This paper investigates the problem of network-based H ∞ output feedback control for a class of stochastic nonlinear systems. A novel model is proposed to describe the systems taken into two sides of communication channels in the network environment, which is more general than one side of communication channel. The design procedure of observer-based controller is presented, which guarantees the asymptotic stability in the mean square of the resulting closed-loop system with an H ∞ performance. Finally, a crane example is utilized to show the effectiveness and potential of the developed techniques.
Turbo-encoded multiple-input multiple-output (MIMO) radio links have recently been proposed for the support of high-speed downlink packet access (HSDPA) in UMTS, where the re-use of spreading codes across the transmitter antennas results in high levels of interference. The state-of-the-art receiver chain for such a link incorporates space-time channel equalization, de-spreading, pre-whitening and finally a posteriori probability (APP) detection. A multi-stage partial parallel interference canceller (MS-PPIC) is considered as a low complexity alternative to the APP detector and its max-log variant. Nonlinear cancellation metrics are derived for the MS-PPIC and its performance is compared with the APP detector for flat and dispersive channels. It is shown that the MS-PPIC can provide similar performance compared to APP and, for low coding rates, superior performance compared to max-log-APP, at a substantially lower computational complexity.
Vehicle crash are considered to be events with high complexity from the mathematical points of view. The high experiment cost and huge time-consumption make the establishment of a mathematical model of vehicle crash which can simplify the analysis process in great demand. In this work, we present the application of LPV-ARMAX model to simulate the car-to-pole collision with different initial impact velocities. The parameters of the LPV-ARMAX are assumed to be functions of the initial impact velocities. Instead of establishing a set of LTI models for vehicle crashes with various impact velocities, the LPV-ARMAX model is comparatively simple and applicable to predict the responses of new collision situations different from those used for identification. The comparison between the predicted response and the real test data is conducted, which shows the high fidelity of the LPV-ARMAX model.
Recent results in output-feedback controller design make possible an efficient computation of static output-feedback controllers by solving a single-step LMI optimization problem. This new design strategy is based on a simple transformation of variables, and it has been applied in the field of vibration control of large structures with positive results. There are, however, some feasibility problems that can compromise the effectiveness and applicability of the new approach. In this paper, we present some relevant properties of the variable transformations that allow devising an effective procedure to deal with these feasibility issues. The proposed procedure is applied in designing a static velocity-feedback H ∞ controller for the seismic protection of a five-story building with excellent results.
This paper is devoted to the issue of observer-based adaptive sliding mode control of distributed delay systems with deterministic switching rules and stochastic jumping process, simultaneously, through a neural network approach. Firstly, relying on the designed Lebesgue observer, a sliding mode hyperplane in the integral form is put forward, on which a desired sliding mode dynamic system is derived. Secondly, in consideration of complexity of real transition rates information, a novel adaptive dynamic controller that fits to universal mode information is designed to ensure the existence of sliding motion in finite-time, especially for the case that the mode information is totally unknown. In addition, an observer-based neural compensator is developed to attenuate the effectiveness of unknown system nonlinearity. Thirdly, an average dwell-time approach is utilized to check the mean-square exponential stability of the obtained sliding mode dynamics, particularly, the proposed criteria conditions are successfully unified with the designed controller in the type of mode information. Finally, a practical example is provided to verify the validity of the proposed method.
This paper proposes a finite-time fuzzy adaptive quantized control scheme for a class of triangular structural nonlinear systems. Specifically, a smooth function with intermediate control law is introduced in the modified backstepping recursive process to eliminate the effect of quantization. The output constraints issue is solved by employing a barrier Lyapunov function. Then, a command filter is applied to avoid repeatedly differentiating virtual control signals and reduce the computational complexity. Moreover, the proposed method can guarantee that the tracking error converges to a small neighborhood of the origin in the finite time. Finally, the performance and the effectiveness of the proposed method are demonstrated via simulation results.
A robust observer design is proposed for Takagi‐Sugeno fuzzy neutral models with unknown inputs. The model consists of a mixed neutral and discrete delay, and the disturbances are imposed on both state and output signals. Delay‐dependent sufficient conditions for the design of an unknown input T‐S observer with time delays are given in terms of linear matrix inequalities. Some relaxations are introduced by using intermediate variables. A numerical example is given to illustrate the effectiveness of the given results.
An extended model predictive control algorithm is proposed to address constrained robust model predictive control. New upper bounds on arbitrarily long time intervals are derived by introducing two external parameters, which can relax the requirements for the increments of the Lyapunov function. The main merit of this new approach compared to other well-known techniques is the reduced conservativeness. The proposed method is proved to be effective for a class of uncertain fuzzy Markov jump systems with partially unknown transition probabilities. A single pendulum example is given to illustrate the advantages and effectiveness of the proposed controller design method.
No abstract is provided for this article.
In this paper, a recursive autoregressive model is presented to estimate modal parameters of the crash pulse recorded during a full-scale vehicle crash test. Those parameters can be further utilized to characterize a physical model, so called Maxwell model, which is composed of a serial spring-mass-damper model to simulate a vehicle crash event. Results produced by this viscoelastic system closely follow the reference vehicle's kinematics. Thanks to the application of nonlinear model's parameters estimated by RARMAX model it is possible to gain a closer insight into the nature of the vehicle collision. To evaluate the correctness of this methodology, the comparative analysis between the original vehicle's kinematics and behavior of a Maxwell model with the nonlinear parameters estimated by RARMAX model is presented.
This paper deals with adaptive output tracking of a transverse flux permanent magnet machine as a nonlinear system with unknown nonlinearities by utilizing Takagi-Sugeno type neuro-fuzzy networks. The technique of feedback linearization and H control are used to design an adaptive control law for compensating the unknown nonlinear parts, such the effect of cogging torque, as a disturbance on the rotor angle and angular velocity tracking performances. Finally, the capability of the proposed method is shown by the simulation results.
The tensile strength of asphaltic mixtures is an important parameter in designing the pavement materials and life assessment of the overlays. This parameter is often determined experimentally by using the indirect diametral tension (IDT) test or sometimes by employing the semi-circular bend (SCB) test. However, neither can provide accurate and true tensile strength values for practical and field situations. While the applied load to the overlay induced by traffic loading is along the compaction direction, there is a 90-degree angle difference between the direction of applied loading to the IDT and SCB samples and the compaction direction of the asphalt mixture manufactured inside the Marshall or Gyratory cylinders. Hence, in this research, a novel test specimen is proposed for the first time to measure the tensile strength of asphalt concrete materials in more realistic conditions. The proposed method utilizes a disc shape sample named Symmetric Disc Bend (SDB), which is a specimen loaded by a conventional three-point bending fixture. The tensile strength value obtained from the SDB specimen was observed to be significantly greater than the results obtained from the SCB and IDT methods for any given test conditions. The main reason for such discrepancy can be attributed to the compaction direction of the asphalt mixture and the applied loading direction to the samples. Accordingly, the tensile cracking resistance of the HMA mixture along the compaction direction is significantly higher than in the other directions. Therefore, the test data often determined from the IDT testing method can provide conservative predictions for the service life of real asphaltic pavements. In addition, due to the bending type load in the SDB testing procedure, the proposed method provides better consistency with the tensile cracking of real flexible pavements subjected to bending type loads applied from the vehicles. Some suitable SDB dimensions and loading span ranges were proposed for conducting the indirect tensile strength tests using the SDB specimen. In addition, the fracture patterns of specimens tested were simulated and predicted using the XFEM method, and stress distributions were reviewed.
