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Crosswinds and transverse slopes of the road surface affect the motion of a ground vehicle as disturbances. The objective of this paper is to develop a method for estimating crosswind disturbances and lateral force disturbances caused by transverse slopes of the road surface under the variation of the vehicle speed. Firstly, a dynamical model of a vehicle is described as a Linear Parameter‐Varying (LPV) system in which the value of the coefficient matrices vary with the vehicle velocity. Then, an algorithm to estimate the disturbance is derived based on Moving Horizon Estimation (MHE) and applied to the derived LPV system. Furthermore, a simple control law which counteracts the effects of the disturbances on the lateral velocity and the yaw rate in steady‐state based on the estimates of the disturbances is presented. The effectiveness of the proposed method is demonstrated by a numerical example. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The utilization of a repetitive controller to cancel periodic disturbance or noise in mechanical systems has become increasingly important for industrial applications. In this study, a repetitive control process was developed using a data classification method, with a fuzzy regression approach and basis function, to reduce tracking errors in feedback controllers. First, a system model using the basis function is illustrated to compute the matched basis functions and their associated coefficients. A real case example of improving the focus of an electron beam subjected to periodic fluctuations has been described for verification and error analysis. Next, model algorithms containing pure and fuzzy regression are introduced into a repetitive feedback control system to reduce tracking errors caused by a periodic disturbance. System output data are categorized using fuzzy inference rules as similar data forming a single group are typically more reliable than the entire output data. The fuzzy theorem approach adopts a Gaussian membership function for system output variables owing to uncertainties that arise from modeling errors, environmental noise, etc. It is determined that the repetitive control process based on data classification with a fuzzy regression approach is more effective than using a pure regression approach. Increasing the number of data classifications initially improves accuracy; however, this decreases when the number of data classifications continues to increase. The optimal root-mean-square output tracking error convergence value was determined as 10-14.09 when the system output data was classified into four categories, demonstrating the satisfactory reduction of a periodic disturbance. Similar results were obtained using the pure regression algorithm, where the lowest averaged verification error was 2.71% for the linear basis function model, with data classified into four categories, and this corresponded to an average prediction error of 3.86%.

A robust adaptive controller that consists of a well-known PI controller and a robust frequency estimation in parallel was presented to cancel unknown sinusoidal disturbance in a stable linear time invariant system. The convergence of frequency estimation, the accurate cancellation of disturbance and the asymptotic stability of the overall feedback control system are analyzed by slow integral manifold and averaging method. The key advantages include asymptotically convergent cancellation for disturbance with much low frequency, the asymptotic stability of the whole error feedback system independent to the parameters of the plant and robust applicability in engineering. Simulation results validate the transient convergence performance and the steady-state anti-noise performance as well as the action of parameters of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we develop an adaptive disturbance cancellation tracking control strategy with the asymptotically converging output tracking errors for a class of multi-input and multi-output (MIMO) nonlinear Euler–Lagrange systems with unknown time-varying disturbances under input saturation. The unknown time-varying disturbances are firstly described as the outputs of a multivariate linear unknown exosystem with unavailable regressor and regression parameter. To estimate the unavailable regressor, an observer is constructed, such that the disturbance cancellation is converted to an adaptive control problem. An auxiliary dynamic system (ADS) is employed to mitigate the effect of the input saturation. Then, a robust adaptive tracking control law is proposed incorporating the above and a robustifying term into the adaptive vectorial backstepping design tool. It is proven theoretically that the asymptotic convergence of the output tracking errors of Euler–Lagrange systems is achieved, while the uniform ultimate boundedness of the remaining signals of the resulting closed-loop control system is guaranteed. Simulation and comparison results on a two-link rigid manipulator and a scale model ship are presented to illustrate the effectiveness and the superiority of the proposed control scheme. • The disturbance cancellation is transformed into the adaptive control problem. • The asymptotic convergence of the output tracking errors is achieved. • Both disturbances and input saturation are considered in the control design. [ABSTRACT FROM AUTHOR]

We design adaptive algorithms for both cancellation and estimation of unknown periodic disturbance, by feedback of state--derivatives ( i.e.,} without position information for mechanical systems) for the plants which are modeled as a linear time invariant system. We consider a series of unmatched unknown sinusoidal signals as the disturbance. The first step of the design consists of the parametrization of the disturbance model and the development of observer filters. The result obtained in this step allows us to use adaptive control techniques for the solution of the problem. In order to handle the unmatched condition, a backstepping technique is employed. Since the partial measurement of the virtual inputs is not available, we design a state observer and the estimates of these signals are used in the backstepping design. Finally, the stability of the equilibrium of the adaptive closed loop system with the convergence of states is proven. As a numerical example, a two-degree of freedom system is considered and the effectiveness of the algorithms are shown.

We design adaptive algorithms for both cancellation and estimation of unknown periodic disturbance, by feedback of state-derivatives (i.e., without position information for mechanical systems) for the plants which are modeled as a linear time invariant system. We consider a series of unmatched unknown sinusoidal signals as the disturbance. The first step of the design consists of the parametrization of the disturbance model and the development of observer filters. The result obtained in this step allows us to use adaptive control techniques for the solution of the problem. In order to handle the unmatched condition, a backstepping technique is employed. Since the partial measurement of the virtual inputs is not available, we design a state observer and the estimates of these signals are used in the backstepping design. Finally, the stability of the equilibrium of the adaptive closed loop system with the convergence of states is proven. As a numerical example, a two-degree of freedom system is considered and the effectiveness of the algorithms are shown. [ABSTRACT FROM AUTHOR]

This study develops a rotary-type active vibration control device (Active Wheel Damper, AWD) using a fly-wheel to control vibrations in flexible structures. The AWD achieves lightweight and higher inertia by the fly-wheel, and can be mounted on the flexible structure easily. In addition, the AWD can realize sky-hook controller easily because it can measure the absolute angular velocity of the flexible structure by the gyro sensor. So, the AWD uses Sky-hook With Disturbance Cancellation (SWDC) control, which is combined controller of a sky-hook control and a disturbance cancellation control with very high vibration suppression potential. However, control performance depends on the resolutions of sensors (Analog-Digital converters) and controller outputs (Digital-Analog converters), and higher cost is necessary for using the higher resolution sensors and controllers. In general, control performance deteriorates due to using low cost instruments with low resolutions. This paper investigates a method for cost-performance improvement of the AWD by using the dynamic quantizer (DQ) for practical use. So this study applies the dynamic quantizer into the SWDC controller of the AWD to prevent performance deterioration due to using the sensor and controllers with low resolutions. In addition, the parameters of the dynamic quantizer is optimized by Genetic Algorithm (GA) to achieve higher control performance under the condition using low resolution instruments. Usefulness and the performance of the proposed method are shown by numerical simulations.

In this paper we are interested in the problem of adaptive state observation of linear time-varying (LTV) systems where the system and the input matrices depend on unknown time-varying parameters. It is assumed that these parameters satisfy some known LTV dynamics, but with unknown initial conditions. Moreover, the state equation is perturbed by an additive signal generated from an exosystem with uncertain constant parameters. Our main contribution is to propose a globally convergent state observer that requires only a weak excitation assumption on the system, which is satisfied in the present context of regulation. [ABSTRACT FROM AUTHOR]

In this paper, we examine the potentiality of passive coherent location (PCL) for indoor area monitoring. In particular, we show that Wi-Fi transmissions can be successfully exploited as waveforms of opportunity to perform moving target detection and localization based on the passive radar principle. Moreover, we investigate the advanced capability to obtain high-resolution cross-range profiles of the observed targets via inverse-synthetic-aperture-radar (ISAR) techniques. To these purposes, appropriate processing techniques are introduced to cope with the limitations resulting from the indoor applications such as the strong returns from the stationary scene and the high density of potential targets. The proposed system concept has been tested against both simulated and real data sets. The reported results clearly show that using few receiving channels connected to properly dislocated antennas allows an accurate target localization and tracking. In addition, reliable and stable profiles are obtained for the targets moving in the surveyed scene, which might fruitfully feed a classification stage. This contributes to the demonstration of the effective applicability of the passive radar concept for improving internal and external security of private/public premises. [ABSTRACT FROM PUBLISHER]

Abstract: The adaptive disturbance cancellation problem is considered for single-input, single-output, linear systems when the linear exosystem which generates the disturbances to be rejected and/or the reference signals to be tracked is unknown, that is both its order and its parameters are unknown. The proposed regulator makes use of two observers and contains an adaptive internal model which tunes internal parameters on the basis of the output regulation error. It is shown that: if , that is the adaptive internal model can reproduce the required input, the regulation error tends exponentially to zero; if , that is the adaptive internal model can only approximate the required input within an approximation error , the regulation error tends exponentially into a closed ball whose radius is proportional to , provided that is sufficiently small so that singularities are avoided. [Copyright &y& Elsevier]

Ionic polymer-metal composites (IPMCs) are promising candidates in various sensing and actuation applications due to their light weight, large bending, and low actuation voltage requirements. However, IPMCs are still in the early stage of development, and their bending response can vary widely depending on various factors such as fabrication process, water content, temperature, and contact with electrodes. To control IPMCs in a predictable manner and to minimize the effects of plant uncertainty and external disturbances, a precise and robust control scheme is required. In the present work, a three-part adaptive feedforward control architecture is employed for IPMC deflection control. First, adaptive identification is performed to identify changes in the dynamic behavior over time and in the input voltage using a gradient descent method. Second, an adaptive feedforward controller is implemented to control the dynamic response of the plant, where the IPMC displacement is observed and is used to adjust the parameters of the controller. Third, noise and disturbance cancelling is performed using an additional adaptive canceller, which does not affect the system dynamics. Our results show that the adaptive identification and feedforward controller with disturbance cancellation using the gradient descent method provides accurate tracking performance under plant variation and disturbance. Especially, the fast convergence speed of the proposed technique makes it practical for online control. [ABSTRACT FROM AUTHOR]

A control method for achieving zero compliance to direct disturbance is proposed for a vibration isolation system. The structure of the proposed zero-compliance system is as follows. A middle mass is suspended by a spring from the base. The isolation table is suspended and moved by a linear actuator that is fixed to the middle mass. When direct disturbance acts on the isolation table, the middle mass begins to move in the same direction as the disturbance. The actuator operates to move the isolation table in the opposite direction to cancel the displacement of the middle mass to the base. To verify the effectiveness of this principle, a single-axis apparatus was fabricated. In this apparatus, the isolation table and the middle mass are guided to move horizontally to study characteristics without the influence of gravity. A voice coil motor (VCM) is installed between the isolation table and the middle mass, and integral—proportional—derivative (IPD) control is implemented to achieve displacement cancellation control. Another VCM is installed between the middle mass and the base, and PD control is implemented for realizing the prescribed stiffness and damping. The efficacy of the designed control system is confirmed experimentally. [ABSTRACT FROM AUTHOR]

An effective technique for extracting an audio input from a composite signal that contains a nonstationary noise-corrupted periodic disturbance is presented. The proposed technique cancels the periodic disturbance using a synthesized signal whose parameters are ad- justed adaptively. A combination of a generalized phase-locked loop (PLL) and an adaptive least mean square (LMS) method is used. The PLL creates a pair of basis signals that are phase-locked with the fundamental harmonic of the periodic disturbance. Harmonics generated from these basis signals are then used in the LMS method to minimize the average power of the residual nonperiodic signal. The virtue of this approach is that it does not depend on an explicit accurate estimate of the fundamental frequency of the disturbance. Furthermore, relatively large changes in the fundamental frequency can be tracked so long as they remain within the acquisition range of the PLL. Simulations and experimental results are presented that demonstrate the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

Abstract: An adaptive technique is presented that performs synchronous amplitude demodulation while adaptively canceling systematic disturbances—frequently encountered in sensors and instrumentation applications. The method is effective in jointly estimating and tracking the signal amplitude along with additive DC bias, interfering sinusoids, or exponentially decaying transients. Lyapunov method is used to study the stability and convergence of the proposed technique. In addition, the extension of the algorithm for multiple sinusoid case is also presented. Computer simulations and the experimental results are included to demonstrate the effectiveness and applicability of the proposed scheme in applications like resolver, synchros, and power system relays. It can easily be implemented in cost effective manner requiring minimal computation effort and hardware. [Copyright &y& Elsevier]

Abstract: For non-minimum phase plants, the loop transfer recovery (LTR) design of integral controllers based on the disturbance cancellation is considered. Since the design requires an unstabilizable extended plant, the standard LTR method cannot be applied. A new partial LTR method is proposed to overcome the difficulty. The target of the proposed design is a fictitious controller including a disturbance estimator based on the measurement of the minimum phase state. It is shown that the Riccati equation including the gain matrix of the disturbance estimator in the target can be used to recover the target feedback property in the output feedback controller. A simple design example is presented to show the effectiveness of the proposed method. [Copyright &y& Elsevier]