Robust Linear Quadratic Regulator Controller Research Articles

Optimal robust control approaches for a geostationary satellite attitude control

In this paper, two-optimal robust fuzzy proportional-integralderivative (FPID) and linear-quadratic regulator (LQR) controllers have been implemented for attitude control of a geostationary satellite, utilising momentum wheels. In the designed FPID controller, two fuzzy inference engines have been used, from which the second engine, is accounted to control the satellite attitude in severe deviations and preventing the system from instability. The designed FPID controller is optimised using the multi-objective genetic algorithm (MOGA) based on desired objective functions, which are deviation error from equilibrium states and control efforts. The optimal FPID controller is designed in such a way that while making extremum the desired objective functions, it also provides an appropriate controlling performance. Throughout designing robust LQR controller, design matrices of R and Q are selected in such a way to form a balance between the made control efforts and the settling time of the system.

GA-based robust LQR controller for interleaved boost DC–DC converter improving fuel cell voltage regulation

Proton Exchange Membrane Fuel Cell (PEMFC) is one of the most promising technologies for sustainable energy production due to the high power density, low operative temperature and more convenient use for several applications. Nevertheless, the high generated current that characterizes PEMFC requires a specific power conditioning. In addition, specific controller must be designed to fit with system operative points changing associated with the variation of this high current. To deal with this challenge, in this paper, an electrochemical system composed of a Proton Exchange Membrane Fuel Cell (PEMFC) feeding via two phases IBC has been proposed and investigated. For robustness, the used IBC for fuel cell voltage regulation is controlled by linear quadratic regulator (LQR). Then, genetic algorithms technique is applied to optimize the LQR controller parameters giving optimal control coefficients and can if necessary be adjusted according to each working situation change. The model of the entire system is studied using Matlab/Simulink environment. The simulation’s comparative standard and robustness results both demonstrate that the proposed GA-based LQR controller outperforms the conventional PI in terms of performance metrics (overshoot reduction: between 58.93% and 97.09%; response time reduction: between 56.40% and 77.00% and ripple reduction: between 84.00% and 94.86%).

Robust LQR control for stall flutter suppression: A polytopic approach

In this paper, a robust Linear Quadratic Regulator (LQR) of a NACA 0018 wing with a flap actuator is developed for stall flutter suppression. The nonlinear and switched set of equations of the aeroelastic model is detailed and conveniently expressed as a polytopic uncertain system. A Linear Matrix Inequalities (LMIs) formulation of the LQR problem in the presence of uncertainties is used for the control design. Simulation results confirm the desirable behavior of the arising closed-loop system.

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.

Output Constraint Control on Path Following of Four-Wheel Independently Actuated Autonomous Ground Vehicles

The path-following problem for four-wheel independently actuated autonomous ground vehicles is investigated in this paper. A novel output constraint controller is proposed to deal with the lateral offset control in path following and maintain the vehicle lateral stability in the presence of tire sliding effects. The innovations of this work lie in the following two aspects: 1) A novel output constraint control strategy, namely, the hyperbolic projection method, is proposed to strictly bound the lateral offset to prevent the vehicle from transgressing the safety bound in path following; 2) an adaptive and robust linear quadratic regulator controller is adopted to obtain the optimal active front-wheel steering and direct yaw-moment control inputs with vehicle lateral stability consideration and to eliminate the effect of parameter uncertainties. CarSim–Simulink joint simulation results indicate that the proposed controller can compactly bound the lateral offset to avoid transgressing the safe boundary during path following, particularly in extreme driving conditions, in the presence of tire sliding effects and system uncertainties.

Active front-steering control of a sport utility vehicle using a robust linear quadratic regulator method, with emphasis on the roll dynamics

One of the well-known methods for improving the lateral stability of a vehicle is to utilize an active steering controller. Common active steering systems use feedback signals from a yaw rate sensor and side-slip angle estimation. However, in some driving conditions, skilled drivers can prevent vehicle rollover using the steering angle of the vehicle. Hence, the effect of an active front-steering controller on the roll angle of the vehicle is studied in this paper. For this study, a three-degree-of-freedom linear model of a vehicle which has the lateral motion, the yaw motion and the roll motion as the degrees of freedom is derived. The effectiveness of the active steering controller on the roll stability of the vehicle is examined by simulations in a wide range of longitudinal velocities of the vehicle using a linear quadratic regulator controller. The results obtained indicate that the active steering controller increases the roll stability of the vehicle only at low vehicle speeds and also that consideration of the roll degree of freedom in the design of the active steering controller is not effective at high vehicle speeds. Therefore a two-degree-of-freedom bicycle model is sufficient for active steering controller design. Another part of this paper is dedicated to designing a practical active steering controller for a vehicle with time-varying and uncertain parameters. In fact, designing a controller which guarantees the stability of the vehicle with simultaneous uncertainties in the cornering stiffnesses of the tyres and in the time-varying velocity is the main goal of this paper. Another important advantage of the proposed controller is its simplicity and static structure. In fact, this controller design is carried out offline and can be implemented for use in a real vehicle. This simple and powerful controller is a robust linear quadratic regulator controller. For designing a robust linear quadratic regulator controller, a polytopic model of the two-degree-of-freedom vehicle is obtained, which considers the uncertainty in the parameters. In addition, a linear matrix inequality is used to design a linear quadratic regulator controller for an uncertain or parameter-varying system. Finally, the performance of the designed robust linear quadratic regulator controller was studied by simulating the vehicle responses in some manoeuvres. A sport utility vehicle model is used for simulation purposes. This non-linear vehicle model has eight degrees of freedom and its tyres are assumed to be both linear and non-linear. The performance of the robust linear quadratic regulator controller was studied for vehicles with both linear and non-linear Pacejka tyres. The proposed controller guarantees robust stability of the closed-loop system in the presence of 50% variation in the vehicle speed and 20% uncertainty in the stiffnesses of the tyres.