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.

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.

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.

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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.

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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 takeoff 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.

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