We propose a high-gain disturbance observer (HGDOB)-based backstepping control with position tracking error constraint for electro-hydraulic systems to improve the position tracking performance in the presence of disturbances. The HGDOB is designed to estimate the disturbances that include the friction, the load force, and the parameter uncertainties. Auxiliary state variables are proposed to avoid amplification of the measurement noise in the HGDOB. To compensate for the disturbances while guaranteeing tolerance of the position tracking error, the backstepping controller is proposed by using the barrier Lyapunov function. As a result, the proposed method satisfies the output constraint and improves the position tracking performance in the presence of disturbances. Its performance is validated via simulations and experiments.

A nonlinear position tracking controller with a disturbance observer (DOB) is proposed to track the desired position in the presence of the disturbance for electrohydraulic actuators (EHAs). The DOB is designed in the form of a second-order high-pass filter in order to estimate the disturbance. The nonlinear controller is designed for position tracking as a near input-output linearizing inner-loop load pressure controller and a backstepping outer-loop position controller. Variable structure control is implemented in order to compensate for the error in disturbance estimation. The desired load pressure is designed to generate the pressure using the differential flatness property of the EHA's mechanical subsystem. The disturbance within the bandwidth of the DOB can be cancelled by the proposed method. The performance of the proposed method is validated via simulations and experiments.

In this paper, we propose a new approach for a robust multirate lane-keeping control scheme with predictive virtual lanes. First, the multirate lane-keeping control scheme is proposed to improve the lane-keeping performance and to reduce the ripple in the yaw rate. To improve the lane-keeping performance on a curved road, the integral of the lateral offset error is added to the state feedback controller. A multirate Kalman filter (KF) has been developed to resolve the problems caused by slow lane detection due to the vision processing system. This multirate KF estimates vehicle states at a fast rate using a microprocessor. Utilizing the estimated states, the linear quadratic state feedback control operates at the same fast update rate of the microprocessor. Thus, a multirate control scheme can reduce the ripple in the yaw rate. Second, we propose a virtual lane prediction method that compensates for the momentary failure of lane detection from unexpected problems. If the camera sensor momentarily fails while obtaining lane information, the predicted virtual lane can be substituted for the lane detection using the camera sensor in the proposed control scheme. Thus, the proposed control scheme can normally operate when the lane information is momentarily unavailable. The performance of the proposed method was evaluated via experiments.

In DC microgrids, constant power loads (CPLs) reduce the effective damping of the DC-DC converter and may induce destabilizing effects into the DC-DC converter. To overcome such problems regarding CPL and ensure large-signal stability of DC-DC converters in DC microgrids, some feedforward terms are added to $V$ - $I$ droop-based dual-loop controller for a DC-DC converter based on the large-signal model. It is proven that the feedforward terms can not only improve the transient response but also guarantee the exponential stability of the closed-loop system in the whole operating range in regards to a large-signal manner, which is verified by using a singular perturbation model. Moreover, a disturbance observer is designed to estimate the output current, thereby enabling the removal of the current measurement sensor. The proposed technique can be easily plugged into a pre-defined $V$ - $I$ droop-based dual-loop controller without an additional sensor being required. Ultimately, both simulation and experimental tests verify the effectiveness of the proposed method.

Although previous control methods improve control performance in electrohydraulic servo system (EHSS), they require full-state feedback information and/or the derivative of the measured signals so that noise may be amplified. In this paper, we propose a high-gain-observer-based integral sliding mode control to improve the position tracking performance of the EHSSs while solving the previous problems. The proposed method consists of a high-gain observer and an integral sliding mode controller. The high-gain observer is designed to estimate the velocity and load pressure using the position feedback. The stability is proven without the approximation of the model in EHSS. The integral sliding mode controller is proposed to improve the position tracking performance using the flatness property of the system. In the controller, the required derivatives of the state variables are obtained using the flatness property without employing the derivative of the measured signal.