Active Control System Research Articles

Research on fast optimal reference sensor placement in active road noise control

The noise reduction performance of the active road noise control (ARNC) system highly depends on the location of the reference sensors. Generally, the optimal sensor locations are evaluated by calculating the multiple coherence function (MCF) between all possible reference signal combinations with road noise. However, this trial-and- error method becomes time-consuming when the number of candidate locations is large. The transfer path analysis method can select the optimal sensor locations quickly while with low accuracy. Therefore, this article proposes two fast optimal sensor placement (FOSP) methods, namely, Wiener filter (WF)-FOSPand the MCF-FOSP, respectively. In both methods, the sensors are iteratively extended to the desired number, and each added sensor maximizes the predicted noise reduction of this iteration loop. Numerous ARNC simulations based on measured signals are conducted to illustrate the performance of the proposed two methods in terms of efficiency and accuracy. The results demonstrate that the WF-FOSP method provides the best comprehensive performance. The data analysis for one operating condition takes three minutes, and the absolute error is within 5% with respect to the benchmark. In addition, two schemes are discussed to obtain a set of sensor locations compatible with the noise reduction requirement of different operating conditions. The sensor locations can achieve a maximum average noise reduction of 7.29 dB(A) under four operating conditions.

Warmstarting strategies for convex optimization based multi-channel constrained active noise control filter design

In real-world applications of active noise control (ANC) systems, various constraints are supposed to be satisfied in the controller design process. The optimal control filter coefficients can be obtained by solving a constrained optimization problem, which usually requires a significant computational effort. Recently, a convex formulation in conic form was proposed for ANC filter design. The proposed formulation was shown to result in a computational time reduction by several orders of magnitude. It is of great interest to further improve its efficiency by using a priori information of the optimal filter coefficients. One potential way of achieving this goal is to introduce a warmstart technique so that the filter solution of a similar system or environment can be referred to for selecting the starting point of the optimization algorithm. However, the conic formulation should be solved by the interior-point method, which, in general, is challenging for applying warmstart techniques. In the current work, relaxation methods are proposed to the constraints of original ANC filter design formulation so that the warmstart techniques can be applied. Then, a warmstarting technique proposed in previous study is used to solve a series of perturbed problems, and the performance of the warmstarting technique is investigated. Results show that with the proposed modifications applied, the warmstarting strategy can significantly reduce the number of iterations needed for solving the conic formulation of the ANC filter design problem without much tuning efforts, and the method is effective and robust in various environmental setups.

Attitude Control of Quadrotor UAV Using Improved Active Disturbance Rejection Control

The quadrotor UAV has complex aerodynamics, unstable altitude, and easy to be disturbed by internal and external uncertainties during flight, so good attitude control becomes a challenge, this paper improves the active disturbance rejection controller to improve the system's anti-jamming ability and response speed in response to the above problems. Firstly, a quadrotor UAV dynamics model is established; then the Ifal function is constructed, which solves the problems that the inflection point of the fal function is not smooth, which is easy to cause the system jitter and the system gain is large when the error is large, and finally the performance is verified by using MATLAB/Simulink simulation software. The simulation results show that the constructed Ifal function is smoother and has better convergence, and compared with the traditional active disturbance rejection control, the improved active disturbance rejection control system has faster response speed, stronger anti-jamming ability and robustness in the attitude control of quadrotor UAV.

Vibration Control of Innovative Lightweight Thermoplastic Composite Material via Smart Actuators for Aerospace Applications

Piezoelectric actuators and sensors can be incorporated into aerospace structures to suppress unwanted flexible oscillations. These devices need to interact with various passive structures, including innovative materials such as thermoplastic composites, which offer several advantages over traditional options. This study explores the application of a piezoelectric-based vibration control system on a lightweight carbon-reinforced thermoplastic material. Numerical and experimental investigations are conducted to assess the mechanical properties and damping behavior of the composite. As a case study, an equivalent orthotropic shell laminate is developed to facilitate finite element modeling of two composite solar panel structures equipped to a spacecraft. Moreover, an electro-mechanical formulation is implemented to integrate smart actuators and sensors onto the composite hosting structure. Finally, the efficiency of the active vibration control system is assessed when significant vibration perturbations are caused on the panels by rigid–flexible dynamics coupling during agile attitude maneuvers. The results demonstrate the damping factor of the material can be noticeably improved, making the proposed system a promising technological solution for further aerospace applications.

A fuzzy based intelligent scheme for enhancing the performance of the optimal controllers by online weighting matrix selection in seismically excited nonlinear buildings

In the present work, an effective strategy is proposed to improve the efficiency of the optimal controllers that are based on minimizing a performance index by using a fuzzy controller. In the used fuzzy system, the weighting matrices of the optimal controller are tuned online according to the response of the structural system. In order to assess the effectiveness of the proposed control scheme, its function is investigated in two phases on a 3-story nonlinear benchmark building equipped with MR dampers. In the first phase, a linear quadratic Gaussian (LQG) controller is combined with a fuzzy logic system (Fuzzy-LQG) and the efficiency of the used technique is compared with three different cases of the conventional LQG controllers. The results show that the Fuzzy-LQG, in addition to using an optimal level of demand energy, has a better performance than the conventional LQG methods in controlling the maximum responses of the structure. In the second phase, the performance of a polynomial optimal controller that is a summation of polynomials in nonlinear states in combination with the fuzzy system is investigated. At this stage, the effectiveness of the designed control system (Fuzzy Polynomial) in terms of seismic performance criteria with the results of a conventional LQG active control system, an optimal adaptive neuro-fuzzy inference system (ANFIS) and a neural network predictive control (NNPC) system is evaluated. The results show that this method is successful in improving the structural performance of a nonlinear building subjected to earthquakes.

An active piezoelectric damping vibration control system for the sting used in wind tunnel

In wind tunnel tests, the cantilever sting supporting system often suffers from low-frequency and large-amplitude resonance due to its inherent low structural damping characteristic, resulting in the degradation of data quality and structural safety. To improve wind tunnel testing safety and data accuracy, this paper is dedicated to establish an active vibration control system using piezoelectric stack actuators. A novel methodology of vibration monitoring based on modal transformation, which uses measured strain and a Strain-to-Displacement Transformation (SDT) matrix to reconstruct dynamic displacement field, is proposed herein. Meanwhile, strain sensor positions are optimized by an improved Particle Swarm Optimization (PSO) algorithm to reduce systematic estimation errors of this method. Furthermore, a Back-Propagated Neutral Network (BPNN) is established to implement a self-adaptive control strategy. A series of verification tests are performed to demonstrate the validity of the proposed system. Experimental results indicate that the relative Root Mean Square Error (RMSE) between estimated vibration displacement and measured vibration displacement is less than 3%, and a vibration attenuation of over 14 dB/Hz is achieved in ground tests, proving the superiority of this intelligent active vibration suppression system.

ANALYSIS OF ACTIVE SECONDARY SUSPENSION WITH MODIFIED SKYHOOK CONTROLLER TO IMPROVE RIDE PERFORMANCE OF RAILWAY VEHICLE

The aim of this work is to determine the effectiveness of active suspension control systems in improving the ride quality of railway vehicles. A 13-degrees-of-freedom (DOF) full-body model is provided, including lateral, yaw, and rool motions of the body and bogies, and lateral displacement of the four wheelsets. The suspension system of railway vehicles and the dynamics of track irregularities are combined in a set of governing equations. MATLAB/Simulink is used to build a full-body dynamics model of a rail vehicle. The effectiveness of the active suspension systems equipped with the suggested controller has been tested for the purpose of evaluating its performance. Compared to passive systems, the results showed a more than 60 % improvement in vehicle performance on irregular tracks.

A Novel Tandem Differential Edge Sensor Layout for Segmented Mirror Telescopes.

The performance of an active control system, crucial for the co-phase maintenance of segmented mirrors, is closely related to the spatial layout of sensors and actuators. This article compares two types of edge sensor layouts, vertical and horizontal, and proposes a novel tandem differential sensor layout that saves layout space and reduces the number of positioning references. The control performance of this scheme is analyzed in terms of error propagation, mode representation, and the scalable construction of the control matrix. Finally, we constructed a tandem differential-based sensor detection system to examine the performance of edge sensors and the effect of laboratory environmental variables on sensor measurements. Simulations and experiments demonstrate that this scheme has the same ability to fully characterize actuator modification modes as the Keck edge sensor layout. Although the total error multiplier is slightly larger than the latter, it has fewer scalable control matrix types and stronger spatial and segmental shape adaptation capabilities. Actual measurements show that the sensor's own noise in a tandem differential layout is less than 20 nm, which meets the requirements for future segmented co-phase maintenance. This layout type can potentially be applied to future small and medium-sized segmented splices.

An experimental study on the upper limit frequency of global active noise control in car cabins

In this case study, the upper limit frequency for global noise control in car cabins is investigated with numerical simulations, and experimental results of global control are presented for the first time. To simulate the complicated noise field in a running car, a 1.90 m × 1.50 m × 1.10 m rectangular enclosure, which is approximately the size of a typical car is used with point monopoles evenly distributed near the boundaries generating the primary sound field. Besides verifying the fact that the upper limit frequency of effective control increases with the number of secondary sources, a formula is proposed in this paper to estimate the number of secondary sources required to achieve global control up to a certain frequency. The simulations are carried out in the time domain based on the transfer functions measured between the secondary loudspeakers and 40 evaluation points evenly distributed in a typical car, which show that the upper limit frequency of 3 dB global control is about 200 Hz while using 4 secondary sources and it can be improved to 315 Hz with 7 secondary sources. An active noise control system is realized with 16 accelerometers picking up vibration reference signals and 4 or 7 loudspeakers as secondary sources, and the real time test results in the car running at 50 km/h on a typical asphalt road demonstrated the validity of the findings in numerical simulations.

Retracted: Active Compliance Control System for Intelligent Inspection Robot in Power Room

Retracted: Active Compliance Control System for Intelligent Inspection Robot in Power Room

Research on precise control of piston eccentricity by electromagnetic levitation in labyrinth piston compressor

The piston in the Labyrinth piston compressor (LPC) usually runs eccentrically in the cylinder, which results in large internal leakage and low volumetric efficiency. An active electromagnetic control method based on the electromagnetic levitation theory was proposed in this paper to control the piston eccentricity, and a triple close-loop multi-factor coupled feedback control strategy composed of a current loop, a velocity loop, and a displacement loop was designed to realize the levitation control of the piston. The experimental research shows that there is serious piston eccentricity in the LPC, and the piston eccentricity is positively correlated with the increase of compressor pressure ratio and speed. By adopting the active electromagnetic control system proposed in this paper, the piston eccentricity is significantly reduced, and the maximum reduction is over 88%. Further research shows that the volume flow rate and volumetric efficiency of the LPC with control are maximum improved by about 45.6% and 44%, respectively. In conclusion, the piston eccentricity in the LPC could be effectively reduced by adopting the active electromagnetic control method proposed in this paper, thus improving its performance.

Modeling and design of magnetorheological elastomer isolator system for an active control solution to reduce the vibration transmission in elevator context

The attenuation of the structure-borne sound caused by elevator systems in residential buildings is a priority for manufacturers. This work develops a model of an active control isolation system for the vibrations produced by the elevator drive machine. This solution proposes the substitution of conventional passive isolators by new ones made of a magnetorheological elastomer (MRE), a smart material whose modulus can be modified by applying a magnetic field. To guide the design process, MRE isolators are fabricated and experimentally tested statically and dynamically in compression mode. Subsequently, the parameters of the MRE are fitted to build a nonlinear material sub-model that accounts for the frequency, amplitude, and magnetic field dependency. Afterward, a global model of the elevator drive machine vibration isolation system is developed, which incorporates the drive machine, structure, and MRE-based isolator. To enhance vibration isolation, two active control strategies are designed and assessed. Simulation results predict that active control systems based on MRE isolators improve vibration isolation as compared to traditional passive systems. The excitation amplitude and frequency, along with the control strategy and magnetization of the MRE isolators are shown to be critical parameters when designing an active control solution.

Model Experimental Study on a T-Foil Control Method with Anti-Vertical Motion Optimization of the Mono Hull

T-foils with active control systems can adjust their attack angle according to the movement of the ship in real time, providing higher lift force and improving the seakeeping performance of a ship. The optimization of the control signal and that of the control method have an important influence on the effect of active T-foils. In this paper, the control method of the T-foil’s swinging angle is established and optimized on the basis of model testing in order to increase the effect of the T-foil. First, the governing equation is introduced by establishing the proportional relationship between the angular motion of the hull and the lift moment of the T-foil. On the basis of the model of the T-foil’s lift force, the governing equation of the T-foil’s swinging angle is deduced and simplified using the test results of the ship model with a passive T-foil and without a T-foil. Then, the active T-foil control system is established by comparing the effects of T-foils with different control signals. Finally, the efficacies of the passive and active T-foil are reported and discussed. It is found that the pitch angular velocity is a more appropriate signal than the pitch angle and pitch angular acceleration. T-foils with pitch angular velocity control can decrease the vertical motion response in the resonance region of a ship’s encounter frequency by more than about 20% compared to the case of the bare ship model, while also increasing the anti-bow acceleration effect by more than 15% compared to the case of passive control. The results obtained by model testing have a certain guiding significance for specific engineering practices.

Experimental Study on Performance of Impact Damper For Various Mass Ratios

Vibration plays a vital role in many structural elements. Excessive vibration can cause failure due to resonance and fatigue, malfunctioning of critical components, etc. Vibration can be controlled using passive, active and hybrid control systems. This paper presents the experimental studies carried out on the behaviour of impact dampers, which belong to the category of passive vibration control devices that are used to attenuate vibration of discrete and continuous systems. Impact damping is a technique for improving damping of a dynamic system by means of dissipation of energy due to collision of a free mass on the main mass.
 Experimental studies are carried out for forced vibration conditions by giving sinusoidal varying forcing function to the cantilever beam system using an exciter system and the time/frequency response function is determined. Impact mass is placed at free end of cantilever beam and the system is given constant base excitation and the damping of the system is studied by varying the frequency. Experiments are conducted for various mass ratios with different impact mass materials and the results are compared with theoretical predictions.

A Virtual Sensing Active Noise Control System Based on a Functional Link Neural Network for an Aircraft Seat Headrest

PurposeThe goal of this work is to propose a local Active Noise Control system for an aircraft seat’s headrest. This system should be able to extend the quiet zone beyond the physical microphones that can be placed behind the passenger’s head due to space constraints. Furthermore, the control algorithm should perform efficiently when non-linear phenomena exist during the sound propagation.MethodsA functional link neural network and a computationally efficient Multiple Input Multiple Output approach are used for the system’s implementation. The quiet zone is extended by linearly estimating the acoustic pressure in front of the headrest surface. The main novelty of this paper is the combination of these methods in an attempt to improve acoustic pressure attenuation performance, while keeping computational complexity low.ResultsThe proposed control algorithm has been evaluated through numerical simulations, including Finite Element Method and experimental tests at an aircraft cabin mock-up. The results show that for a real-world acoustic disturbance, a 10 dB reduction in sound pressure level was achieved 10 cm away from the headrest surface. In addition, the attenuation of some harmonics can reach 20 dB and in most cases is bigger than the linear FxLMS algorithm.ConclusionsTo summarize, it has been demonstrated that a multichannel functional link neural network using a simple virtual sensing technique can efficiently attenuate synthesized and real world acoustic disturbances captured in a tilt-rotor aircraft’s cabin. Finally, it can create an adequate quiet zone for gentle head movement while maintaining its stability.

A Comprehensive Implementation of Road Surface Classification for Vehicle Driving Assistance: Dataset, Models, and Deployment

The prior monitoring of the road surface conditions provides valuable information to vehicle trajectory planning and active control systems. Road surface perception with vision sensors is an emerging technology that has recently gained much attention. However, there are few reports on an exhaustive technical scheme and application practice for driving assistance. This study first creates a large-scale road surface image dataset containing one million samples with detailed road friction level, material, and unevenness level annotations. A convolutional neural network (CNN) classification model constrained by a combined loss function and adapted optimization strategies is trained on the dataset. Then we propose a decision-level fusion method based on the improved Dempster-Shafer evidence theory to enhance the robustness of the classification algorithm. Finally, the developed models are deployed on the embedded hardware platform. The top-1 accuracy for classifying road surface images reaches 92.05% by the CNN model and 97.50% after fusion. Onboard experiments illustrate the advantage and superiority of the developed technical framework, which has excellent potential in real-vehicle applications for driving assistance.

A Complete Design of Smart Pad That Reduces Snoring

This paper presents integration of active noise control (ANC) systems with a smart pad to reduce the noise made by snoring. One reference microphone, two secondary speakers and two error microphones are used with a feedforward ANC algorithm in the smart pad design. Several smart functions including snore detection, quiet zone localization, and advanced audio integration are proposed. An effective way to satisfy the causality constraint of the feedforward ANC system is presented. The smart pad is independent of the pillow and is not in contact with the user; it is portable and is not a burden to the user during sleep. Several experiments are conducted to confirm the effectiveness of the smart pad when used on a full-size bed.

Control of Quarter-Car Active Suspension System Based on Optimized Fuzzy Linear Quadratic Regulator Control Method

Vehicle suspension systems, which affect driving performance and passenger comfort, are actively researched with the development of technology and the insufficient quality of passive suspension systems. This paper establishes the suspension model of a quarter of the car and active control is realized. The suspension model was created using the Lagrange–Euler method. LQR, fuzzy logic control (FLC), and fuzzy-LQR control algorithms were developed and applied to the suspension system for active control. The purpose of these controllers is to improve car handling and passenger comfort. Undesirable vibrations occur in passive suspension systems. These vibrations should be reduced using the proposed control methods and a robust system should be developed. To enhance the performance of the fuzzy logic control (FLC) and fuzzy-LQR control methods, the optimal values of the coefficients of the points where the feet of the member functions touch are calculated using the particle swarm optimization (PSO) algorithm. Then, the designed controllers were simulated in the computer environment. The success of the control performance of the applied methods concerning the passive suspension system was compared in percentages. The results are presented and evaluated graphically and numerically. Using the integral time-weighted absolute error (ITAE) criterion, the methods were compared with each other and with the studies in the literature. As a result, it was found that the proposed control method (fuzzy-LQR) is about 84.2% more successful in body motion, 90% in car acceleration, 84.5% in suspension deflection, and 86.7% in tire deflection compared to the studies in the literature. All these results show that the car’s ride comfort has been significantly improved.

Aspects of active-passive controls of nanoparticles of chemically reactive and radiative nanofluid flow past a frequently moving thin needle with thermal and velocity slip: A numerical framework

This communication unfolds the flow features and distribution of mass, heat of a steady MHD nanofluidic stream over an axially moved thin needle with passive and active controls of tiny particles. A linear sort of heat radiation with magnetic influence and a higher-order chemical reaction are addressed in this study. The investigation has been enriched by the consideration of thermophoretic forces with the Brownian movement of fluid. The statement of the problem is formed on the basis of Buongiorno’s model, which introduced the existence of thermal & velocity slips. A suitable set of conversions was utilized to transfigure the foremost equations into nondimensional ordinary ones. Due to the extreme nonlinearity of this problem, we avoid the analytical scheme of solution. Hence, we have implemented the RK4 procedure in shooting approach through the algebra software MAPLE 2017, to solve it in a numerical manner. Numerous graphical diagrams and tables are buildups to discuss our attained impacts. Also, it is ensured the validation of these results with the study which was published earlier. Investigation depicts that the order of chemical reaction intensifies fluid density for active control, while the reverse is recorded in the passive strategy. Velocity slip amplifies the drag friction but reduces the transportation of heat. In the active control system, advanced chemical reaction offers more transmission of heat, but the opposite happens in another control.

Development of a Sound Quality Evaluation Model Based on an Optimal Analytic Wavelet Transform and an Artificial Neural Network

The purpose of this study was to develop a sound quality model for real time active sound quality control systems. The model is based on an optimal analytic wavelet transform (OAWT) used along with a back propagation neural network (BPNN) in which the initial weights and thresholds are determined by particle swarm optimisation (PSO). In the model the input signal is decomposed into 24 critical bands to extract a feature matrix, based on energy, mean, and standard deviation indices of the sub signal scalogram obtained by OAWT. The feature matrix is fed into the neural network input to determine the psychoacoustic parameters used for sound quality evaluation. The results of the study show that the present model is in good agreement with psychoacoustic models of sound quality metrics and enables evaluation of the quality of sound at a lower computational cost than the existing models.