汽车转向防抱死制动控制系统研究

为了研究解决车辆转向过程中防抱死制动稳定性问题,设计了一种由执行级、协调级组成的分层控制系统,在执行级,设计了基于遗传算法的汽车ABS最优滑模控制器;设计了基于遗传算法的汽车转向滑模控制器。在协调级,针对制动和转向两个子系统提出协调控制方案,给出具体协调策略。用仿真结果验证所设计控制算法的稳定性和有效性。     

Robust adaptive control of a bio-inspired robot manipulator using bat algorithm

This paper proposes a novel adaptive fractional order PID sliding mode controller (AFOPIDSMC) using a Bat algorithm to control of a Caterpillar robot manipulator. A fractional order PID (FOPID) control is applied to improve both trajectory tracking and robustness. Sliding mode controller (SMC) is one of the control methods which provides high robustness and low tracking error. Using hybridization, a new combined control law is proposed for chattering reduction by means of FOPID controller and high trajectory tracking through using SMC. Then, an adaptive controller design motivated from the SMC is applied for updating FOPID parameters. A metaheuristic approach, the Bat search algorithm based on the echolocation behavior of bats is applied for optimal design of the Caterpillar robot in order to tune the parameter AFOPIDSMC controllers (BA-AFOPIDSMC). To study the effectiveness of Bat algorithm, its performance is compared with five other controllers such as PID, FOPID, SMC, AFOPIDSMC and PSO-AFOPIDSMC. The stability of the AFOPIDSMC controller is proved by Lyapunov theory. Numerical simulation results completely indicate the advantage of BA-AFOPIDSMC for trajectory tracking and chattering reduction.     

Vehicle adaptive cruise control design with optimal switching between throttle and brake

For vehicle adaptive cruise control(ACC) systems,the switching performance between throttle and brake determines the driving comfort,fuel consumption and service lives of vehicle mechanical components.In this paper,an ACC algorithm with the optimal switching control between throttle and brake is designed in model predictive control (MPC) framework.By introducing the binary integer variables,the dynamics of throttle and brake are integrated in one model expression for the controller design.Then the ACC algorithm is designed to satisfy not only safe car following,but also the optimal switching between throttle and brake,which leads to an online mixed integer quadratic programming solved by the nested two-loop method.The simulation results show that the proposed ACC algorithm meets the requirements of safe car following,outperforms the traditional algorithms by performing smoother responses,reducing the switching times between throttle and brake,and therefore improves driving comfort and fuel efficiency significantly.     

A nonlinear control scheme for imprecisely known processes using the sliding mode and neural fuzzy techniques

This article considers the regulation control of nonlinear chemical processes whose dynamics are imprecisely known. A nonlinear control scheme that incorporates a sliding mode controller (SMC) and a neural fuzzy strategy is proposed to deal with this kind of processes. The sliding mode controller designed on the base of a previously known process model is implemented to keep system’s trajectory around the desired manifold. For extra and/or unknown dynamics that cannot be captured before the SMC design stage, an intelligent scheme of utilizing a neural fuzzy strategy is then used to provide an adaptive ability to accommodate the perturbation, which therefore is able to force the system output back to and maintain in the desired set point. The effectiveness and applicability of the proposed scheme are demonstrated through the control of a continuous stirred tank reactor with existing simultaneously the unmodeled side reactions, measuring error, and extra matched and unmatched disturbances. The potential use of a sliding observer along with the proposed scheme is also investigated in the work. Extensive simulation results reveal that the incorporation of the model-based SMC and the intelligent neural fuzzy technique appears to be an effective and promising approach to the nonlinear control of chemical processes whose dynamics are imprecisely known.     

Yaw Moment Control Strategy for Four Wheel Side Driven EV

When four wheel side driven EV travals in steering or changes lanes in high speed, the vehicle is easy to side-slip or flick due to the difference of wheel hub motor and a direct effect of vehicle nonlinear factors on vehicle yaw motion, which would affect vehicle handling and stability seriously. To solve this problem, a joint control strategy, combined with the linear programming algorithm and improved sliding mode algorithm, which combines the exponential reaching law and saturation function was proposed. Firstly, the vehicle dynamics model and the reference model according with the structure and driving characteristics of four wheel side driven EV were set up. Then, introduced the basic method of the improved sliding mode variable structure control and complete the sliding mode variable structure controller design basic on vehicle sideslip angle and yaw velocity.The controller accomplish optimal allocation of vehicle braking force through a linear programming algorithm, according to yaw moment produced by the vehicle motion state. Single lane driving simulation results show that the proposed control strategy can not only control vehicle sideslip angle and yaw velocity well, but also accomplish good controlling of the vehicle yaw moment, so as to significantly improve the handling and stability of vehicle.     

Second-order terminal sliding mode control for hypersonic vehicle in cruising flight with sliding mode disturbance observer

This paper focuses on the design of nonlinear robust controller and disturbance observer for the longitudinal dynamics of a hypersonic vehicle (HSV) in the presence of parameter uncertainties and external disturbances. First, by combining terminal sliding mode control (TSMC) and second-order sliding mode control (SOSMC) approach, the secondorder terminal sliding control (2TSMC) is proposed for the velocity and altitude tracking control of the HSV. The 2TSMC possesses the merits of both TSMC and SOSMC, which can provide fast convergence, continuous control law and hightracking precision. Then, in order to increase the robustness of the control system and improve the control performance, the sliding mode disturbance observer (SMDO) is presented. The closed-loop stability is analyzed using the Lyapunov technique. Finally, simulation results illustrate the effectiveness of the proposed method, as well as the improved overall performance over the conventional sliding mode control (SMC).     

Adaptive Chattering Free Neural Network Based Sliding Mode Control for Trajectory Tracking of Redundant Parallel Manipulators

In this paper, an adaptive chattering free neural network‐based sliding mode control (ACFN‐SMC) method is proposed for tracking trajectories of redundant parallel manipulators. ACFN‐SMC combines adaptive chattering free radial basis function neural networks (RBFN), sliding mode control with online updating the robust term parameters, and a nonlinear compensation item for reducing tracking errors. The stability of the closed‐loop system with modeling uncertainties, frictional uncertainties, and external disturbances is ensured by using the Lyapunov method. The proposed controller has a simple structure and little computation time while securing dynamic performance with expected quality in tracking trajectories of redundant parallel manipulators. In addition, the ACFN‐SMC strategy does not need to know the upper bound of any uncertainties. From the simulation results, it is evident that the proposed control strategy not only has significantly higher robustness capability for uncertainties but also can achieve better chattering elimination when compared with those using existing intelligent control schemes.     

GBF-CMAC和滑模控制的柔性结构系统控制

针对一类不确定系统的跟踪控制,设计了一种将GBF-CMAC（cerebellar model articulation controller with Gauss basis function）与滑模控制相结合的控制系统。利用符号距离和分层结构减少了神经网络所需存储器的数量,并提出了一种神经网络参数的自适应学习律。将设计的控制器用于含有不确定性和欠驱动结构的高阶柔性直线结构系统的跟踪控制,并与一般滑模控制和积分滑模控制进行了比较。实验结果表明,所设计的控制器不仅具有较好的鲁棒性,而且改善了滑模控制存在的抖振问题。同时通过调整神经网络的参数对抖振进行控制,实现了抖振和跟踪性能之间的最优选择。     

Design and evaluation of a model predictive vehicle control algorithm for automated driving using a vehicle traffic simulator

This paper describes the design and evaluation of a model predictive control algorithm for automated driving on a motorway using a vehicle traffic simulator. For the development of a highly automated driving control algorithm, motion planning is necessary to satisfy driving condition in various road traffic situations. There are two key issues in motion planning of automated driving vehicles. One of the key issues is how to handle potentially dangerous situations that could occur in order to guarantee the safety of vehicles. The second key issue is how to guarantee the disturbance rejection of the controller under model uncertainties and external disturbances. To improve safety with respect to the future behaviors of subject vehicles, not the current states but rather the predicted behaviors of surrounding vehicles should be considered. The desired driving mode and a safe driving envelope are determined based on the probabilistic prediction of surrounding vehicles behaviors over a finite prediction horizon. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope during a finite prediction horizon, a motion planning controller is designed based on an model predictive control (MPC) approach. The developed control algorithm has been successfully implemented on a vehicle electronic control unit (ECU). The proposed control algorithm has been evaluated on a real-time vehicle traffic simulator. The throttle, brake, and steering control inputs and the controlled vehicle behavior have been compared to those of manual driving.     

Intelligent tracking control of a dual‐arm wheeled mobile manipulator with dynamic uncertainties

This paper presents an intelligent control approach that incorporates sliding mode control (SMC) and fuzzy neural network (FNN) into the implementation of back‐stepping control for a path tracking problem of a dual‐arm wheeled mobile manipulator subject to dynamic uncertainties and nonholonomic constraints. By using the back‐stepping technique, the system equations are reformulated into two levels: the kinematic level and the dynamic level. A sliding manifold is constructed by considering the disturbance free kinematic level equations only. With all the system uncertainties concentrated in the dynamic level, an FNN controller associated with a switching type of control law is employed to enforce sliding mode on the prescribed manifold. All parameter adjustment rules for the proposed controller are derived from the Lyapunov theory such that uniform ultimate boundedness for both the tracking error and the FNN weighting updates is ensured. A simulation study, which compares different control design approaches, is included to illustrate the promise of the proposed SMC–FNN method. Copyright © 2012 John Wiley & Sons, Ltd.     

Fuzzy sliding mode control for a robot manipulator

This work presents the design of a robust control system using a sliding mode controller that incorporates a fuzzy control scheme. The presented control law superposes a sliding mode controller and a fuzzy logic controller. A fuzzy tuning scheme is employed to improve the performance of the control system. The proposed fuzzy sliding mode control (FSMC) scheme utilizes the complementary cooperation of the traditional sliding mode control (SMC) and the fuzzy logic control (FLC). In other words, the proposed control scheme has the advantages which it can guarantee the stability in the sense of Lyapunov function theory and can ameliorate the tracking errors, compared with the FLC and SMC, respectively. Simulation results for the trajectory tracking control of a two-link robot manipulator are presented to show the feasibility and robustness of the proposed control scheme. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Vehicle longitudinal brake control using variable parameter sliding control

A modified sliding control with variable control parameter was introduced to reduce the large change of pressure feedback in the hydraulic brake control process of automated highway vehicles. An average decay function was used to smooth both high and low frequency oscillations of the desired diaphragm force and output force in the vacuum booster to remedy the oscillations generated by using the pushrod force as the end-brake control. Simulation results indicate that the variable parameter sliding control significantly reduces the speed and space tracking errors in the large brake processes, and the errors experienced during these processes are dominated by the large brake pressure lag rather than the switching delay time between throttle and brake.     

Improving asynchronous motor speed and flux loop control by using hybrid fuzzy-SMC controllers

This paper presents a new method combining sliding mode control (SMC) and fuzzy logic control (FLC) to enhance the robustness and performance for a class of non-linear control systems. This fuzzy sliding mode control (FSMC) is developed for application in the area for controlling the speed and flux loops of asynchronous motors. The proposed control law can solve those problems associated with the conventional control by sliding mode control, such as high current, flux and torque chattering, variable switching frequency and variation of parameters, in which a robust fuzzy logic controller replaces the discontinuous part of the classical sliding mode control law. Simulation results of the proposed FSMC technique on the speed and flux rotor controllers present good dynamic and steady-state performances compared to the classical SMC in terms of reduction of the torque chattering, quick dynamic torque response and robustness to disturbance and variation of parameters.     

无级变速汽车的自适应模糊控制研究

为提高无级变速汽车控制系统对外界负荷扰动和各种运行工况的自适应能力,本文在简单的无级变速系统模型的基础上,设计了无级变速汽车的自适应模糊控制系统.所设计的自适应模糊控制系统由参数自调节油门模糊控制器和混合型模糊-PID的无级变速器速比和制动控制器构成,该控制系统只与汽车的瞬时运行状态有关而与汽车的参数无关,因此它对不确定的汽车参数和外界负荷的扰动具有良好的鲁棒性.仿真结果表明所设计的模糊控制系统具有良好的自适应能力.     

Aeronautical and space vehicle control in dynamic sliding manifolds

Multiple loop multiple time scale sliding mode control technique based on dynamic sliding manifold is developed and applied to aeronautical and space vehicle control. Minimum and non-minimum phase output tracking problems for aeronautical and space vehicles are addressed in dynamic sliding manifold. Numerical examples of the flight controller design for controlling minimum and non-minimum phase manoeuvres of an F-16 jet fighter are presented. An example of an attitude controller design for the X-33 technology demonstration reusable launch vehicle using sliding mode control based on dynamic sliding manifold is also considered. Numerical simulations illustrate the effectiveness of the dynamic sliding manifold technique.     

车载惯性稳定平台的神经网络滑模控制

三轴车载惯性稳定平台为复杂的MIMO非线性系统,针对其在不确定扰动下的伺服控制问题,本文设计了一种神经网络反演滑模控制器(NNBSMC).首先,选用反演法对其解耦,同时引入滑模控制律增加系统的抗干扰性;其次针对框架间的非线性摩擦力与系统耦合选用RBF神经网络作为扰动估计器,以便实时估计与补偿;然后采用前向增稳通道应对建模参数不精确以保证系统的稳定性.最后,利用Lyapunov定理分析了闭环系统的稳定性,在伺服控制与姿态锁定的仿真实验中分别与双环PID、滑模控制和反演滑模控制作对比,结果验证了提出的控制算法的有效性和鲁棒性.     

Fuzzy tracking control design for hypersonic vehicles via T-S model

The main focus of this paper is on designing a T-S fuzzy controller for the hypersonic vehicle. The longitudinal dynamics of the vehicle are studied using time-scale decomposition to reduce the complexity of T-S modeling. The dynamic inversion with PI control technique is applied for the slow dynamics to derive the flight path angle command and throttle setting by taking the pilot altitude and velocity command as its inputs. The T-S fuzzy controller is designed for the fast dynamics to derive the elevator d...     

Neural network-based sliding mode control of electronic throttle

A neural network-based sliding mode controller for an electronic throttle of an internal combustion engine is proposed. Electronic throttle is modeled as a linear system with uncertainties and affected by disturbances depending on the states of the system. The disturbances, consisting of an unknown friction and a torque caused by the dual spring mechanism inside the mechanical part of the throttle, are estimated by a neural network whose parameters are adapted on-line. The sliding mode controller and the parameters adaptation scheme are derived in order to achieve a tracking of a smooth reference signal, while preserving boundedness of all signals in the closed-loop system. Experimental results are presented which demonstrate the efficiency and robustness of the proposed control scheme.     

Novel smooth sliding mode attitude control design for constrained re-entry vehicle based on disturbance observer

This paper investigates the attitude tracking control system design for reusable launch vehicle (RLV) in re-entry phase with input constraint, model uncertainty and external disturbance. The novel control scheme is designed via combining the advantages of the robust property of sliding mode control (SMC), the compensation ability of disturbance observer (DOB) and the systematic design procedure of backstepping technique. By applying DOB technique to estimate the lumped uncertainty, there is no need to choose the switch gain larger than the bound of uncertainty. Through designing the exponential form sliding surface and smooth sliding mode controller, the chattering and discontinuous problem inherent in the traditional SMC is alleviated. An additional system is constructed to handle input constraint. Based on Lyapunov theory, the asymptotic stability of the closed-loop system is proven. At last, compared simulations are presented to verify the effectiveness of the proposed control approach.     

Design of uncertain multi-input systems with state delay and input deadzone nonlinearity via sliding mode control

The problem of robust stabilization of a class of uncertain multi-input time-delayed systems with deadzone nonlinearity in the actuator is considered. To achieve a stable uncertain multi-input system, sliding mode control (SMC) is adopted in the controller design. The proposed controller guarantees the global reaching condition of the sliding mode in the uncertain multi-input system. In the sliding mode, the investigated time-delayed systems with deadzone nonlinearity still possess the insensitivity to the uncertainties and/or disturbances, which can be seen in the systems with linear inputs. In addition, the proposed controller can work effectively for systems no matter whether sector nonlinearity and/or deadzone exists in the actuator or not. However, such property cannot be obtained by the controller design through traditional SMC for the systems without input nonlinearity. Besides, the traditional SMC controller might produce limit cycles once the system contains deadzone in the input. Furthermore, the presented controller ensures the system trajectories globally exponentially converged in the sliding mode. Finally, two examples are illustrated to demonstrate the effectiveness of the proposed sliding mode controller.