1 School of Astronautics, Harbin Institute of Technology, Harbin, Heilongjiang, China 2 School of Electrical and Electronic Engineering, The University of Adelaide, SA 5005, Australia 3 Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway 4 Institute of Automation and Complex Systems, University of Duisburg-Essen, Duisburg, Germany 5 College of Automation, Chongqing University, Chongqing 400044, China
In this paper, a new approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the ant colony optimization (ACO) is proposed. On-line adaptive fuzzy identification is introduced to identify the system parameters. These parameters are used to calculate the objective function based on a predictive approach and structure of RST control. Then the optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to determine optimal controller parameters of RST control. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, where the proposed approach provides better performances compared with proportional integral-ant colony optimization controller and adaptive fuzzy model predictive controller.
This study deals with linear parameter-varying modelling and output-feedback H∞ control design for an offshore wind turbine. The controller is designed with consideration that not all the information in the feedback loop will be used. This constraint is incorporated into the design procedure. Constrained information means that a special zero-non-zero pattern is forced upon the gain matrix. The constrained controller is obtained based on parameter-dependent Lyapunov functions and formulated in terms of linear-matrix inequalities. Since the functions are dependent on the wind speed and accurate wind speed measurements are rarely available in practice, an extended Kalman filter is used to estimate the wind speed. The controller is designed in such a way that it should maintain its stability and performance even if one of the sensors in the feedback loop should malfunction. The control objectives are to mitigate oscillations in the structure and drivetrain, to smoothen power/torque output in addition to keep the closed-loop system stable. This should be achieved by means of individual blade pitch. A traditional procedure for designing a controller for such a system is to choose an operating point and assume it works in a suitable way under the influence of turbulent wind. In this study, the wind turbine model is obtained from the software fatigue, aerodynamic, structural and turbulence (FAST). To design the controller, the model is linearised about several operating points. The degrees of freedom in the linearised model are chosen according to the controller objectives. The linear models are valid within the span of operating points. Finally, the controller is tested on the fully non-linear system under the influence of turbulent wind and a scenario where one of the sensors in the feedback loop is malfunctioning. The closed-loop response of the presented controller is compared to the closed-loop response of the baseline controller included in the FAST package along with a controller designed based on a single linearised model.
This paper deals with the controller synthesis for a class of positive two-dimensional (2D) switched delay systems described by the Roesser model. This kind of systems has the property that the states take nonnegative values whenever the initial boundaries are nonnegative, some delay-dependent sufficient conditions for the exponential stability of positive 2D switched systems with state delays are given. Furthermore, the design of positive state feedback controller under which the resulting closed-loop system meets the requirements of positivity and exponential stability is presented in terms of linear matrix inequalities (LMIs). An example is included to illustrate the effectiveness of the proposed approach.
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.
No abstract is provided for this article.
In this paper, the problems of estimations of faults and fault-tolerant control design are simultaneously discussed for a class of uncertain Takagi-Sugeno fuzzy descriptor systems. First, a fuzzy adaptive observer, which can decouple the external disturbances, is proposed to provide the state, actuator fault and sensor fault estimations. Then, on the basis of the estimated information, an actuator fault-tolerant controller is proposed to stabilize the descriptor closed-loop system while attenuating the disturbances by the H technique. The existence conditions of the designed observer and controller are given in terms of linear matrix inequalities, which can be solved easily by some mathematical tools. Finally, a numerical example is provided to validate the effectiveness of the proposed methods.
With the rapid development of automation technologies, aerospace engineering systems, including aircraft, satellite, and spacecraft, have become increasingly susceptible to system/component malfunctions. Failure to take appropriate responses to even relatively minor defects can result in highly destructive events. A conventional feedback control design may result in an unsatisfactory performance or even instability in the event of malfunctions. Because of this, fault diagnosis (FD) and fault-tolerant control (FTC) technologies that can ensure the safety of handicapped systems have attracted significant interest. FTC design and relevant techniques have provided a flexible framework for dealing with these challenges since the 1970s. There has been significant progress since the 1970s by the active research community, through symposiums and seminars, as well as the vast number of publications on the subject. The research illustrates that FD and FTC are effective and applicable in many engineering plants, especially for aerospace engineering systems. However, it still remains a challenging research area in applications relating to aircraft, spacecraft, and satellites.
In this article, a computationally effective strategy to obtain multioverlapping controllers via the inclusion principle is applied to design a state-feedback multioverlapping linear-quadratic regulator controller for a 20-story building. The proposed semidecentralized controller only requires state information of neighboring stories to compute the corresponding control actions. This particular information exchange configuration allows introducing a dramatic reduction in the transmission range required for a wireless implementation of the communications system. More specifically, just a one-story transmission range is required by the proposed multioverlapping controller, while a full-building transmission range would be necessary in a classical centralized design. From a computational point of view, the presented design strategy only involves the actual computation of a reduced set of low-dimension controllers. The numerical simulations indicate that despite the simplified low-dimension design and the severe information exchange constraints, the proposed semidecentralized multioverlapping controller achieves a surprisingly high level of seismic attenuation when compared with the centralized linear-quadratic regulator controller.
An eigensystem realization algorithm (ERA) approach for estimating the structural system matrices is proposed in this paper using the measurements of acceleration data available from the real crash test. A mathematical model that represents the real vehicle frontal crash scenario is presented. The model’s structure is a double-spring-mass-damper system, whereby the front mass represents the vehicle-chassis and the rear mass represents the passenger compartment. The physical parameters of the model are estimated using curve-fitting approach, and the estimated state system matrices are estimated by using the ERA approach. The model is validated by comparing the results from the model with those from the real crash test.
In this chapter, we investigate the observer-based finite-time robust H ∞ vibration control problem for half-car active suspension systems with actuator parametric uncertainties and nonlinearities. The objective is to derive a suitable robust vibration controller which makes the vibration of the closed-loop suspension system be finite-time stabilizable and satisfies the given H ∞ performance index. Applying the Lyapunov function approach, we establish sufficient conditions to control the bounce and pitch vibrations in half-car active suspension system, stabilize the attitude of the vehicle, and improve the riding comfort. The observer-based finite-time robust H ∞ vibration controller gain parameters can be solved directly by using the existing linear matrix inequalities optimization techniques. Finally, a half-car active suspension model is used to illustrate the feasibility and validity of the proposed methods.
This paper investigates the problems of delay-dependent stability analysis and memory ℋ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller synthesis for a class of continuous-time Markovian jump linear systems (MJLSs) via an input-output (IO) approach. The generality lies in that the exactly known, partially unknown and uncertain transition rates are simultaneously incorporated into the defective mode information. It is first shown that the original system with time-varying delay can be reformulated by a new IO model through a process of two-term approximation and the stability problem of the original system can be transformed into the scaled small gain (SSG) problem of the IO model. Then, based on a Markovian Lyapunov-Krasovskii formulation of SSG condition together with some convexification techniques, the stability analysis and state-feedbackℋ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller synthesis conditions for the underlying MJLSs are formulated in terms of linear matrix inequalities. Simulation studies are provided to illustrate the effectiveness and superiority of the proposed analysis and design methods.
This paper investigates the problem of quantized filtering for a class of continuous‐time Markovian jump linear systems with deficient mode information. The measurement output of the plant is quantized by a mode‐dependent logarithmic quantizer, and the deficient mode information in the Markov stochastic process simultaneously considers the exactly known, partially unknown, and uncertain transition rates. By fully exploiting the properties of transition rate matrices, together with the convexification of uncertain domains, a new sufficient condition for quantized performance analysis is first derived, and then two approaches, namely, the convex linearization approach and iterative approach, to the filter synthesis are developed. It is shown that both the full‐order and reduced‐order filters can be obtained by solving a set of linear matrix inequalities (LMIs) or bilinear matrix inequalities (BMIs). Finally, two illustrative examples are given to show the effectiveness and less conservatism of the proposed design methods.
