This paper investigates the problem of robust H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> filtering for uncertain two-dimensional (2-D) discrete systems in the Fornasini-Marchesini local state-space (FM LSS) model with polytopic uncertain parameters. The goal of the paper is to design filters such that the finite frequency (FF) H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> norm of the filtering error system has a specified upper bound for all uncertainties. A generalized bounded real lemma (BRL) is first derived for FF H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance analysis of nominal 2-D FM LSS systems, and then a method, in terms of solving optimization problems with LMI constraints, is presented for robust FF H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> filter analysis and design. An illustrative example is given to show the improvements of the proposed filter design methods.
Active noise control (ANC) methods have been extensively used for reducing the noise level over the past decade. In particular, in the range of low frequencies they can effectively reduce the noise level higher than passive control methods. However, except in some special cases, in ANC only local zones of quiet are obtained. In this paper one of such exceptions is investigated—an active noise-controlling casing. More specifically, a noise source is placed inside the casing. Casing vibrations are actively controlled to achieve global noise reduction in free-field conditions. The global noise reduction is obtained using the Switched Error FXLMS algorithm and using error signals from error microphones located at appropriate points around the casing. It is shown that selected microphone array configurations can provide global noise reduction in free-field conditions. Performance of this approach is experimentally verified in a laboratory room with an exemplary acoustic treatment.
The Transport and Road Research Laboratory has previously reported on research which shows that leg protection for motorcyclists can be designed which will be of benefit to the legs without detriment to the head. It has also been shown that the United Kingdom draft specification on leg protection can be sucessfully applied to a large touring machine. This report describes the application of leg protection to a sports motorcycle Kawasaki GPZ 500S. The purpose of the test series was twofold. First, to show the effect of leg protection, designed and tested to the U.K. draft specification, on the potential leg and head injuries when fitted to a sports motorcycle. The second purpose was to compare the performance of the TRRL injury indicating leg, which is not frangible, with one that is, and to determine whether or not the TRRL leg is an appropriate device with which to assess potential leg injuries and dummy trajectory in motorcycle impact testing. For the covering abstract see IRRD 853578.
In this paper, the problems of output tracking control and filtering are investigated for Takagi-Sugeno fuzzy-approximation-based nonlinear descriptor systems in the discrete-time domain. Especially, the unreliability of the communication links between the sensor and actuator/filter is taken into account, and the phenomenon of packet dropouts is characterized by a binary Markov chain with uncertain transition probabilities, which may reflect the reality more accurately than the existing description processes. A novel bounded real lemma (BRL), which ensures the stochastic admissibility with H∞ performance for fuzzy discrete-time descriptor systems despite the uncertain Markov packet dropouts, is presented based on a fuzzy basis-dependent Lyapunov function. By resorting to the dual conditions of the obtained BRL, a solution for the designed fuzzy output tracking controller is given. A design method for the full-order fuzzy filter is also provided. Finally, two examples are finally adopted to show the applicability of the achieved design strategies.
This paper employs fuzzy set theory to solve the unintuitive problem of the Markowitz mean‐variance (MV) portfolio model and extend it to a fuzzy investment portfolio selection model. Our model establishes intervals for expected returns and risk preference, which can take into account investors′ different investment appetite and thus can find the optimal resolution for each interval. In the empirical part, we test this model in Chinese stocks investment and find that this model can fulfill different kinds of investors’ objectives. Finally, investment risk can be decreased when we add investment limit to each stock in the portfolio, which indicates our model is useful in practice.
This paper investigates the sampled-data stabilization problem of spacecraft relative positional holding with improved Lyapunov function approach. The classical Clohessy-Wiltshire equation is adopted to describe the relative dynamic model. The relative position holding problem is converted into an output tracking control problem using sampling signals. A time-dependent discontinuous Lyapunov functionals approach is developed, which will lead to essentially less conservative results for the stability analysis and controller design of the corresponding closed-loop system. Sufficient conditions for the exponential stability analysis and the existence of the proposed controller are provided, respectively. Finally, a simulation result is established to illustrate the effectiveness of the proposed control scheme.
This paper presents development of a mathematical model to represent the real vehicle frontal crash scenario. The vehicle is modeled by a double spring-mass-damper system. The front mass m <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> represents the chassi of the vehicle and rear mass m <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> represents the passenger compartment. The physical parameters of the model (Stiffness and dampers) are estimated using Nonlinear least square method (Levenberg-Marquart algorithm) by curve fitting the response of a double spring-mass-damper system to the experimental displacement data from the real vehicle crash. The model is validated by comparing the results from the model with the experimental results from real crash tests available.
No abstract is provided for this article.
In recent years, significant advances in vibration control of structures have been achieved due greatly to the emergent technologies based on smart materials, such as mangnetorheological (MR) fluids. This paper develops a computational algorithm for the modeling and identification of the MR dampers by using wavelet systems to handle the nonlinear terms. By taking into account the Haar wavelets, the properties of integral operational matrix and of product operational matrix are introduced and utilized to find an algebraic representation form instead of the differential equations of the dynamical system. It is shown that MR damper parameters can be estimated easily by considering only the algebraic equations obtained.
The problem of trajectory tracking is considered in this paper for Lagrange systems disturbed by second moment processes. For random differential equations, the concept of noise-to-state practical stability and its criterion are proposed. A state-feedback tracking control is designed by using vectorial backstepping method, which covers Slotine–Li controller and “PD+” controller as special cases. As natural extension, adaptive control is further researched, and a practical equivalence principle is presented. For the above two cases, results of global noise-to-state stability of closed-loop systems are obtained, and practical trajectory tracking can be achieved under a practical parameters-tuning principle. Simulations are conducted for a nonlinear benchmark system to illustrate the effectiveness and advantages of the proposed new control strategies.
In this paper a state-space estimation procedure that relies on the time-domain analysis of input and output signals is used for mathematical modeling of vehicle frontal crash. The model is a double-spring–mass–damper system, whereby the front mass and real mass represent the chassis and the passenger compartment, respectively. It is observed that the dynamic crash of the model is closer to the dynamic crash from experimental when the mass of the chassis is greater than the mass of the passenger compartment. The dynamic crash depends on pole placement and the estimated parameters. It is noted that when the poles of the model are closer to zero, the dynamic crash of the model is far from the dynamic crash from the experimental data. The stiffness and damping coefficients play an important role in the dynamic crash.
