Mert Sever

Observer Based Optimal Vibration Control of a Full Aircraft System Having Active Landing Gears and Biodynamic Pilot Model

This paper deals with the design of an observed based optimal state feedback controller having pole location constraints for an active vibration mitigation problem of an aircraft system. An eleven-degree-of-freedom detailed full aircraft mathematical model having active landing gears and a seated pilot body is developed to control and analyze aircraft vibrations caused by runway excitation, when the aircraft is taxiing. Ground induced vibration can contribute to the reduction of pilot’s capability to control the aircraft and cause the safety problem before take-off and after landing. Since the state variables of the pilot body are not available for measurement in practice, an observed based optimal controller is designed via Linear Matrix Inequalities (LMIs) approach. In addition, classical LQR controller is designed to investigate effectiveness of the proposed controller. The system is then simulated against the bump and random runway excitation. The simulation results demonstrate that the proposed controller provides significant improvements in reducing vibration amplitudes of aircraft fuselage and pilot’s head and maintains the safety requirements in terms of suspension stroke and tire deflection.

L2 gain state derivative feedback control of uncertain vehicle suspension systems

This paper is concerned with the design of a robust L2 gain state derivative feedback controller for an active suspension system. An uncertain quarter vehicle model is used to analyze vehicle suspension performance. Parametric uncertainty is assumed to exist in sprung mass, tire stiffness and suspension damping coefficients. Polytopic type state space representation is used to enable robust controller design via a linear matrix inequalities (LMIs) framework. Then nominal and robust L2 gain state derivative feedback controllers having bounded controller gains and robust L2 gain state feedback controllers are tested against ISO2631 random road disturbances with different road grades and vehicle horizontal velocities. Simulation results show that the proposed robust L2 gain state derivative feedback controller is very effective in improving ride comfort without deterioration on road holding ability.

Active Trailer Braking system design with Linear Matrix Inequalities based multi-objective robust LQR controller for vehicle-trailer systems

An Active Trailer Braking system is designed for the mitigation of trailer sway. Motion of the vehicle-trailer system on the horizontal plane with three degrees of freedom is modeled. Variations on the dynamic behaviors are studied due to the changes in longitudinal velocity. Then, performance objectives of controller is specified in terms of robust stability and lower bound of damping ratio for a prescribed longitudinal velocity range. Linear Matrix Inequalities based robust multi-objective LQR controller is designed with constraints on closed-loop pole locations and guarantee of robust stability. Finally, superiority of the designed controller is shown by using some numerical comparison with a classical Algebraic Riccati Equation based LQR design reported in the literature.

Disturbance attenuation of asymmetric structure by LMI based optimal state feedback controller with saturated actuators

This paper is concerned with the design of linear matrix inequalities (LMIs) based optimal state-feedback controller design for seismically excited asymmetric structures (AS) having stiffness irregularities. The system is modelled in terms of mass, natural frequencies, damping ratio and eccentricities to easily obtain torsionally flexible (TF) model. A one storey, two-way asymmetric structural system is used to illustrate the effectiveness of the approach through simulations. The modelled system has bi-lateral and rotational degrees of freedom. Frequency responses show the effectiveness of proposed controller by means of a decrease in the peak values of translation at each resonance frequency. Moreover, the time domain simulation results, acquired by using real time-history data of San Francisco and El Centro Earthquakes also show that proposed controller is very effective in reducing vibration amplitudes of each direction by applicable control signals and guaranteeing the stability of the closed loop system.

Vehicle stability enhancement and rollover prevention by a nonlinear predictive control method

In this study, a nonlinear predictive control method is developed for the active steering control of a sport utility vehicle. The method is tested on a nonlinear mathematical model of an 11-degree-of-freedom vehicle. The system performance is evaluated by considering that the control law must keep the actual yaw rate close to the desired yaw rate and minimizing the vertical load changes at each wheel. The latter is proposed for this work. The vertical load changes play an important role in the dynamics and the stability of the system. The effectiveness of the control method is demonstrated through numerical simulation by using a vehicle model that includes three case studies: rapid lane change at low and high velocities and the fishhook manoeuvre. The results show that the stability of the vehicle is maintained and its rollover propensity is decreased. In addition, the proposed controller is compared with a well-known linear model predictive controller.

LMI-based design of an I-PD+PD type LPV state feedback controller for a gantry crane

In this paper, an alternative gain-scheduled PID tuning procedure is proposed for gantry crane control systems. In order to avoid excessive overshoot and aggressive control action due to the proportional kick and/or derivative kick effects, an I-PD+PD type control law is considered. The scheduling parameter is considered the cable length due to the payload lifting and lowering movements. A linear parameter-varying (LPV) gantry crane model is constructed to enable gain-scheduled controller design with a linear matrix inequalities (LMIs) framework. Based on the LPV model, a convex optimization problem is formulized to minimize L2 gain under regional pole location constraints. Then, a fixed gain L2 gain state feedback I-PD+PD type controller and a conventional pole placement state feedback I-PD+PD controller are designed to investigate the efficiency of the proposed controller. A pole placement controller is tuned to minimize the very common ITAE (integral of time multiplied by absolute error) performance index. Simulation results show that the proposed controller has superior tracking performance under time-varying cable length, when compared with nominal fixed gain controllers.

Active control of a non-linear landing gear system having oleo pneumatic shock absorber using robust linear quadratic regulator approach

This paper deals with the active control of a non-linear active landing gear system equipped with oleo pneumatic shock absorber. Runway induced vibration can cause reduction of pilot’s capability of control the aircraft and results the safety problem before take-off and after landing. Moreover, passenger–crew comfort is adversely affected by vertical vibrations of the fuselage. The active landing gears equipped with oleo pneumatic shock absorber are highly non-linear systems. In this study, uncertain polytopic state space representation is developed by modelling the pneumatic shock absorber dynamics as a mechanical system with non-linear stiffness and damping properties. Then, linear matrix inequalities-based robust linear quadratic regulator controller having pole location constraints is designed, since the classical linear quadratic regulator control design is dealing with linearized state space models without considering the non-linearities and uncertainties. Thereafter, numerical simulation studies are carried out to analyse aircraft response during taxiing. Bump- and random-type runway irregularities are used with various runway class and wide range of longitudinal speed. Simulation results revealed that neglecting the non-linear dynamics associated with oleo pneumatic shock absorber results significant performance degradation. Consequently, it is demonstrated that proposed robust linear quadratic regulator controller has a superior performance in terms of passenger–crew comfort and operational safety when compared to classical linear quadratic regulator.

Observer-based H2 controller design for a vibration isolation stage having hybrid electromagnets

Vibration isolation systems based on hybrid electromagnets, consisting of electromagnet and permanent magnet, have a potential usage in many industrial areas, such as clean room design, transportation, semiconductor manufacturing, suspension systems, and robotic surgery due to providing mechanical contact free vibration isolation. Using permanent magnets in the electromagnet structure has some crucial advantages, such as a minimized volume and a more compact structure. Furthermore, the essential force for levitation of vibration isolation stage can be generated by only the permanent magnet(s), which means, by using hybrid electromagnets, magnetic levitation can be achieved with considerably low energy consumption against possible vibrations. This property is called zero-power behavior. However, the main problems of magnetic levitation process are as follows: it has highly nonlinear nature even if it can be linearized; it has unstable pole(s), which makes the system vulnerable in terms of stability. In recent years, linear matrix inequality-based design of controllers has received considerable attention and become very popular due to their ability to satisfy multiobjective design requirements. However, an observer-based H2 controller design for a vibration isolation system having hybrid electromagnets has not been considered yet. Therefore, the linear matrix inequality-based controller is employed to minimize the effect of disturbances on the following objectives, such as vibration isolation, zero-power property, and protection of the levitation gap. The effectiveness of the proposed method is shown with the numerical simulation studies and compared with classical Linear Quadratic Regulator (LQR) approach.

Output derivative feedback vibration control of an integrated vehicle suspension system

In this article, we present a novel approach to design an L2 gain output derivative feedback controller for active vibration control of a vehicle suspension system. In vibration control problems, state derivative signals such as acceleration and velocity are easier to obtain rather than the state variables such as position and velocity, since the accelerometers are simpler, cheaper and more reliable than position sensors. First, an L2 gain output derivative feedback controller is proposed by taking into account that measuring state derivative signals belong to driver body and electro-hydraulic actuator is not applicable in practice. Then, an L2 gain state derivative feedback controller and an L2 gain static output feedback controller are designed to investigate efficacy of the proposed controller. Performance of the controllers is tested against bump- and random-type road irregularities. A 4-degree-of-freedom integrated vehicle suspension model that includes a quarter vehicle suspension, a seat suspension, a driver body and an electro-hydraulic actuator is used throughout the numerical simulation studies. Simulation results show that proposed L2 gain output derivative feedback controller provides compatible performance improvement in the state derivative feedback control and static output feedback control with more viable feedback strategy.

Gradient descent based classification of road induced disturbances for active suspension systems

Active suspensions are designed to meet conflicting performance requirements such as ride comfort and safety. Achievable ride comfort performance without reaching the limits of road holding and suspension bottoming, is limited by the road disturbance roughness level. In order to obtain best ride comfort performance against different road induced disturbances, it is essential to switch among different controllers according to road roughness level. In this study, a classification algorithm based on logistic regression trained by gradient descent was presented to switch the controller with respect to road disturbance values. The classification algorithm with logistic regression model is trained by the road disturbance data provided by standards. A disturbance observer to estimate the road induced disturbance is designed, then a sigmoid activation function was proposed to change the controller by using only the road disturbance data. The suggested algorithm was tested on the road induced disturbance produced by observer. It was proved that the algorithm without complexity classified the road induced disturbance with the one hyperplane reducing the overfitting condition in training process. As a result, the proposed algorithm can be efficiently used to detect the controller switching instants in real time application.