This paper presents a method by which to design linear quadratic (LQ) static output feedback (SOF) controllers with a 2-DOF quarter-car model for an active suspension system. Generally, it is challenging to implement linear quadratic regulator (LQR), designed with a full-car model, in actual vehicles because doing so requires 14 state variables to be precisely measured. For this reason, LQR has been designed with a quarter-car model and then applied to a full-car model. Although this requires far fewer state variables, some of them are still difficult to measure. Thus, it is necessary to design a LQ SOF controller which uses available sensor signals that are relatively easily measured in real vehicles. In this paper, a LQ SOF controller is designed with a quarter-car model and applied to a full-car model for ride comfort. To design the controller, an optimization problem is formulated and solved by a heuristic optimization method. A frequency domain analysis and a simulation with a simulation package show that the proposed LQ SOF controllers effectively improve the ride comfort with an active suspension system.

This paper presents a method to design a virtual reference feedforward controller (VRFC) for an active suspension system. Generally, it is not easy to apply a feedforward control to an active suspension system because a reference or disturbance is difficult to measure or estimate. Instead of measuring references or disturbances, a virtual reference on heave motion of a sprung mass representing a bump is defined and used for feedforward control in this paper. Feedforward controller with the virtual reference is combined with feedback controllers such as linear quadratic regulator (LQR) and linear quadratic (LQ) static output feedback (SOF) controller. To fully take advantages of the virtual reference for an active suspension system, it is necessary to find optimal parameters of the virtual reference which maximizes control performance. For the purpose, a simulation-based optimization is formulated and solved by a heuristic optimization method. A simulation with a simulation package shows that the proposed VRFC is quite effective in improving the ride comfort with an active suspension system.

In-wheel motor vehicles are gaining attention as a new type of electric vehicle due to their efficient power units located inside each wheel hub. However, they are more susceptible to wheel resonance due to the increase in unsprung mass caused by the weight of the motor. This can result in both decreased ride comfort and driving stability. To resolve this issue, in this study, we aim to apply an optimal switching controller with a semi-active actuator—a magnetorheological (MR) damper. For the implementation of the optimal switching controller, road type classification is also carried out. An acceleration sensor is used for the road type classification, and the control logics include a ride comfort controller (the linear quadratic regulator (LQR_Paved Road)) and a wheel motion controller (LQR_Off Road) for improved driving stability. For paved roads, the LQR_Paved Road control input is applied to the MR damper. However, if a road type prone to wheel resonance is detected, the control logic switches to the LQR_Off Road. During the transition, a weighted average of both the LQR_Paved Road and LQR_Off Road control input is applied to the actuator. Computer simulations are performed to evaluate the vibration control performance, including the ride comfort and driving stability on various road profiles.

This paper presents coordinated compensation schemes between active and semi-active actuators in suspension control system. Generally in active suspension systems, active actuators have been adopted to generate a control force calculated by a controller. However, active actuators adopted in actual vehicles have physical constraints such as maximum force, bandwidth and force-velocity limitation. On the other hand, a semi-active actuator can be a good alternative to active one in view of maximum force and bandwidth despite it cannot generate an active control force. However, the performance of semi-active actuators is limited by half of active ones. Hence, it is necessary to compensate the control force of semi-active actuators by active ones. In this paper, it is assumed that a vehicle has both of active and semi-active actuators. A control force needed to enhance ride comfort is generated by linear quadratic regulator (LQR). The controller is designed with 2-DOF quarter-car model and applied into 7-DOF full-car one. To generate the control force with active and semi-active actuators, several coordinated compensation schemes are proposed. A simulation on a simulation package show that the proposed coordinated compensation schemes are effective in reducing the control force of the active actuator over the wider range of frequencies.

In-wheel motor vehicles are gaining attention as a new type of electric vehicle due to their efficient power units located inside each wheel hub. However, they are more susceptible to wheel resonance due to the increase in unsprung mass caused by the motor's weight. This can result in decreased both the ride comfort and driving stability. To resolve this issue, this study aims to apply an optimal switching controller with a semi-active n actuator; magnetorheological (MR) damper. For the implementation of the optimal switching controller, a road type classification is also carried out. An acceleration sensor is used for road type classification, and control logics include a ride comfort controller; the linear quadratic regulator (LQR _Paved Road) and a wheel motion controller (LQR_Off Road) for improved driving stability. For paved roads, the LQR_Paved Road control input is applied to the MR damper. However, if a road type prone to wheel resonance is detected, the control logic switches to the LQR_Off Road. During the transition, a weighted average of both LQR_ Paved Road and LQR_Off Road control input is applied to the actuator. Computer simulations are undertaken to evaluate vibration control performance, including the ride comfort and driving stability at various road profiles.