Publications

The modeling and attitude stabilization control problems of a four-rotor vertical takeoff and landing unmanned air vehicle (UAV) known as the quadrotor are investigated. The quadrotor’s attitude is represented by the unit quaternion rather than Euler angles to avoid singularity problem. Taking dynamical behavior of motors into consideration and ignoring aerodynamic effect, a nonlinear controller is developed to stabilize the attitude. The control design is accomplished by using backstepping control technique. The proposed control law is based on the compensation for the Coriolis and gyroscope torques. Applying Lyapunov stability analysis proves that the closed-loop attitude system is asymptotic stable. Moreover, the controller can guarantee that all the states of the system are uniformly ultimately bounded in the presence of external disturbance torque. The effectiveness of the proposed control approach is analytically authenticated and also validated via simulation study.

This paper deals with the problem of sliding mode control design for nonlinear stochastic singular semi-Markov jump systems (S-MJSs). Stochastic disturbance is first considered in studying S-MJSs with a stochastic semi-Markov process related to Weibull distribution. The specific information including the bound of nonlinearity is known for the control design. Our attention is to design sliding mode control law to attenuate the influences of uncertainty and nonlinear term. First, by the use of the Lyapunov function, a set of sufficient conditions are developed such that the closed-loop sliding mode dynamics are stochastically admissible. Then, the sliding mode control law is proposed to ensure the reachability in a finite-time region. Finally, the practical system about dc motor model is given to verify the validity of the proposed method.

This paper presents a delay-dependent approach to robust filtering for linear parameter-varying (LPV) systems with discrete and distributed time-invariant delays in the states and outputs. It is assumed that the state-space matrices affinely depend on parameters that are measurable in real-time. Some new parameter-dependent delay-dependent stability conditions are established in terms of linear matrix inequalities (LMIs) such that the filtering process remains asymptotically stable and satisfies a prescribed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance level. Using polynomially parameter-dependent quadratic (PPDQ) functions and some Lagrange multiplier matrices, we establish the parameter-independent delay-dependent conditions with high precision under which the desired robust H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> filters exist and derive the explicit expression of these filters. A numerical example is provided to demonstrate the validity of the proposed design approach.

Notice of Violation of IEEE Publication Principles <br><br> After careful consideration by a duly constituted committee, an author of this article, Hamid Reza Karimi, was found to have acted in violation of the IEEE Principles of Ethical Publishing by artificially inflating the number of citations to this article. <br/> This brief paper studies the exponential stabilization problem for the Takagi-Sugeno fuzzy systems with a variable sampling. Different from previous results, the gains of fuzzy state feedback controller adopted in this paper are time-varying during two consecutive sampling instants, which can contribute to the enlargement of the allowable sampling interval by choosing a suitable design parameter. To reduce the design conservativeness, a novel fuzzy time-dependent Lyapunov functional (FTDLF) is put forward to fully exploit the accessible information about the sampling pattern and the fuzzy basis functions. Moreover, a more relaxed constraint condition is presented to ensure the positive definiteness of the FTDLF on sampling intervals. By resorting to the novel FTDLF and the relaxed constraint condition, new exponential stabilization criteria dependent on and independent of upper bounds on time derivatives of fuzzy basis functions are established, by which a larger sampling interval can be achieved. One example is offered to demonstrate the validity and superiorities of the obtained new results.

An exponential H8 synchronization method is addressed for a class of uncertain master and slave neural networks with mixed time-delays, where the mixed delays comprise different neutral, discrete and distributed time-delays. An appropriate discretized Lyapunov-Krasovskii functional and some free weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing a delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H8 synchronization of the two coupled master and slave neural networks regardless of their initial states. Numerical simulations are provided to demonstrate the effectiveness of the established synchronization laws.

We address the problem of downlink throughput improvement for IEEE 802.11a/g systems by using a modified access point equipped with multiple antennas. The main restriction is that the standard terminals should not be modified in any way. An alternating time-offset space division multiple access (SDMA) solution is proposed for a conference room scenario. A simulation is based on channel models approved by the IEEE 802.11 Standards Group and takes into account the main features of the IEEE 802.11a/g standard. It is demonstrated that a near doubling of downlink capacity can be achieved in a conference room environment.

A wavelet-based approach is presented in this paper to reconstruct acceleration pulse of a vehicle involved in a crash event. The described method for time-frequency analysis is based on techniques which investigate both: time and frequency components of a signal being considered. It is achieved in this work by application of Morlet wavelet properties. Major frequency components which are included in the original acceleration pulse are identified. Subsequently, their times of occurrence are detected as well. Those steps are necessary for multiresolution analysis which leads to creation of a scalegram of the reference signal. Finally, having full insight into the time-frequency components of the analyzed characteristics, the reconstruction of the reference signal is executed — superposition principle allows to combine major signal components yielding the reproduced crash pulse. The comparative analysis between the current method's outcome and the behavior of a real car is performed and reliability of the actual methods and tools is evaluated.

Two closely related iterative receivers for mitigation of both intra- and inter-cell interference are considered for HSDPA in UTRA-TDD. The first receiver is based on coherent detection with pre-whitening with respect to the spatio-temporal structure of the interference. The second receiver is based on interference suppression via deterministic least-squares filtering. The performance of the receivers is evaluated via system-aware link-level simulations of 2-cell indoor and 7-cell urban scenarios. Performance improvements over the conventional RAKE receiver are reported in the form of BER statistics.

Within the context of the environmental perception of autonomous vehicles (AVs), this paper establishes a sensor model based on the experimental sensor fusion of lidar and monocular cameras. The sensor fusion algorithm can map three-dimensional space coordinate points to a two-dimensional plane based on both space synchronization and time synchronization. The YOLO target recognition and density clustering algorithms obtain the data fusion containing the obstacles’ visual information and depth information. Furthermore, the experimental results show the high accuracy of the proposed sensor data fusion algorithm.

In this paper, first, an adaptive neural network (NN) state-feedback controller for a class of nonlinear systems with mismatched uncertainties is proposed. By using a radial basis function NN (RBFNN), a bound of unknown nonlinear functions is approximated so that no information about the upper bound of mismatched uncertainties is required. Then, an observer-based adaptive controller based on RBFNN is designed to stabilize uncertain nonlinear systems with immeasurable states. The state-feedback and observer-based controllers are based on Lyapunov and strictly positive real-Lyapunov stability theory, respectively, and it is shown that the asymptotic convergence of the closed-loop system to zero is achieved while maintaining bounded states at the same time. The presented methods are more general than the previous approaches, handling systems with no restriction on the dimension of the system and the number of inputs. Simulation results confirm the effectiveness of the proposed methods in the stabilization of mismatched nonlinear systems.

This paper is concerned with the state feedback control problem for a class of two-dimensional (2D) discrete-time stochastic systems with time-delays, randomly occurring uncertainties and nonlinearities. Both the sector-like nonlinearities and the norm-bounded uncertainties enter into the system in random ways, and such randomly occurring uncertainties and nonlinearities obey certain mutually uncorrelated Bernoulli random binary distribution laws. Sufficient computationally tractable linear matrix inequality–based conditions are established for the 2D nonlinear stochastic time-delay systems to be asymptotically stable in the mean-square sense, and then the explicit expression of the desired controller gains is derived. An illustrative example is provided to show the usefulness and effectiveness of the proposed method.Keywords: 2D stochastic systemsrandomly occurring uncertaintiesrandomly occurring nonlinearitieslinear matrix inequality (LMI) AcknowledgementsThe third author would like to thank the Alexander-von-Humboldt Foundation for providing the support to this research possible. The authors are also grateful to the anonymous reviewers for their helpful comments.Additional informationFundingThis work was supported by the National Natural Science Foundation of China under [grant number 61273120].Notes on contributorsZhaoxia DuanZhaoxia Duan was born in Sichuan Province, China, in 1989. She received her BS degree in Automation from Nanjing University of Science and Technology (NUST), Nanjing, China, in 2011. Now she is pursuing a PhD degree in Control Theory and Control Engineering from NUST, Nanjing, China. Her current research interests include robust control and filtering, switched systems, two-dimensional systems and nonlinear systems. Display full sizeZhengrong XiangZhengrong Xiang received his PhD degree in Control Theory and Control Engineering at Nanjing University of Science and Technology, Nanjing, China, in 1998. Since 1998, he has been faculty member and he is currently full professor at Nanjing University of Science and Technology. He was appointed as Lecturer in 1998 and Associate Professor in 2001 at Nanjing University of Science and Technology. He is a member of the IEEE, member of the Chinese Association for Artificial Intelligence. His main research interests include switched systems, nonlinear control, robust control and networked control systems. Display full sizeHamid Reza KarimiHamid Reza Karimi is a Professor in Control Systems at the Faculty of Engineering and Science of the University of Agder in Norway. His research interests are in the areas of nonlinear systems, networked control systems, robust control/filter design, time-delay systems, wavelets and vibration control of flexible structures with an emphasis on applications in engineering. He is a senior member of IEEE and serves as chairman of the IEEE chapter on control systems at IEEE Norway section. He is also serving as an editorial board member for some international journals, such as Mechatronics, Neurocomputing, Information Sciences, Asian Journal of Control, Journal of Franklin Institute, Journal of Systems and Control Engineering, and International Journal of Control, Automation and Systems. He is a member of IEEE Technical Committee on Systems with Uncertainty, IFAC Technical Committee on Robust Control and IFAC Technical Committee on Automotive Control. Display full size

This paper presents application of physical models composed of springs, dampers and masses joined together in various arrangements to simulation of a real car collision with a rigid pole. Equations of motion of those systems are being established and subsequently solutions to obtained differential equations are formulated. We start with a general model consisting of two masses, two springs, and two dampers, and illustrate its application to represent fore-frame and aft-frame of a vehicle. Hybrid models, as being particular cases of two mass-spring-damper model, are elaborated afterwards and their application to predict results of real collision is shown. Models’ parameters are obtained by fitting their response equations to the real vehicle's crush coming from the acceleration measurement analysis. For full-scale experiment and created models we perform both: kinematic and energy responses comparative analysis.

This paper presents an adaptive neural control approach for nonstrict-feedback nonlinear systems in presence of unmodeled dynamics, unknown control directions and input dead-zone nonlinearity. To handle the difficulty due to uncertain control directions, Nussbaum gain functions are applied. Based on the structural characteristic of radial basis function neural networks, a backstepping-based adaptive neural control algorithm is developed. The main contributions of this paper lie in the fact that a backstepping-based neural control algorithm is developed for nonstrict-feedback nonlinear systems with unmodeled dynamics, unknown control directions and actuator dead-zone, and the total number of adaptive laws is not greater than the order of control system. As a beneficial result, the controller is much easier to be implemented in practice with less computational burden. A simulation example is given to reveal the viability of the presented approach. It is demonstrated by both theoretical analysis and simulation study that the presented control strategy ensures the semiglobally uniform ultimate boundedness of all closed-loop system signals.

This report considers attempts to develop dummy motorcyclists with breakable legs. Material characteristics are discussed. The variation in the scatter fracture load of different materials is compared using the Weibull modulus. The materials used in the different dummy legs have been calibrated statically and uni-axially whereas in crash tests multi-axial dynamic loads are sustained. The Independent Action criterion is used to show that: (1) compressive and torsion loads have only a small effect on bending; and (2) differences in results from different laboratories is the result of scatter in the material characteristics. The effect that leg fracture has on dummy trajectory is described using previously published experimental pedestrian impacts, motorcycle crash tests and pedestrian and car occupant computer simulation studies. Head trajectory is shown to be largely unaffected by leg fracture. For the covering abstract of the conference see IRRD 864606.

This paper deals with a convex optimization approach to the problem of robust network-based H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control for linear systems connected over a common digital communication network with norm-bounded parameter uncertainties. Firstly, we investigate the effect of both the output quantization levels and the network conditions under static quantizers. Secondly, by introducing a descriptor technique, using Lyapunov-Krasovskii functional and a suitable change of variables, new required sufficient conditions are established in terms of delay-range-dependent linear matrix inequalities for the existence of the desired network-based quantized controllers with simultaneous consideration of network induced delays and measurement quantization. The explicit expression of the controllers is derived to satisfy both asymptotic stability and a prescribed level of disturbance attenuation for all admissible norm bounded uncertainties. One example is utilized to illustrate the design procedure proposed in this paper.