Search

This paper describes an integrated speed and steering control driver model for vehicle–driver closed-loop simulation at high-speed maneuvering. In numerous research studies, the performance of vehicle control systems is validated via closed-loop computer simulations due to safety, cost, and repeatability issues. A driver model for the analysis of interactions between vehicle systems and drivers is a significant part of the validation. In particular, in developing a chassis control system, limit-driving characteristics of the actual driver, which mainly affects the performance of the system, has to be taken into consideration. Thus, the proposed driver model is developed to realize the actual driver's driving pattern. A speed control part of the proposed driver model consists of two modules, i.e., the real-time velocity planner and the motion stabilizer. The former plans the desired velocity profile from curvature information on a preview desired path in real time. The latter, i.e., the motion stabilizer, is developed to cope with losing maneuverability through deceleration because there is an obvious limitation to securing stability with velocity profile planning only. On the other hand, a steering control part of the proposed driver model utilizes the yaw-rate gain-based self-adaptation algorithm. An actual driver drives a vehicle without an exact understanding of system dynamics, and the self-adaptation algorithm is adequate for this characteristic accordingly. The proposed driver model has been validated by comparison with an expert driver's driving data, collected on the Korea International Circuit in Yeongam, Korea. [ABSTRACT FROM PUBLISHER]

The results of tests of payload oscillations, forced by linear control function which allows to minimize payload sway after acceleration phase and after overhead crane stopping are presented in this paper. The analysis of solution of this problem has been carried out. The algorithm of operation for real drive system which takes into account the possibilities of driving of an overhead crane is also presented. The impact of inaccuracies of measurement of the ropes length on minimizing a displacements of payload during the duty cycle is shown as well. The correctness of the method is confirmed by results both simulation and experimental tests. [ABSTRACT FROM AUTHOR]

The main objective in distributed sensor networks is to reach agreement or consensus on values acquired by the sensors. A common methodology to approach this problem is using the iterative and weighted linear combination of those values to which each sensor has access. Different methods to compute appropriate weights have been extensively studied, but the resulting iterative algorithm still requires many iterations to provide a fairly good estimate of the consensus value. In this paper, different accelerating consensus approaches based on adaptive and non-adaptive filtering techniques are studied and applied on the problem of acoustic source localization using the adaptive projected subgradient method. A comparative simulation study shows that the non-adaptive polynomial filters based on Newton's interpolating polynomials and semidefinite programming can provide more accelerated consensus and better estimation accuracy than adaptive filters evaluated using constrained affine projection algorithm or stochastic gradient algorithm provided that the network topology is known beforehand. [ABSTRACT FROM AUTHOR]

For the terminal phase guidance problem of the missile intercepting weaving maneuvering target, an adaptive internal model guidance laws in the three-dimensional (3-D) engagement space is proposed in this paper. The guidance law adopts the disturbance rejection theory by treating the target weaving maneuvering accelerations as external disturbance, which comprises of nominal part and adaptive part. The nominal part based on feedback linearization method ensures the whole guidance system stable and the adaptive part based on internal model principle is used to recover the disturbance signals on-line to reject the target maneuver asymptotically. The algorithm guarantees the whole guidance system with satisfying performance both in transient and steady state on the effect of target maneuver on guidance system. The stability analyses and theory proof are provided in this paper. At last, numerical simulations are carried out to illustrate the effectiveness of the proposed guidance law. [ABSTRACT FROM AUTHOR]

This paper presents the mathematical modeling of a multivariable process used in level control, under the assumptions that all pipes are filled with fluid and the inertial effects caused by flow variations, in case of small accelerations, are neglected. Because of the way the two tanks are interconnected and interact with each other, the resulting mathematical model is nonlinear. In the paper it is proposed a robust control algorithm for this plant developed based on H-infinity loop shaping procedure. The required computations and the study of the behavior of the system are done in the Matlab simulation environment. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for intelligent fuzzy logic (IFL) controller tuning via firefly algorithm (FA) and particle swarm optimization (PSO) for a semi-active (SA) suspension system using a magneto-rheological (MR) damper. The SA suspension system’s mathematical model is established based on quarter vehicles. The MR damper is used to change a conventional damper system to an intelligent damper. It contains a magnetic polarizable particle suspended in a liquid form. The Bouc–Wen model of a MR damper is used to determine the required damping force based on force–displacement and force–velocity characteristics. The performance of the IFL controller optimized by FA and PSO is investigated for control of a MR damper system. The gain scaling of the IFL controller is optimized using FA and PSO techniques in order to achieve the lowest mean square error (MSE) of the system response. The performance of the proposed controllers is then compared with an uncontrolled system in terms of body displacement, body acceleration, suspension deflection, and tire deflection. Two bump disturbance signals and sinusoidal signals are implemented into the system. The simulation results demonstrate that the PSO-tuned IFL exhibits an improvement in ride comfort and has the smallest MSE for acceleration analysis. In addition, the FA-tuned IFL has been proven better than IFL–PSO and uncontrolled systems for both road profile conditions in terms of displacement analysis. [ABSTRACT FROM AUTHOR]

Under complicated situations, such as the low slippery road surface and split-μ road surface, traction control system is the key issue to improve the performance of vehicle acceleration and stability. In this paper, a novel control strategy with engine controller and active pressure controller is presented. First and foremost, an ideal vehicle model is proposed for simulation; then a method for the calculation of optimal slip ratio is also brought. Finally, the scheme of control method with engine controller and active brake controller is presented. From the results of simulation and road tests, it can be concluded that the acceleration performance and stability of a vehicle equipped with traction control system (TCS) can be improved. [ABSTRACT FROM AUTHOR]