Lateral controller design for an unmanned vehicle via Kalman filtering

This paper proposes a lateral control system for an unmanned vehicle that is designed to improve the responsiveness of the system with the use of a PD control. The vehicle heading error can be stabilized, and the transient response characteristics can be improved using the proposed controller. A mathematical model of the vehicle dynamics using two degrees of freedom was developed for the controller design. The waypoint tracking method for autonomous navigation was tested with incorporation of the Point-to-Point algorithm with position and heading measurements received from GPS receivers via Kalman filtering. The performance of the designed controller was verified through experiments with a real vehicle.     

基于快速控制原型的ABS控制器开发

介绍了基于dSPACE实时系统的ABS控制器快速控制原型的设计方法。提出了运用MATLAB代码生成工具将快速控制原型控制算法移植到ABS控制器中的方法,解决了快速控制原型设计和真实控制器设计的衔接问题。试验结果表明,ABS控制器与快速控制原型具有同样的控制效果;快速控制原型方法使开发过程中的分析和验证工作更加快捷,缩短了ABS控制器的开发周期,提高了系统开发效率。     

汽车辅助驾驶系统上位控制方法研究

在建立两辆汽车组成的动力学系统模型基础上，应用线性二次型最优理论及时间－能量最优理论研究了汽车辅助驾驶系统上位控制方法。针对现有方法存在的问题，将LQ法及时间－能量最优法相结合，提出了一种改进的上位系统控制方法。理论分析及仿真试验结果表明，新的控制方法在满足安全性和舒适性要求的同时，显著降低了系统的响应时间。     

Integration of vehicle yaw stabilisation and rollover prevention through nonlinear hierarchical control allocation

This work presents an approach to rollover prevention that takes advantage of the modular structure and optimisation properties of the control allocation paradigm. It eliminates the need for a stabilising roll controller by introducing rollover prevention as a constraint on the control allocation problem. The major advantage of this approach is the control authority margin that remains with a high-level controller even during interventions for rollover prevention. In this work, the high-level control is assigned to a yaw stabilising controller. It could be replaced by any other controller. The constraint for rollover prevention could be replaced by or extended to different control objectives. This work uses differential braking for actuation. The use of additional or different actuators is possible. The developed control algorithm is computationally efficient and suitable for low-cost automotive electronic control units. The predictive design of the rollover prevention constraint does not require any sensor equipment in addition to the yaw controller. The method is validated using an industrial multi-body vehicle simulation environment.     

Identification of nonlinear systems using modified particle swarm optimisation: a hydraulic suspension system

This paper presents a novel modified particle swarm optimisation (MPSO) algorithm to identify nonlinear systems. The case of study is a hydraulic suspension system with a complicated nonlinear model. One of the main goals of system identification is to design a model-based controller such as a nonlinear controller using the feedback linearisation. Once the model is identified, the found parameters may be used to design or tune the controller. We introduce a novel mutation mechanism to enhance the global search ability and increase the convergence speed. The MPSO is used to find the optimum values of parameters by minimising the fitness function. The performance of MPSO is compared with genetic algorithm and alternative particle swarm optimisation algorithms in parameter identification. The presented comparisons confirm the superiority of MPSO algorithm in terms of the convergence speed and the accuracy without the premature convergence problem. Furthermore, MPSO is improved to detect any changes of system parameters, which can be used for designing an adaptive controller. Simulation results show the success of the proposed algorithm in tracking time-varying parameters.     

Automatic guidance control of an articulated all-wheel-steered vehicle

This paper presents automatic guidance control of a single-articulated all-wheel-steered vehicle being developed by the Korea Railroad Research Institute. The vehicle has an independent drive motor on each wheel except for the front axle. The guidance controller is designed so that the vehicle follows the given reference path within permissible lateral deviations. We use a three-input/three-output linearised model derived from the nonlinear dynamic model of the vehicle. For the purpose of simplifying the controller and making it tunable, we consider a decentralised control configuration. We first design a second-order decoupling compensator for the two-input/two-output system that is strongly coupled and then design a first-order controller for each decoupled feedback loop by using the characteristic ratio assignment method. The simulation results for the nonlinear dynamic model indicate that the proposed control configuration successfully achieves the design objectives.     

混合动力汽车动力总成试验台研究

基于混合动力汽车有串联、并联和混联等多种结构形式的特点,提出以模块化设计思想来搭建混合动力汽车动力总成试验台的方法,从而达到了在比较短的时间内、以尽量小的改动适应不同混合动力汽车动力总成结构形式组合需要的目标。根据研究需要,首先完成了混合动力汽车动力总成试验台并联形式的建设,并利用该试验台对所研制的混合动力城市客车多能源动力总成控制器进行了初步调试,验证了该控制器的软硬件设计和并联电动助力型控制策略。同时,所完成的发动机台架试验和电机台架试验也充分证明了试验台模块化设计思想的可行性和有效性。     

Sensorless adaptive speed control of a permanent-magnet dc motor for anti-lock brake systems

An adaptive control algorithm was developed for the sensorless speed control of a permanent-magnet DC motor directly connected to the hydraulic pump of an antilock brake system. Due to the severe cost and reliability constraints of the application, the motor speed was controlled by a very simple on-off switching method, in which the only measurement required is the voltage across the control switch. The motor speed was calculated solely from the back-EMF voltage during the period of the control cycle when the switching controller is in the switch-off mode. The stability of the developed adaptiveswitching control algorithm was proven mathematically and confirmed experimentally in several vehicle tests over a wide range of target speeds and pump-load conditions. The accuracy and the response time of the controller can easily be tuned by adjusting a single tuning parameter. The switching frequency of the controller can also easily be tuned by adjusting the over-and undershoot thresholds independently from the accuracy of the speed-tracking control.     

Design of robust-stable and quadratic finite-horizon optimal controllers with low trajectory sensitivity for uncertain active suspension systems

This paper presents a design method for designing the robust-stable and quadratic-finite-horizon-optimal controllers of uncertain active suspension systems. The method integrates a robust stabilisability condition, the orthogonal functions approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA). Using the integrative computational method, a robust-stable and quadratic-finite-horizon-optimal controller with low-trajectory sensitivity can be obtained such that (i) the active suspension system with elemental parametric uncertainties is stabilised and (ii) a quadratic-finite-horizon-integral performance index including a quadratic trajectory sensitivity term for the nominal active suspension system is minimised. The robust stabilisability condition is proposed in terms of linear matrix inequalities (LMIs). Based on the OFA, an algebraic algorithm only involving the algebraic computation is derived for solving the nominal active suspension feedback dynamic equations. By using the OFA and the LMI-based robust stabilisability condition, the dynamic optimisation problem for the robust-stable and quadratic-finite-horizon-optimal controller design of the linear uncertain active suspension system is transformed into a static-constrained-optimisation problem represented by the algebraic equations with constraint of LMI-based robust stabilisability condition; thus greatly simplifies the design problem. Then, for the static-constrained-optimisation problem, the HTGA is employed to find the robust-stable and quadratic-finite-horizon-optimal controllers of the linear uncertain active suspension systems. A design example is given to demonstrate the applicability of the proposed integrative computational approach.     

Design and Evaluation of Robust Cooperative Adaptive Cruise Control Systems in Parameter Space

This paper is on the design of cooperative adaptive cruise control systems for automated driving of platoons of vehicles in the longitudinal direction. Longitudinal models of vehicles with simple dynamics, an uncertain first order time constant and vehicle to vehicle communication with a communication delay are used in the vehicle modeling. A robust parameter space approach is developed and applied to the design of the cooperative adaptive cruise control system. D-stability is chosen as the robust performance goal and the feedback PD controller is designed in controller parameter space to achieve this D-stability goal for a range of possible longitudinal dynamics time constants and different values of time gap. Preceding vehicle acceleration is sent to the ego vehicle using vehicle to vehicle communication and a feedforward controller is used in this inter-vehicle loop to improve performance. Simulation results of an eight vehicle platoon of heterogeneous vehicles are presented and evaluated to demonstrate the efficiency of the proposed design method. Also, the proposed method is compared with a benchmark controller and the feedback only controller. Time gap regulation and string stability are used to assess performance and the effect of the vehicle to vehicle communication frequency on control system performance is also investigated.     

Handling stability improvement through robust active front steering and active differential control

The design of the integrated active front steering and active differential control for handling improvement of road vehicles is undertaken. The controller design algorithm is based on the solution of a set of linear matrix inequalities that guarantee robustness against a number of vehicle parameters such as speed, cornering and braking stiffnesses. Vehicle plane dynamics are first expressed in the generic linear parameter-varying form, where the above-stated parameters are treated as interval uncertainties. Then, static-state feedback controllers ensuring robust performance against changing road conditions are designed. In a first series of simulations, the performance of the integrated controller is evaluated for a fishhook manoeuvre for different values of road adhesion coefficient. Then, the controller is tested for an emergency braking manoeuvre executed on a split-μ road. In all cases, it is shown that static-state feedback controllers designed by the proposed method can achieve remarkable road handling performance compared with uncontrolled vehicles.     

Linear matrix inequality based control of vehicle active suspension system

Linear matrix inequality (LMI) methods, novel techniques in solving optimisation problems, were introduced as a unified approach for vehicle's active suspension system controller design. LMI methods were used to provide improved and computationally efficient controller design techniques. The active suspension problem was formulated as a standard convex optimisation problem involving LMI constraints that can be solved efficiently using recently developed interior point optimisation methods. An LMI based controller for a vehicle system was developed. The controller design process involved setting up an optimisation problem with matrix inequality constraints. These LMI constraints were derived for a vehicle suspension system. The resulting LMI controller was then tested on a quarter-car model using computer simulations. The LMI controller results were compared with an optimal PID controller design solution. The LMI controller was further tested by incorporating a nonlinear term in the vehicle's suspension model; the LMI's controller degraded response was enhanced by using gain-scheduling techniques. The LMI controller with gain-scheduling gave good results in spite of the unmodelled dynamics in the suspension system, which was triggered by large deflections due to off-road driving.     

Coupled vibration analysis of Maglev vehicle-guideway while standing still or moving at low speeds

Dynamic instability, that is, resonance, may occur on an electromagnetic suspension-type Maglev that runs over the elevated guideway, particularly at very low speeds, due to the flexibility of the guideway. An analysis of the dynamic interaction between the vehicle and guideway is required at the design stage to investigate such instability, setting slender guideway in design direction for reducing construction costs. In addition, it is essential to design an effective control algorithm to solve the problem of instability. In this article, a more detailed model for the dynamic interaction of vehicle/guideway is proposed. The proposed model incorporates a 3D full vehicle model based on virtual prototyping, flexible guideway by a modal superposition method and levitation electromagnets including feedback controller into an integrated model. By applying the proposed model to an urban Maglev vehicle newly developed for commercial application, an analysis of the instability phenomenon and an investigation of air gap control performance are carried out through a simulation.     

混合动力客车多能源动力总成控制器研制与试验

介绍了某混合动力客车多能源动力总成控制器样品的主要设计原理和所采取的控制策略，以及为验证控制器设计而搭建的试验台的结构原理和控制器的台架试验情况。     

Adaptive feedforward control of a steer-by-wire system by online parameter estimator

The tracking control of the steer-by-wire (SBW) system to achevie desired steering motion is the core issue for the design of algorithm. Most of model-based tracking control assumed the constant parameters without the consideration of dynamic characteristics. The external disturbances and model nonlinearities can bring uncertainties of the system parameters. To reduce the influence of parameter uncertainties, an online estimator by output error identification method is proposed to estimate the dynamic parameters of a SBW system. Meanwhile, the parameter gradient projection method is applied to eliminate the parameter drift, while a full order state observer is developed to weaken the effects of noise disturbance during the parameter identification. Since the sensitivity of parameter uncertainties for the feedforward control, the online estimator is incorporated into the control model and improve the controlled robustness. The proposed adaptive feedforward controller is conducted by the real-time experiments to show the tracking performance.     

Robust yaw stability control for electric vehicles based on active front steering control through a steer-by-wire system

A robust yaw stability control design based on active front steering control is proposed for in-wheel-motored electric vehicles with a Steer-by-Wire (SbW) system. The proposed control system consists of an inner-loop controller (referred to in this paper as the steering angle-disturbance observer (SA-DOB), which rejects an input steering disturbance by feeding a compensation steering angle) and an outer-loop tracking controller (i.e., a PI-type tracking controller) to achieve control performance and stability. Because the model uncertainties, which include unmodeled high frequency dynamics and parameter variations, occur in a wide range of driving situations, a robust control design method is applied to the control system to simultaneously guarantee robust stability and robust performance of the control system. The proposed control algorithm was implemented in a CaSim model, which was designed to describe actual in-wheel-motored electric vehicles. The control performances of the proposed yaw stability control system are verified through computer simulations and experimental results using an experimental electric vehicle.     

ABS控制器参数的优化设计

在基于逻辑门限的ABS控制策略的基础上，建立了汽车ABS系统的仿真模型；提出了使用遗传算法优化设计ABS控制器的参数，并利用遗传算法和数字仿真相结合的手段，获得了参数设计结果。通过对优化设计参数和原设计参数运行结果的比较，证明基于遗传算法的优化设计方法有效，设计结果可供工程实践参考。     

Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.     

基于遗传算法的公路纵断面优化设计方法

纵断面优化设计是公路优化设计中一个重要的组成部分,遗传算法是一种高效的全局寻优算法。介绍了用遗传算法实现纵断面优化设计的具体方法步骤,并编制出了计算机应用程序。经输入公路原始数据进行实例计算,取得了令人满意的结果,证明了遗传算法在纵断面优化设计中的可行性及全局寻优的性能。     

Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.