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This paper presents robust evolving cloud-based controller (RECCo) for the distributed solar collector field (DSCF). The main issue of the DSCF is that the primary energy source (variable) cannot be manipulated. Beside this, unpredictable changing of environmental conditions (outlet temperature, cloudiness, solar radiation) on the daily basis strongly influence the dynamics of the whole process. According...
This paper demonstrates a nonlinear robust controller design for the twin rotor control system (TRCS). TRCS is a multiple-input-multiple-output (MIMO) system having nonlinear, unstable and coupled dynamics. The proposed controller is designed using dynamic surface control (DSC) technique. The DSC is advance version of integral Backstepping control approach through the use of dynamic low pass filters...
This paper qualitatively, compares MRAC and Modified MRAC scheme when the adaptation laws are designed using different approaches. The controller parameter adaptation laws are designed based on the MIT rule and Lyapunov theory. The effect of augmenting the system with PID has also been studied. The augmented system provided better responses.
A global task coordinate frame (GTCF) based learning adaptive robust controller (LARC) is practically synthesized for an industrial X-Y linear-motor-driven stage to achieve not only good parametric adaptation ability and uncertain disturbance robustness, but also excellent transient/steady-state contouring performance. With the employment of GTCF which is globally based on the shape of the desired...
In this paper, we review a new approach in proving global boundedness of adaptive systems in the presence of nonparametric uncertainties. Recently, a rigorous mathematical proof has been suggested citing global boundedness for a class of unmodeled dynamics with minimal restrictions. The analytic methodology presented therein provides a novel approach to robust adaptive control. The underlying ideas,...
Designing missile autopilots is a challenging problem due to highly nonlinear uncertain aerodynamics, and stringent performance requirements. In this paper a robust adaptive augmenting controller is designed for a generic non-minimum phase pitch-axis missile autopilot. The control system consists of a robust L2 gain optimal controller as a baseline and an incremental robust direct Model Reference...
Adaptive control theory is a promising technology to improve the performance and stability of nominal controllers in the presence of system uncertainties. However, conventional model reference adaptive control schemes are not robust in the presence of unmodeled dynamics, actuator constraints etc. To overcome the above limitations, recently various new adaptive control schemes are proposed in the literature...
We propose a robust composite adaptive impedance controller with bounded-gain forgetting (BGF) for a three degree-of-freedom (3-DOF) active prosthetic leg for transfemoral amputees. We design a robust adaptive controller so the error trajectories converge to a boundary layer and the controller shows robustness to ground reaction forces (GRFs) and parameter uncertainties. The boundary layer not only...
In this paper, we propose a robust visual tracking method based on a temporal ensemble framework. Different from conventional ensemble-based trackers, which combine weak classifiers into a strong one using AdBoost in spatial fusion manners, our method adopts a powerful and efficient tracker integrated with its snapshots in different temporal windows of online tracking process to construct a temporal...
This paper presents a nonlinear internal model construction method by introducing certain coined Luenberger observer-like trial samples and further using Lyapunov's auxiliary theorem for confirmation. Specifically, it comes up with several novel types of parameterized nonlinear internal models with certain output in a constructive fashion, distinguishing themselves from existing ones proposed in the...
In this paper, the problem of robust tracking control is investigated. Simulation on the longitudinal model of a flexible air-breathing hypersonic vehicle (FAHV) with actuator saturation and uncertainties is conducted. In order to guarantee that the velocity and altitude to track their reference commands, an adaptive anti-up control strategy is presented based on sliding mode control method. The adaptive...
We study in this paper the problem of adaptive trajectory tracking control for a class of nonlinear systems with parametric uncertainties. We propose to use a modular approach: We first design a robust nonlinear state feedback that renders the closed loop input-to-state stable (ISS). Here, the input is considered to be the estimation error of the uncertain parameters, and the state is considered to...
For the ultralow altitude airdrop decline stage, many factors such as actuator nonlinearity, the uncertain atmospheric disturbances and model unknown nonlinearity affect the precision of trajectory tracking, A robust adaptive neural network dynamic surface control method is proposed. The ultra-low altitude airdrop longitudinal dynamics with actuator input nonlinearity is established, the neural network...
In modern power electronic systems, DC-DC converter is one of the main controlled power sources for driving DC systems. But the inherent nonlinear and time-varying characteristics often result in some difficulties mostly related to the control issue. This paper presents a robust nonlinear adaptive controller design with a recursive methodology based on the pulse width modulation (PWM) to drive a DC-DC...
This paper presents a self tuning robust predictive current controller that can be applied to both single and three phase grid tie voltage source inverters. Due to its adaptive capability, this control has a great robustness to paremetric variations, presents low steady-state current error and lowers dead time distortion in contrast with its nonadaptive variant (RPCC). Both simulation and experimental...
Traffic produces not only pollution but also many incidents producing material lost and human injuries or even persons dead. But not all the incidents involve two cars, it may be pedestrian and any type of cycles (motorcycles, bicycles, tricycles, etc). Most of the approaches try to model traffic accidents using traditional information and avoiding some other like environment elements, driver profile,...
In this paper, we present a new model reference adaptive control (MRAC) for flight control system of unmanned aerial vehicle (UAV) with uncertainties. The beginning of new algorithm design is combining direct MRAC with indirect adaptive control, which is called composite model reference adaptive control (CMRAC). In the indirect part, we use a reverse filter to filter the system input. Then, we employ...
This paper is dedicated to the memory of Steven L. Grant for his exceptional contributions to the echo cancellation problem. The regularization is mandatory in all ill-posed problems, especially in the presence of additive noise. In this paper, we consider the regularized recursive least-squares (RLS) algorithm and present a method to find its regularization parameter, depending on the signal-to-noise...
This paper aims at comparing two local outliers detection techniques. One is based on a Least Squares Support Vector Machine technique within a sliding window-based learning algorithm. A modification is proposed to improve its performance in non-stationary time-series. The second method relies on the Principal Component Analysis theory along with a robust orthonormal projection approximation subspace...
This paper presents a robust LQ control system with Model Reference Adaptive Control (MRAC) law for a jib crane. Our approaches show that the robust control performance is improved in the presence of nonlinear uncertainties by adding MRAC law into the usual robust control system. The proposed system is synthesized as follows. Firstly, the process to design a robust LQ controller in the framework of...
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