Current Issue : October - December Volume : 2017 Issue Number : 4 Articles : 5 Articles
In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation) for vehicle suspension\nsystems, this paper proposes an adaptive optimal control method for quarter-car active suspension systemby using the approximate\ndynamic programming approach (ADP). Online optimal control lawis obtained by using a single adaptive criticNNto approximate\nthe solution of the Hamilton-Jacobi-Bellman (HJB) equation. Stability of the closed-loop system is proved by Lyapunov theory.\nCompared with the classic linear quadratic regulator (LQR) approach, the proposed ADP-based adaptive optimal control\nmethod demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass) and unknown road\ndisplacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed\ncontrol strategy....
In this paper, we use a hybrid feedback control method to study lag synchronization\nin uncertain drive-response dynamical networks with a feature that the unknown\nsystem parameter exists in the node dynamics. We then design two hybrid feedback\ncontrol methods to achieve the lag synchronization including the linear and adaptive\nfeedback control. With the designed controllers and update laws for the system\nparameter in the node dynamics, we obtain two theorems on the lag synchronization\nbased on the LaSalle invariance principle. When the lag synchronization is achieved,\nwe identify the unknown system parameter. Finally, we provide two numerical\nexamples to verify the efficiency of the proposed control schemes....
For a quarter car with nonlinear active suspension in rough road, the problem of random modeling and control is considered.\nAccording to the relative motion principle, the influence of rough road can be seen as that force is disturbed by the noise and a\nrandom model is constructed. By an appropriate transform, the model is transformed into a lower triangular system, which can\nbe used as backstepping method. Then a controller is designed such that the mean square of the state converges to an arbitrarily\nsmall neighborhood of zero by tuning design parameters. The simulation results illustrate the effectiveness of the proposed scheme.\nTherefore, the active suspension system offers better riding comfort and vehicle handing to the passengers....
Due to the intermittent nature of wind, the wind power output tends to be inconsistent, and hence maximum power point tracking\n(MPPT) is usually employed to optimize the power extracted from the wind resource at a wide range of wind speeds. This paper\ndeals with the rotor speed control of a 2MW direct-driven permanent magnet synchronous generator (PMSG) to achieve MPPT.\nThe proportional-integral (PI), proportional-derivative (PD), and proportional-integral-derivative (PID) controllers have widely\nbeen employed in MPPT studies owing to their simple structure and simple design procedure. However, there are a number\nof shortcomings associated with these controllers; the trial-and-error design procedure used to determine the P, I, and D gains\npresents a possibility for poorly tuned controller gains, which reduces the accuracy and the dynamic performance of the entire\ncontrol system. Moreover, these controllers� linear nature, constricted operating range, and their sensitivity to changes in machine\nparameters make them ineffective when applied to nonlinear and uncertain systems. On the other hand, phase-lag compensators\nare associated with a design procedure that is well defined from fundamental principles as opposed to the aforementioned trialand-\nerror design procedure. This makes the latter controller type more accurate, although it is not well developed yet, and hence it\nis the focus of this paper. The simulation results demonstrated the effectiveness of the proposed MPPT controller....
The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking\ncontroller is one of the key technologies in intelligent vehicle research. This paper mainly designs a\nlateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control.\nFirstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle\nparameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled\nAuto-Regression and Moving-Average) model, a second-order control system model is built. Using\nforgetting factor recursive least square estimation (FFRLS), the system parameters are identified.\nFinally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path\ntracking control based on the vehicle model and the steering system model. Experimental simulation\nresults show that the proposed model and algorithm have the high real-time and robustness in path\ntracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation\ntracking control, and lays the foundation for the vertical and lateral coupling control....
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