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In general, it is not easy work to design controllers and observers for high-order nonlinear systems. Planar motors that are applied to semiconductor wafer-stage processes have 14th-order nonlinear dynamics and require high resolution for position tracking. Thus, many sensors are required to achieve enhanced tracking performance because there are many state variables. To handle these problems, we developed a Lyapunov-based controller to improve the position tracking performance. Consequently, a nonlinear observer (NOB) was also developed to estimate all of the state variables including the position, the velocity, and the phase current using only position feedback. The closed-loop stability is proved through Lyapunov theory and the input-to-state stability (ISS) property. The proposed method was evaluated based on the simulation results and compared with the conventional proportional–integral–derivative (PID) control method to show the improvement in the position tracking performance.

This study presents LPV H∞ control with an augmented nonlinear observer (ANOB) to improve both the position and yaw tracking errors for Sawyer motors. The proposed control method consists of the forces and torque modulation scheme, an ANOB, and a Lyapunov-based current controller with the LPV H∞ state feedback controller to guarantee the stability of tracking error dynamics. The ANOB is designed to estimate all the state variables including the position, velocity, current, and disturbance using only position feedback. We propose a vertex expansion technique to solve the influence of the convex interpolation parameters in the LPV system on the tracking error performance. To be robust against disturbance, a state feedback controller with the LPV gain scheduling is determined by applying the H∞ control in the linear-matrix-inequality (LMI) technique. The closed-loop stability is proved through the Lyapunov theory. The effectiveness of the proposed control method is evaluated through simulation results and compared with the conventional proportional-integral-derivative (PID) control method to verify both the improved tracking error performance and a suitable disturbance rejection.

In this paper, position control using both a nonlinear position controller and a current controller with an augmented observer is proposed for a Brushless DC motor. The nonlinear position controller is designed to improve the position tracking performance based on the tracking error dynamics. The current controller is developed to track the desired currents generated from the desired torque, which is calculated based on the nonlinear position controller. The augmented observer is designed to obtain the knowledge of both state variables and disturbance. Closed-loop stability is proven through the Lyapunov theorem. Simulations were performed to evaluate the effectiveness of the proposed method.

This paper proposes a robust tracking control method for swing-up and stabilization of a rotational inverted pendulum system by applying equivalent input disturbance (EID) rejection. The mathematical model of the system was developed by using a Lagrangian equation. Then, the EID, including external disturbances and parameter uncertainties, was defined; and the EID observer was designed to estimate EID using the state observer dynamics and a low-pass filter. For robustness, the linear-quadratic regulator method is used with EID rejection. The closed-loop stability is proven herein using the Lyapunov theory and input-to-state stability. The performance of the proposed method is validated and verified via experimental results.

In the existing literature, studies on position controller design using only position feedback, considering the disturbances for single-rod electro-hydrostatic actuators (EHAs), have not been reported. Herein, we propose a robust nonlinear position control with an extended state observer (ESO) for single-rod EHAs. A new EHA model that consists of position, velocity, and acceleration with an internal state variable is developed. Instead of the separated port pressure dynamics, the acceleration dynamics were defined. The external disturbance, model, and input function uncertainties were lumped into a disturbance. An ESO is developed to estimate the disturbance, as well as the position, velocity, and acceleration. In practice, it is difficult to accurately estimate the disturbance because it includes the external disturbance, system dynamics, and input function uncertainty. The poor estimation performance may degrade the position tracking performance, but a high gain cannot be used to suppress the estimation error because of the measurement noise amplification. To resolve this problem, a robust nonlinear position controller is developed via a backstepping procedure. In the controller, a nonlinear gain is implemented to sufficiently suppress position tracking without the use of a high gain. The stability of the closed-loop system is mathematically proven using the input-to-state stability. The proposed method is simple and suitable for real-time control.

In this paper, a nonlinear differential braking control method is developed to avoid collision during lane change under driver torque. The lateral dynamics consist of lateral offset error and yaw error dynamics and can be interpreted as a semi-strict feedback form. In the differential braking control problem under the driver torque, a matching condition does not satisfy, and the system is not in the form of, the strict feedback form. Thus, a general backstepping control method cannot be applied. To overcome this problem, the proposed method is designed via the combination of the sliding mode control and backstepping. Two sliding surfaces are designed for differential braking control. One of the surfaces is designed considering the lateral offset error, and the other sliding surface is designed using the combination of the yaw and yaw rate errors as the virtual input of the lateral offset error dynamics. A brake steer force input is developed to regulate the two sliding surfaces using a backstepping procedure under the driver torque. Integral action and a super twisting algorithm are used in the lateral controller to ensure the robustness of the system. The proposed method, which is designed via the combination of the sliding mode control and backstepping, can improve the lateral control performance using differential braking. The proposed method is validated through simulations.

We propose a nonlinear position control using a differential flatness concept with a load torque observer to compensate for the sinusoidal load torque in electro-hydraulic actuators (EHAs) EHAs. In an EHA with a rotational joint, the load torque is a sinusoidal disturbance, whose magnitude can be estimated via a load torque observer. In the proposed load torque observer, the load torque can be estimated without requiring its maximum frequency to be known. The position controller tracks position and comprises an inner-loop load pressure controller and an outer-loop position controller. The former tracks the desired pressure via near input–output linearization. The desired pressure is developed using the differential flatness of the mechanical system in the EHA. The feedback plus feedforward outer-loop position controller is designed to track the desired position and to compensate for the load torque. The stability of the closed-loop system is mathematically proven using the input-to-state stability property.

In this paper, a stability-driven optimal disturbance observer (DO) is proposed. The proposed method does not require any plant inverse dynamics to detect introduced disturbances or a stabilizing Q filter. It does not require additional compensators to resolve causality problems, due to the relative degree, or filters to solve instability problems of non-minimum phase plants. Using this method enables wideband and narrowband disturbances to be attenuated by simply multiplying the corresponding peak filters by the baseline weight function. Furthermore, the proposed DO guarantees the stability of closed-loop systems because the already designed outer-loop systems are considered as a target plant to be stabilized and because of the Lyapunov stability-based H∞ control. In the application example, it was confirmed that the proposed method is effective, and the position error signals were improved by 20.9% in commercial hard disk drives and 36.6% in optical image stabilization systems.

We consider the indefinite, linear-quadratic, mean-field-type stochastic zero-sum differential game for jump-diffusion models (I-LQ-MF-SZSDG-JD). Specifically, there are two players in the I-LQ-MF-SZSDG-JD, where Player 1 minimizes the objective functional, while Player 2 maximizes the same objective functional. In the I-LQ-MF-SZSDG-JD, the jump-diffusion-type state dynamics controlled by the two players and the objective functional include the mean-field variables, i.e., the expected values of state and control variables, and the parameters of the objective functional do not need to be (positive) definite matrices. These general settings of the I-LQ-MF-SZSDG-JD make the problem challenging, compared with the existing literature. By considering the interaction between two players and using the completion of the squares approach, we obtain the explicit feedback Nash equilibrium, which is linear in state and its expected value, and expressed as the coupled integro-Riccati differential equations (CIRDEs). Note that the interaction between the players is analyzed via a class of nonanticipative strategies and the “ordered interchangeability” property of multiple Nash equilibria in zero-sum games. We obtain explicit conditions to obtain the Nash equilibrium in terms of the CIRDEs. We also discuss the different solvability conditions of the CIRDEs, which lead to characterization of the Nash equilibrium for the I-LQ-MF-SZSDG-JD. Finally, our results are applied to the mean-field-type stochastic mean-variance differential game, for which the explicit Nash equilibrium is obtained and the simulation results are provided.

In existing methods, full-state feedback is required for the position tracking of single-rod Electro Hydrostatic Actuators (EHAs). Measuring a full state is not always possible because of cost and space limitations. Furthermore, measurement noise from pressure sensors may degrade the control performance. We propose an observer-based nonlinear position control with nonlinear coordinate transformation while only using position measurement to improve the position tracking of single-rod EHAs. The proposed method comprises a position controller and an observer. We propose a nonlinear coordinate transform for the controller design. The desired force is designed for the position tracking and boundedness of the internal state. The position controller is designed to track the desired state variables for the EHAs. Meanwhile, a nonlinear observer is proposed in order to estimate a full state using only the position measurement. The stability of the closed-loop system is investigated via an input-to-state stability property. The performance of the proposed method is validated via both simulations and experiments.

In this paper, we propose a nonlinear position control using only position feedback to guarantee the tolerances for position tracking errors and yaw. In the proposed method, both mechanical and electrical dynamics are considered. The proposed method consists of the nonlinear position controller and nonlinear observer. The nonlinear position controller is designed by a backstepping procedure using the barrier Lyapunov function to satisfy the constraints of position error and yaw. The nonlinear observer is developed to estimate full state using only position feedback. The stability of the closed-loop system is proven using Lyapunov and input-to-state stabilities. Consequently, the proposed method satisfies the constraints of position error and yaw using only position feedback for the planar motor.

For several decades, disturbance observers (DOs) have been widely utilized to enhance tracking performance by reducing external disturbances in different industrial applications. However, although a DO is a verified control structure, a conventional DO does not guarantee stability. This paper proposes a stability-guaranteed design method, while maintaining the DO structure. The proposed design method uses a linear matrix inequality (LMI)-based H∞ control because the LMI-based control guarantees the stability of closed loop systems. However, applying the DO design to the LMI framework is not trivial because there are two control targets, whereas the standard LMI stabilizes a single control target. In this study, the problem is first resolved by building a single fictitious model because the two models are serial and can be considered as a single model from the Q-filter point of view. Using the proposed design framework, all-stabilizing Q filters are calculated. In addition, for the stability and robustness of the DO, two metrics are proposed to quantify the stability and robustness and combined into a single unified index to satisfy both metrics. Based on an application example, it is verified that the proposed method is effective, with a performance improvement of 10.8%.