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This paper presents a robust predictive current (RPC) control method for permanent magnet synchronous motor (PMSM). The RPC controller adopts an incremental model, thus the influence of rotor flux can be omitted. This is the main contribution of RPC controller. Moreover, an inductance observer based on Lyapunov stability theorem is adopted to enhance inductance robustness against stator inductance...
Background Modelling is a crucial step in background/foreground detection which could be used in video analysis, such as surveillance, people counting, face detection and pose estimation. Most methods need to choose the hyper parameters manually or use ground truth background masks (GT). In this work, we present an unsupervised deep background (BG) modelling method called BM-Unet which is based on...
Digital predistortion (DPD) is an effective power amplifier (PA) linearization technique improving the system energy efficiency. At this point, real-time DPD adaptation is still an open issue due to the high computational complexity during the coefficients estimation procedure. Online censoring approach, which is effective in reducing the redundant data samples, can be applied in the DPD coefficients...
To deal with parametric uncertainty, load disturbance together with other nonlinear factors in highspeed permanent magnet synchronous motor (PMSM) systems, an adaptive robust controller (ARC) is proposed based on direct torque control method. In the high-speed PMSM modeling process, the unknown nonlinear factors, including modeling error and uncertain disturbance, are considered. Based on the optimized...
Three-degree-of-freedom trajectory tracking of the stratospheric airship is investigated. With a simplified planar dynamic model, an adaptive backstepping sliding mode controller is designed to keep the airship to globally asymptotically track a desired trajectory. Lyapunov functions are used to ensure the tracking performance when model parametric uncertainty and external disturbances exist. Simulation...
Many applications of computer vision, motion captures nowadays are an active research field. Supported by camera innovation in high definition technology and high-speed processing unit technology make higher degree on object detection standard. We can see it from the increasing number of new methods that have improvement in accuracy. In automatic vehicle surveillance area, Spatial Mixture Gaussian...
In this paper, we present a robust pole placement control scheme that can be used to control a wide class of linear and time invariant systems with unknown parameters, including nonminimum phase systems, using only plant input and output signals. We assume that the unknown plant parameters has known bounds, i.e., the control scheme is designed for an interval plant whose coefficients are closed intervals...
The robust adaptive control of uncertain system with unknown time-varying control coefficient is discussed. A novel output sampled control scheme based on characteristic model with neural network estimator is proposed. The design of the control scheme includes characteristic modeling, estimation for the characteristic parameters, and characteristic model-based adaptive control. The estimation method...
Model inaccuracies or parameter uncertainties are unavoidable in the practical control systems, while the uncertain properties could be modeled and estimated by the grey system. Among many grey models, fractional grey model is recently proposed and popularly used in many model analysis and prediction problems. In this paper, the structure uncertainties and external disturbances are considered using...
The interpolation of correspondences (EpicFlow) was widely used for optical flow estimation in most-recent works. It has the advantage of edge-preserving and efficiency. However, it is vulnerable to input matching noise, which is inevitable in modern matching techniques. In this paper, we present a Robust Interpolation method of Correspondences (called RicFlow) to overcome the weakness. First, the...
We consider the problem of depth-based robust 3D facial pose tracking under unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Unlike the previous depth-based discriminative or data-driven methods that require sophisticated training or manual intervention, we propose a generative framework that unifies pose tracking and face model adaptation on-the-fly. Particularly,...
Attitude control is essential for spacecraft to accomplish various tasks, and the attitude tracking is one of the most important attitude control tasks. In this paper the attitude tracking of a rigid spacecraft with bounded input is examined. At the same time, the unknown external disturbances are finite, but their boundaries are unknown. In order to make sure the attitude tracking errors converge...
In this paper, the finite time trajectory tracking method is established for hypersonic vehicles. A new quasi-linear parameter varying model is proposed and a finite time controller is designed by the sliding mode method of output feedback. The matching conditions of disturbances and uncertainties are satisfied naturally which ensures the established control method has very excellent robustness and...
Considering that the hypersonic vehicle is fast time-varying, high nonlinear and strong coupled, which makes designing a well performed controller rather difficult, this paper proposes an attitude control method based on exact feedback linearization control and characteristic model adaptive control to ensure the stability of the control system. Firstly, a nonlinear coupled dynamic model for the hypersonic...
Design of spinning projectile autopilot is a challenge due to uncertain aerodynamics, and stringent performance requirements. To solve the control challenge for such state inaccessible plant, a robust output feedback adaptive controller is designed for a double-channel controlled spinning projectile in this paper. The first step towards the solution is the development of the dynamic model for the...
This paper deals with the tracking control problem of uncertain transmission systems in the presence of elastic deadzone. Due to the derivative term in the elastic deadzone model, it is not straightforward to apply the backstepping control for the elastic system which is not in strict feedback form. To overcome this limitation, the system is first transformed into two cascaded subsystems and an adaptive...
With the development of economy, logistics becomes more and more important. Logistics efficiency depends on the structure of logistics networks. This paper briefly review the studies about complex networks from perspectives of statistical properties, structural models and application areas. Logistics networks and complex networks have same behavior pattern, so we can apply the theories of complex...
This paper proposes a robust adaptive Backstepping controller for the quadrotor attitude dynamics. The attitude dynamic model is obtained to translate into a MIMO nonlinear system with generalized uncertainty. To overcome complex disturbances from various uncertainties, we design a strict feedback controller for the system. It's used to counteract the influence of the uncertainties by robust adaptive...
Deep convolution networks based strategies have shown a remarkable performance in different recognition tasks. Unfortunately, in a variety of realistic scenarios, accurate and robust recognition is hard especially for the videos. Different challenges such as cluttered backgrounds or viewpoint change etc. may generate the problem like large intrinsic and extrinsic class variations. In addition, the...
We propose a diffusion expectation-maximization algorithm with adaptive combiner for distributed estimation over sensor networks. Due to the spatial distribution of the nodes, variation of node profile across the network is a common phenomena in real applications. The unreliable nodes exist and provide inaccurate estimates, which may be caused by high levels of noise or malicious attacks. Instead...
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