method only requires the minimum control force to achieve a good displacement control effect, high control efficiency, and stable control effect.

A novel semi-active suspension algorithm based on a high-precision frequency selector

This study proposes a novel semi-active suspension control algorithm based on a high-precision frequency selector. The algorithm focuses on the phenomenon of redundant switching in frequency domain judgment. Furthermore, the working principle of realizing high-precision selection is explained. The behavior of window sample number N is analyzed theoretically, and the gray prediction theory is used, together with a formerly sampled signal, to predict and obtain advanced output. This can compromise time delay in the control strategy and improve the accuracy of the selector. Using the combined sky-hook and acceleration-driven damper control algorithm and the MIX algorithm as the benchmark, the improved frequency selector is verified under sweep road environments. The results demonstrate that the improved algorithm significantly reduces the number of switches that occur while driving the vehicle, without deteriorating the comfort, thus improving the energy efficiency and service life of the damper.

Development of a Control Algorithm for a Semi-Active Mid-Story Isolation System Using Reinforcement Learning

The semi-active control system is widely used to reduce the seismic response of building structures. Its control performance mainly depends on the applied control algorithms. Various semi-active control algorithms have been developed to date. Recently, machine learning has been applied to various engineering fields and provided successful results. Because reinforcement learning (RL) has shown good performance for real-time decision-making problems, structural control engineers have become interested in RL. In this study, RL was applied to the development of a semi-active control algorithm. Among various RL methods, a Deep Q-network (DQN) was selected because of its successful application to many control problems. A sample building structure was constructed by using a semi-active mid-story isolation system (SMIS) with a magnetorheological damper. Artificial ground motions were generated for numerical simulation. In this study, the sample building structure and seismic excitation were used to make the RL environment. The reward of RL was designed to reduce the peak story drift and the isolation story drift. Skyhook and groundhook control algorithms were applied for comparative study. Based on numerical results, this paper shows that the proposed control algorithm can effectively reduce the seismic responses of building structures with a SMIS.

Deep Reinforcement Learning of Semi-Active Suspension Controller for Vehicle Ride Comfort

Among the controllable suspension systems, the control of the semi-active suspension is mostly based on optimal control. Recently, deep reinforcement learning is widely used as a method to solve the optimal control problem. Control strategies developed using reinforcement learning have shown performance beyond conventional control algorithms in some fields. In the current study, we have proposed a near optimal semi-active suspension ride comfort controller using deep reinforcement learning. An algorithm suitable for a semi-active suspension control environment was selected based on deep reinforcement learning theory to increase convergence in training. Furthermore, a state normalization filter was designed to improve the generalization performance. When compared with the ride comfort oriented classical control algorithms, our trained controller showed the best performance in terms of ride comfort. Policy map comparison with mixed SH-ADD (Skyhook-Acceleration Driven Damping) algorithm suggested the direction to the design of the semi-active suspension control algorithm.

Velocity Tracking Control Algorithm for Semiactive Control of Building Frames

A new control algorithm called velocity tracking control (VTC) is presented for the semi-active control of partially observed building frames using magneto-rheological (MR) dampers. The novelty of the control algorithm relies on the use of special features of the semi active control using MR dampers in which the time history of voltage to be applied to the MR damper can be generated with the help of feedback information from the observed states only; it does not require the estimation of the full state from the measured ones which introduces some errors in the estimated control force generated in the MR damper. The algorithm is developed based on a physical reasoning, which is validated by the Lyapunov stability condition of the first order filter used in the modified Bouc-wen model that models the MR damper. The efficiency of the control algorithm is compared with the passive on control for a number of earthquakes. The response quantities of interest, for which percentage reductions in responses are compared, include the peak top floor displacement, peak inter-story drift and maximum base shear. The results of the study show that the proposed control algorithm provides the maximum percentage reduction in peak inter-story drift in comparison to passive on control. Further, the efficiency of the proposed control algorithm, defined by the percentage reduction of responses per unit control force, is found to be more as compared to the passive on control.

Optimal control of structural vibration using LQG algorithm

This paper proposes a Linear Quadratic Guassian Design (LQG) with based semi-active control algorithm for vibration reduction of building structures. The controlled damper force required by the structure has been calculated from an MR damper of load capacity 100N. A building frame has been selected to illustrate the performance of the proposed algorithm. Four different earthquake acceleration data has been used as input vibration data to the numerical frame. The proposed method of damping on the frame has been found to be more effective to reduce the structural response significantly in comparison with the conventional tuned liquid column damper. The developed method is efficient in providing the optimum control force required to the frame. Therefore, it minimizes the need of high damping capacity and the number of dampers. As a result, it reduces the cost of maintenance and structural control during earthquakes.

Semi-Active Control of Seismic Response on Prestressed Concrete Continuous Girder Bridges with Corrugated Steel Webs

To improve the seismic capacity of prestressed concrete (PC) continuous girder bridges with corrugated steel webs (CSWs), suitable damping control measures can be used to effectively reduce the seismic response of the bridge. Based on the semi-active control theory, the semi-active control system of a three-span PC continuous girder bridge with CSWs is designed, and the semi-active control system program of the three-span PC continuous girder bridge with CSWs is compiled by MATLAB. The time–history curves of damper energy consumption of active optimal control algorithm and three different semi-active control algorithms are compared and analyzed, as are the time–history curves of main girder displacement, acceleration, and pier internal force with or without semi-active control. The study shows that the rational determination of the weight matrix coefficient can make the active control achieve a better vibration absorption effect and economy. The semi-active control algorithm of Hrovat has the best vibration absorption effect, which is closest to that of the active optimal control algorithm. Under the state of semi-active control, the average vibration absorption rate of displacement and acceleration of the main girder with CSWs are 71% and 20%, respectively. The time–history curve of bending moment and shear force in the pier bottom is similar, and the average vibration absorption rate of bending moment and shear force at the bottom of pier #2 is 70%. At the same time, the average vibration absorption rate of bending moment and shear force at the bottom of pier #3 is between 42% and 48%. The semi-active control measure has a good vibration absorption effect on the overall seismic response of the PC continuous girder bridges with CSWs. This study provides a certain reference for the seismic reduction and isolation design of composite structure bridge with CSWs.

New magnetorheological engine mount with controllable stiffness characteristics towards improved driving stability and ride comfort

Engine mount is an important subassembly installed between the chassis and the engine. Its importance is mainly reflected by its capability of protecting the car body from the engine-induced vibrations. The current semi-active engine mount works to mitigate the vibration by changing its damping, while the property of variable stiffness can further suppress the vibrations by reducing the vibration transmissibility. Therefore, this paper developed a new magnetorheological engine mount which can change its stiffness to shift the natural frequency of the mounting system away from the excitation frequency so that resonance can be avoided when the engine is starting. The stiffness controllability also meets the stiffness design conflict between vibration isolation requirement and engine stability requirement when the cars drive on rough roads. The characterization test has verified its field-dependent properties that the effective stiffness has increased by 80.65% and the equivalent damping coefficient has increased by 26.85% as the applied current increases from 0 A to 1.5 A. Then a vibration isolation test was performed to evaluate the mounting system’s vibration reduction performance using a commercial internal combustion engine. The test results verified that the new magnetorheological engine mount under the semi-active control algorithm named Short Time Fourier Transformation is much better at suppressing the engine-induced vibrations than under passive control. And finally, a stability test was conducted and it verified that the new magnetorheological engine mount under Short Time Fourier Transformation control algorithm (semi-active control) performed better stability than the passive control. These experimental results indicate that this new magnetorheological engine mount is highly effective in isolating the engine-induced vibrations and keeping the driving stability.

Real-time neural network based semiactive model predictive control of structural vibrations

Semiactive model predictive control (sMPC) can be very effective, but its computational cost due to the inherent mixed-integer quadratic programming (MIQP) optimization precludes its use in real-time vibration control. This study proposes training neural networks (NNs) to predict in real-time only the MIQP’s integer variables’ values, called a strategy, for a given structure state. Because the number of strategies is exponential in the number of sMPC horizon steps, the resulting NN can be massive. This study proposes to reduce the NN dimension by exploiting the homogeneity-of-order-one nature of this control problem and, using state vector statistics, to efficiently choose training samples. The single large NN is proposed to be split into several much smaller NNs, each predicting a strategy grouping, that together uniquely and efficiently predict the strategy. Given the strategy’s integer values, the MIQP optimization reduces to a quadratic programming (QP) problem, solved using a fast QP solver with proposed adaptations: exploiting optimization efficiencies and bounding sub-optimality; using several NN predictions; and reverting to a simpler (suboptimal) semiactive control algorithm upon occasional incorrect NN predictions or QP solver nonconvergence. Shear building examples demonstrate significant online computational cost reductions with control performance comparable to the conventional MIQP-based control.

A semi-active control method for magnetorheological dampers to suppress the milling vibration of thin-walled workpieces

Thin-walled workpieces are widely used in the aerospace field, and milling is the main processing method of such components. However, thin-walled workpieces are prone to vibrate during milling because of their weak stiffness, and the vibrations significantly affect the processing quality. Therefore, it is important to develop a novel milling vibration suppression method for thin-walled parts. The present work focused on the milling vibration control of a thin-walled workpiece using a semi-active magnetorheological (MR) damper. The forward dynamic model and inverse control model of the MR damper were first established, and its actuating position on the workpiece was then determined by modal analysis. The dynamic model of the MR damper at this position was built based on the proposed dynamic parameter acquisition method and used in the following semi-active control algorithm design. The effectiveness of this algorithm was verified by MATLAB/Simulink simulations. Finally, six groups of milling experiments were carried out using the non-damper, the rigid rod, the damper applied with 1-, 2-, and 3-A currents, and the semi-active control damper to validate the practical effect of the proposed algorithm. It was found that the designed semi-active control MR damper outperformed the constant-current control dampers or the rigid rod. In comparison to the non-damper experiment, the root mean square (RMS) values of milling forces in x- and y-directions decreased by 45.12% and 48.58%, respectively, and surface roughness decreased by 40.22%.

Research on semi-active control of long and large-span continuous beam bridge vibration reduction considering system fault tolerance

In order to reduce the seismic response of long and large-span continuous beam bridge, this paper carried out a study on vibration reduction control of long and large-span continuous beam bridge, and magnetorheological dampers are used to provide control force for the control scheme. Based on the LQR classic optimal active control algorithm, a semi-active control algorithm considering system fault tolerance is proposed. When some dampers fail, the fault-tolerant control algorithm provides compensation output to the control system, so that the control system can still maintain the expected control effect. The actual engineering example of a long and large-span continuous beam bridge is selected, and a finite element analysis program is written. The semi-active vibration reduction control of the long-span continuous beam bridge is calculated and analyzed in various combinations of working conditions. The calculation results show that the method in this paper has achieved good results in controlling the seismic response of the bridge structure.

Modeling and simulation of magnetorheological dampers for the reduction of the seismic response of structures using simulink

The control devices can be used to dissipate the energy of structures subjected to dynamic loads in order to reduce structural damage and prevent the failure of them. The semiactive control devices that have received great attention in recent years are magnetorheological (MR) fluid dampers due to their mechanical simplicity, high dynamic range, large temperature operating range and low power requirements. In the present research work, Matlab and Simulink are used as computational tools for the modeling and simulation of structural control systems with magnetorheological dampers (MRDs). To begin with, the modeling is carried out through simulink block diagrams of the governing differential equations of representative mathematical models of MRDs. Next, a series of simulations is performed in order to replicate experimental results and to be able to validate the modeling step. Finally, the MRDs are integrated together with a semiactive control algorithm and an idealized ten-degrees-of-freedom structure. The main expected outcome is the reduction of the seismic response (response histories, drifts, shear forces and overturning moments).

Experimental investigations on the semi-active control of a valve-driven secondary lateral damper for a high-speed rail vehicle

Passive suspensions cannot sufficiently reduce vehicle vibrations on tracks with poor irregularities or when the vehicle was operated at higher speeds. This study proposes three semi-active control algorithms for a secondary lateral damper to enable the vehicle to be operated on high-speed dedicated railways at 350 km/h and conventional low-speed railways at 160 km/h. A high-speed rail vehicle dynamics model with controllable dampers is built to study the feasibility of those algorithms through numerical investigations. Then, both field tests on track and lab tests on a full-scale roller rig were performed to examine the functionality of the controller hardware system and the valve-driven semi-active damper. Furtherly, a time-delay compensation based on the signal amplitude is developed and verified. Results from the on-track and roller rig tests state that the proposed semi-active control algorithms and the designed control system can effectively improve the ride quality of the vehicle when it is put into operation in different track conditions and at various speeds.

A semi-active control algorithm for nonlinear structures based on uniform distribution of deformation theory

Semi-active control is a promising method for vibration control of civil structures. Magneto-rheological (MR) damper is one of the most common and practical devices among other semi-active control devices. The command voltage is the only controllable property of an MR damper. There are several algorithms for determining the MR damper command voltage such as active control-based algorithms. On active-based algorithms, an initial reference control force is achieved based on a reference active control algorithm, then this force converts to applied voltage. Uniform Distribution of Deformations (UDD) theory is a concept which intends to use the maximum capacity of elemental and structural ductility. When deformations are uniform throughout the entire structure, damages are mostly uniform and the maximum of damage is reduced. This point can be used for designing a new active-based semi-active algorithm. The innovative Uniform Deformation Control (UDC) is an active-based control algorithm. Reference active control forces are achieved using a massless Virtual Added frame with Pinned connections (VAP). This virtual frame makes deformation of the structure more uniform. The axial forces of the VAP beams are the reference active control forces. Afterward, based on these forces, the command voltages of semi-active MR damper are determined. The VAP characteristics are optimized using Charged System Search (CSS) optimization method for making the structural deformations more uniform. Therefore, this new innovative proposed algorithm focuses on reducing damages contrary to common algorithms which focus on reducing responses. The contribution of the present paper is to introduce the new damage-based algorithm. Then, this algorithm will be investigated in comparison with two other common algorithms. The effectiveness of the new proposed algorithm is proved via nonlinear numerical investigations on an office building. The new algorithm can reduce displacements and accelerations with relatively low control forces while making deformations more uniform.

Emotional Learning based adaptive control algorithm for Semi-Active seismic control of structures

A tuned mass damper (TMD) is a passive mass-spring system, widely accepted as an effective response control strategy for a structure under external excitation. The inherent passive nature, optimum tuning requirements of TMDs are known to lead to sensitivity problems and/or detuning of the TMDs for changing vibration conditions, limiting their performance to narrow band of input excitation. Due to these limitations, semi-active control concepts are used to introduce adaptability in passive TMDs. Semi-active response control using TMD is much researched in recent years for protection of civil engineering structures against earthquake. In this study, the efficacy of a semi-active mass driver (MD) system coupled with magnetorheological (MR) damper is investigated for seismic response control of a primary structure. The input current to the MR damper in the semi-active MR-MD is controlled using an adaptive Brain Emotional Learning Based Intelligent Controller (BELBIC) control algorithm in a closed loop architecture. The efficiency of the damping addition from the MR damper to the mass driver which is reducing the response of the primary structure is investigated using analytical and simulation studies, considering off-tuning, emulated using three different tuning cases of the MR-MD. From the studies, it is found that semi-active MR-MD is performing satisfactorily in reducing the seismic response of the primary structure and BELBIC algorithm performs efficiently even during off-tuning conditions and presence of physical constraints.