In this article, a method for nonlinear control is proposed using an extended state observer for position tracking of an electro-hydraulic system (EHS) with only position feedback. The proposed method consists of a high-gain extended state observer (HGESO) and a nonlinear controller. The EHS model is transformed into the normal form to lump a system function and an external disturbance into a disturbance. The HGESO observer is accordingly designed to estimate the full state and disturbance. The nonlinear controller is then developed using backstepping to suppress the position tracking error using the input-to-state stability property. The key innovation of the proposed method is the design of the nonlinear gain to suppress the position tracking error according to the disturbance estimation error. Thus, the use of the high observer gain to accurately estimate the disturbance can be avoided. The stability of the closed loop including the EHS, controller, and observer is then mathematically demonstrated without the need for an approximation of the “sgn” function in the EHS dynamics. The proposed method is verified using simulated and experimental testing.

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.

Recently, controllers using the barrier Lyapunov function (BLF) are widely used to guarantee the tracking error (or state) constraint. A BLF can be defined only when the error is within a predefined boundary. Thus, overall stability can not be guaranteed when the error exceeds the predefined boundary owing to avoidable reasons such as external disturbance. Additionally, near the boundary, the singularity problem causes the peaking phenomenon in the control input. To overcome this problem, BLF based singularity-free nonlinear position control is designed for PMSMs. A state dependent boundary as a smooth function of the error is proposed to suppress the error when it exceeds the predefined boundary. When the error exceeds the predefined boundary, the proposed boundary increases according to the error. A nonlinear position controller is designed using the BLF and state dependent boundary. The tracking error always be controlled to be kept within the boundary by the position controller. When the tracking error exceeds the predefined boundary, the tracking error can return to the predefined boundary with the finite control input. The singularity problem can be solved by using the proposed boundary which is the smooth function. A disturbance observer is designed to estimate the disturbance. The performance of the proposed method is verified by simulations and experiments.

This paper considers a new positioning sensor using position sensitive detector (PSD) under indoor environments. The system consists of PSD module which is attached on the ceiling and infrared (IR) projector modules attached on the interested object, and all modules are connected by wireless communication. In this system, the PSD module detects and determines location of the IR projector module with its light source, and the IR projector module receives its own location information from the PSD module. In particular, the developed system is implemented on the embedded system and it is small, simple, inexpensive and robust localization system. We applied this system to mobile robot navigation on indoor environment, and the experimental results shows the effectiveness of this system