The generalized ESPRIT (GESPRIT) method extends the conventional ESPRIT estimator to estimate the directions-of-arrival (DOAs) of multiple incident signals by using the array with more general geometrical configur...
The generalized ESPRIT (GESPRIT) method extends the conventional ESPRIT estimator to estimate the directions-of-arrival (DOAs) of multiple incident signals by using the array with more general geometrical configurations, where the translational invariance structure is not required. Unfor-tunately, the GESPRIT has serious ambiguous DOA estimates in some scenarios, and its performance degrades severely at low signal-to-noise ration (SNR) and with a small number of snapshots. Although a polynomial version of a new GESPRIT (NGESPRIT) method was given, but its derivation and estimation performance are unavailable in published literature. In this paper, in order to overcome the ambiguity of the GESPRIT and improve the estimation performance, the NGESPRIT method is derived explicitly. Moreover, the equivalence between the proposed NGESPRIT method and the rank reduction (RARE) method is clarified, while the former is more computationally efficient than the latter. Finally the effectiveness of the NGESPRIT method is substantiated through numerical examples.
This paper deals with the problem of tracking the two-dimensional (2-D) direction-of-arrivals (DOAs) (i.e., azimuth and elevation angles) of multiple moving targets with crossover points on their trajectories, and we ...
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This paper deals with the problem of tracking the two-dimensional (2-D) direction-of-arrivals (DOAs) (i.e., azimuth and elevation angles) of multiple moving targets with crossover points on their trajectories, and we propose an new computationally efficient subspace-based 2-D DOA tracking algorithm for the L-shaped sensor array structured by two uniform linear arrays (ULAs). First, a new computationally efficient cross-correlation based 2-D DOA estimation with automatic pairmatching (CODEC) batch method is developed for noncoherent narrowband signals, where the computationally expensive procedures of eigendecomposition in subspace estimation and pair-matching of the estimated azimuth and elevation angles are avoided. Then a new 2-D DOA tracking algorithm is proposed, the association of the estimated azimuth and elevation angles at two successive time instants is accomplished by employing a dynamic mode and the Luenberger state observer. The simulation results show that the proposed tracking algorithm has good adaptability and tracking capability.
In some practical applications, the two-dimensional (2-D) direction-of-arrivals (DOAs) of incident signals should be estimated adaptively or the time-varying 2-D DOAs should be tracked promptly from the noisy array da...
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In some practical applications, the two-dimensional (2-D) direction-of-arrivals (DOAs) of incident signals should be estimated adaptively or the time-varying 2-D DOAs should be tracked promptly from the noisy array data, and multipath propagation is usually encountered due to various reflections, where the incident signals are caused to be coherent (i.e., fully correlated). In this paper, we propose a new computationally efficient subspace-based adaptive algorithm for 2-D DOA tracking of multiple coherent incident signals by using two parallel uniform linear arrays (ULAs). In the proposed algorithm, the computationally expensive eigendecomposition and the pair-matching of estimated 2-D DOAs are avoided, and the association of estimated 2-D DOAs at two successive time instants is accomplished by employing the Luenberger observer and dynamic model of direction trajectories. The effectiveness of the proposed algorithm are verified through numerical examples.
In this paper, we address with the problem of detection the number of narrowband signals impinging on a uniform linear array (ULA) in the presence of multipath propagation. Firstly, by forming a differencing matrix fr...
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In this paper, we address with the problem of detection the number of narrowband signals impinging on a uniform linear array (ULA) in the presence of multipath propagation. Firstly, by forming a differencing matrix from the array covariance matrix to eliminate the effects of uncorrelated incident signals and additive noises, a combined matrix is constructed from this differencing matrix to decorrelate the coherence of signals. Since the number of coherent signals is revealed as the rank of this resultant matrix, a singular value based ratio criterion is proposed to estimate the number of coherent signals. Then, another singular value based ratio criterion is also presented to determine the number of uncorrelated signals from the array covariance matrix. The notable advantage of the proposed method is that it can detect more signals compared to some existing methods, and the number of signals resolved by our method can exceed the number of array sensors.
This paper considers synchronization problem of an uncertain complex dynamical network. The norm-bounded uncertainties enter into the complex dynamical network in randomly ways, and such randomly occurring uncertainti...
This paper considers synchronization problem of an uncertain complex dynamical network. The norm-bounded uncertainties enter into the complex dynamical network in randomly ways, and such randomly occurring uncertainties (ROUs) obey certain mutually uncorrelated Bernoulli distributed white noise sequences. Under the circumstances, a robust $\mathcal{H}_{\infty}$ decentralized dynamic feedback controller is designed to achieve asymptotic synchronization of the network. Based on Lyapunov stability theory and linear matrix inequality (LMI) framework, the existence condition for feasible controllers is derived in terms of LMIs. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our result.
We present a new approach for the synthesis of robust fault detection filters for the model based diagnosis of actuator faults. The underlying synthesis model is a linear pa- rameter varying (LPV) description obtained...
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Permanent magnet synchronous motors (PMSMs) produce a parasitic oscillating torque due to several reasons. This contribution cancels the oscillating torque with adaptive control algorithms. Therefore a mathematical mo...
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Permanent magnet synchronous motors (PMSMs) produce a parasitic oscillating torque due to several reasons. This contribution cancels the oscillating torque with adaptive control algorithms. Therefore a mathematical model of the PMSM is necessary. A model with nonlinear dynamics and a Fourier approach for the ripples is used as a mathematical description. Through comparisons between measured data and simulated data it is shown that the model assumptions are valid. The adaptive algorithm is implemented as an add-on controller to the already existing controlsystem which consists of a feedforward part and a basis controller. The challenge is that the closed loop system has a resonant frequency and the algorithm should have the same performance for all frequencies. Experimental results show the performance and convergence of the adaptive algorithm at constant and non constant velocity.
Abstract Robots are often run with permanent magnet synchronous motors (PMSM) with a high ratio gearbox. Both parts can produce parasitic oscillations (ripples), which let the robot shake at tool center point. The gea...
Abstract Robots are often run with permanent magnet synchronous motors (PMSM) with a high ratio gearbox. Both parts can produce parasitic oscillations (ripples), which let the robot shake at tool center point. The gearbox ripple problem is more complicated to be solved with control theory because only motor side sensors should be used. Due to the internal model principle gearbox side information is necessary to solve the problem. The first algorithm uses an observer to get gearbox side information where the second algorithm uses a gearbox side rate sensor. The algorithms are tested with a nonlinear SISO problem and with a nonlinear MIMO system. In both cases the ripples are canceled with an adaptive controller which estimates the phase and magnitude of the ripple. This adaptive controller is designed separately and is added to the existing basis controller. The algorithms are tested in simulation and on a testbed, which is an industrial application.
This paper describes how the previously developed concept of Pseudo control Hedging (PCH) can be integrated in a Fault Tolerant Flight controller (FTFC) as a safe flight envelope protection system of the first degree....
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There has been an increasing interest in a kind of underactuated mechanical systems, mobile wheeled inverted pendulum (MWIP) models, which are widely used in the field of autonomous robotics and intelligent vehicles. ...
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ISBN:
(纸本)9781424447749;9781424447756
There has been an increasing interest in a kind of underactuated mechanical systems, mobile wheeled inverted pendulum (MWIP) models, which are widely used in the field of autonomous robotics and intelligent vehicles. A novel structure including an MWIP system and a movable seat called UW-Car is proposed in the study. The dynamic model of UW-Car system running in the flat ground is obtained by applying Lagrange's motion equation. A sliding mode control (SMC) method is proposed for the dynamic model, which is capable of both handling the mismatched perturbation and keeping the body upright. An optimal braking scheme is introduced which reduces the velocity of UW-Car to zero first and adjusts the displacement of seat to the centre position. Genetic Algorithm (GA) is adopted to search the optimal parameters for sliding mode controller. The optimal braking scheme is implemented by on-line switching three sliding mode controllers. The effectiveness of the proposed methods is finally confirmed by numerical simulation.
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