Kalman state estimator for aircraft structural load alleviation using eigenpair assignment

Rotational Motion Control by Feedback with Minimum L1-Norm

Abstract. This paper studies a closed-loop wind farm control framework for active power control (APC) with a simultaneous reduction of wake-induced structural loads within a fully developed wind farm flow interacting with the atmospheric boundary layer. The main focus is on a classical feedback control, which features a simple control architecture and a practical measurement system that are realizable for real-time control of large wind farms. We demonstrate that the wake-induced structural loading of the downstream turbines can be alleviated, while the wind farm power production follows a reference signal. A closed-loop APC is designed first to improve the power-tracking performance against wake-induced power losses of the downwind turbines. Then, the nonunique solution of APC for the wind farm is exploited for aggregated structural load alleviation. The axial induction factors of the individual wind turbines are considered control inputs to limit the power production of the wind farm or to switch to greedy control when the demand exceeds the power available in the wind. Furthermore, the APC solution domain is enlarged by an adjustment of the power set-points according to the locally available power at the waked wind turbines. Therefore, the controllability of the wind turbines is improved for rejecting the intensified load fluctuations inside the wake. A large-eddy simulation model is employed for resolving the turbulent flow, the wake structures, and its interaction with the atmospheric boundary layer. The applicability and key features of the controller are discussed with a wind farm example consisting of 3×4 turbines with different wake interactions for each row. The performance of the proposed APC is evaluated using the accuracy of the wind farm power tracking and the wake-induced damage equivalent fatigue loads of the towers of the individual wind turbines.

Fluid-structure coupled simulations are performed for symmetrical quasi-steady pitching maneuvers of a large transport aircraft with a load alleviation system consisting of trailing edge flaps and droop noses at the leading edge. For the fluid part of the simulation, a RANS approach is used, whereas the structural simulation is based on a linear modal model. The selected maneuvers are located on the lift boundary of the maneuver envelope at maximum load factor, as not only are the structural loads high here, but also redistributing lift for load alleviation is especially challenging as the wing is close to stall. For a target value of 33% reduction in wing bending loads, which is derived from the CS-25, the effects of applying load alleviation on wing loads, deformations and aircraft maneuverability are investigated. It is found that the desired reduction of wing bending loads can be achieved for all maneuvers considered, while controlling the torsional moment turns out to be more difficult, especially on the outer wing. A loss of maneuverability due to load alleviation is observed for only one of the maneuvers, while for the other maneuvers the maneuverability could even be increased. In order to assess the influence of the elasticity of the wing, additional simulations of the rigid wing without fluid-structure coupling are carried out and compared with the elastic results. It is found that elasticity has a significant effect on load alleviation, justifying the complex fluid-structure coupled modeling. Finally, also other potential applications of the considered flap system are explored. Here, it is found that the flap system could also be used to extend the flight envelope to higher Mach numbers or higher altitudes, or to achieve a reduction in cruise drag of up to 1.8% by adjusting the spanwise lift distribution.

Realisation of a digital control system, which implements a complete state feedback control strategy for the voltage-source inverter-fed induction motor (IM) drive, is reported. The controller design is based on the application of the linear quadratic regulator (LQR) theory to a linearised state-space model for the machine in the synchronous frame. The control objective is to achieve rotor speed control and orientation of the stator flux vector at constant magnitude by adjusting the stator voltage and frequency. To overcome the detrimental effects of inevitable modelling errors and disturbances, the structure of the feedback controller used here resembles that of the classical proportional-integral controller but is more versatile. The control system design considers the inverter's output limits and proposes an anti-windup scheme to avoid instability risk under integral windup. A supplementary feedforward control loop is provided to enhance transient response of the controlled drive by utilising few future values of the speed reference and load torque signals in advance. The hardware implementation of a controller is discussed and experimental tests are presented, along with computer simulation results, to verify the validity of the method.

The design of a linear, reduced-order, continuous or discrete-time feedforward controller (FFC) is presented. The FFC is located in the reference value branch of a linear feedback system of any order which is designed according to the damping optimum. The aim of the FFC is to decrease the control system reference response time, while retaining a low overshoot and a well-damped form of the reference step response. This is achieved by locating the FFC zeros with the aid of the extended magnitude optimum, which is provided in the continuous or discrete-time variant. The influence of a suboptimally designed feedback system with a reduced-order feedback controller on feedforward control is analyzed. Reduced and full-order FFCs are compared.

The book is examined in the context of its suitability for a first engineering course in feedback control. The text covers several topics normally included in the most current introductory feedback control texts, including: transfer functions and state-space descriptions; Routh-Hurwitz and Nyquist stability criteria; and state-feedback and linear-quadratic regulator theory. It also includes more contemporary topics, such as: robust stability and performance for unstructured perturbations; strong stabilization and Youla parameterization; generalized plants and H/sub/spl infin// design; and H/sub/spl infin// optimization by model matching and interpolation theory. Short appendices are included on normed linear spaces, matrix and abstract algebra, and state-space system manipulations. The material is well presented, with careful proofs of key results. Each chapter includes numerical examples, together with a good list of homework exercises. Some Matlab functions for computing numerical solution are mentioned, but the discussion of software is limited. Unfortunately, the mathematical level of the test is too high, at least for most programs in the United States. The book also omits several standard topics associated with engineering course on feedback control, such as modeling of physical systems, root-locus analysis, digital control, and an introduction to nonlinear systems. As it is, the book would make a very good test for a graduate engineering course in linear feedback control. It could also be a valuable reference for graduate engineering students or applied mathematics students interested in research in the control area.

The design of passive energy dissipation devices (EDD) involves the determination of the required capacity of each damper installed at optimal locations. The fluid viscous damper (FVD) as a passive EDD is commonly used as energy sinks for seismic protection of structures. The present investigation is to deal with the earthquake responses of one- way one-storey asymmetric-plan system with the FVDs. By applying the linear quadratic regulator (LQR) control theory, the calculated control gain is converted to the equivalent fluid viscous damping using a minimum norm method (MNM). How the damping ratio, frequency ratio, aspect ratio, stiffness eccentricity of structures, and FVD equivalent damping ratio affect the optimal eccentric positions of the FVDs are investigated. The damping effects of three control strategies for asymmetric structures under El-Centro earthquake are elucidated. Numerical results demonstrate that the proposed is an alternative method of designing the FVDs for seismic protection of asymmetric structures.

The influences of active stiffening (displacement control) and active damping (velocity control) effects introduced by collocated piezoelectric actuators and sensors on vibration control of composite structures are studied in this paper. A nine-node piezoelectric plate finite element is derived using the first order shear deformation theory to model the distributed actuation and sensing numerically. An output feedback control strategy is developed with the linear quadratic regulator theory in modal domain to estimate the optimal gains for different control efforts off line. Further, the developed control procedure is realised experimentally in an active control system. As an illustration, the effects of both displacement and velocity controls are shown on a CFRP beam. A periodic excitation is applied as disturbance and the amplitude response control is achieved by controlling the displacement and velocity of the vibrating system. It is observed that the active stiffening effect through displacement control is more effective for modes that have the amplitude of vibration relatively high. However, the active damping effect introduced by velocity control is efficient in the third mode control, which shows that a small amount of active damping is sufficient to stabilise a mode having comparatively less amplitude of vibration. Influence of active stiffening on the closed loop system frequency is observed to be more than that of active damping effect.

Controller design for improving lateral vehicle dynamic stability

The main objective of wind turbine control is to make wind power production economically more efficient. This objective is often achieved in two distinct regions, i.e., the below rated wind speed and the above rated wind speed regions. In the below rated wind speed region, generator torque control is used primarily to control rotor speed to track the maximum power coefficient in order to maximize energy capture. In the above rated wind speed region, the blade pitch control is used primarily to regulate the rotor speed in order to regulate the aerodynamic power within its design limit [1]. As the wind turbine sizes are increasing and their mechanical components are built lighter, the reduction of the structural loads becomes a very important task of wind turbine control because structural loads can reduce turbine reliability and lifespan and also may cause power fluctuations. In particular, the reduction of blade loads has received special interest. Wind speed variations across the turbine rotor during rotor rotation, which is caused by the large rotor blade size, the wind shear, turbulence and tower shadow effects, cause periodic oscillations in blade structural loads, andthis structural load is especially important in the above rated wind speed region because high structural loads arise from strong winds. Therefore the individual pitch control is sometimes considered since common collective pitch control cannot compensate for the periodic loads on the blades.

Advanced control of large-scale wind turbines: Structural load reduction and lifetime control

This paper proposes a control method that improves the ability of adult-sized humanoid robots to adapt to weightlifting situations. In order to achieve the goal of having humanoid robots automatically balance their motion for weight-lifting situations, feedback control is added to the motion control system. The feedback sensors include a three-axis accelerometer and a three-axis gyroscopic, which would be processed by Kalman filter, as well as eight force sensors providing the zero moment point (ZMP) information on the robot. These feedback signals are used as the input of a Fuzzy Q-learning controller, which adjusts the motions to keep the stabilization of the robot. The Fuzzy Q-learning controller consists of two stages: one is the stage of fitting the output weights of each pose in motion patterns, and the second is training the rule-table of the controller. The experiment shows that the controller allows the adult-sized robot to walk stably in weight-lifting situation. Thus, the developed controller indeed keeps the balance of the robot in different situations, which gives the robot the ability to adapt to various environments in the manner of human beings.

The present study aims at proposing an analytical method for semi-active structural control by using block pulse functions. The performance of the resulting controlled system and the requirements of the control devices are highly dependent on the control algorithm employed. In control problems, it is important to devise an accurate analytical method with less computational expenses. Block pulse functions (BPFs) set proved to be the most fundamental and it enjoyed immense popularity in different applications in the area of numerical analysis in systems science and control. This work focused on the application of BPFs in the control algorithm concerning decrease the computational expenses. Variable orifice dampers (VODs) are one of the common semi-active devices that can be used to control the response of civil Structures during seismic loads. To prove the efficiency of the proposed method, numerical simulations for a 10-story shear building frame equipped with VODs are presented. The controlled response of the frame was compared with results obtained by controlling the frame by the classical clipped-optimal control method based on linear quadratic regulator theory. The simulation results of this investigation indicated the proposed method had an acceptable accuracy with minor computational expenses and it can be advantageous in reducing seismic responses.

Robust linear control, combined with model-reduction methodologies, is investigated for gust rejection on large, very flexible aircraft using trailing-edge control surfaces. Controllers are designed on linearizations of the nonlinear aeroelastic equations, and the closed-loop response of both the linearized and nonlinear system to discrete gust distributions is compared to the open-loop dynamics. Results show that an controller performs well on a relatively large linearized system, with 9% load alleviation in root bending moments for the critical gust length. When applied to the nonlinear model of the same vehicle, the robust controller gives a good performance in response to short gusts, including the critical length, with even better load reductions than the linear case. However, this performance gap decreases as the gust length is increased. It is also shown how standard model-reduction techniques can provide metrics for the selection of a minimum size of the aeroelastic system. Finally, it is shown that both the full and reduced controllers are capable of stabilizing a large-amplitude phugoid mode on the nonlinear model of the vehicle.

Wearable devices have become a critical driving force in areas such as smart health management, sports tracking, smart homes, and remote healthcare, thanks to advancements in signal transmission and feedback control technologies. This paper systematically reviews the key technologies involved in signal acquisition, transmission, and feedback control in wearable devices, focusing on how closed-loop control enhances user experience and health management through real-time monitoring and dynamic adjustment. By utilizing sensor technology, wearable devices can gather various physiological signals and collaborate with smart systems to provide personalized health and environmental adjustment solutions. The paper also discusses the technical challenges related to latency, energy management, and data security in wearable devices. Additionally, it explores the potential of 5G, artificial intelligence, and next-generation communication technologies to improve device performance. The integration of feedback transmission and closed-loop control offers more intelligent and personalized solutions for future applications in health management, sports tracking, and smart living.