A new active variable stiffness suspension system using a nonlinear energy sink-based controller

This paper presents the active case of a variable stiffness suspension system. The central concept is based on a recently designed variable stiffness mechanism which consists of a horizontal control strut and a vertical strut. The horizontal strut is used to vary the load transfer ratio by actively controlling the location of the point of attachment of the vertical strut to the car body. The control algorithm, effected by a hydraulic actuator, uses the concept of nonlinear energy sink (NES) to effectively transfer the vibrational energy in the sprung mass to a control mass, thereby reducing the transfer of energy from road disturbance to the car body at a relatively lower cost compared to the traditional active suspension using the skyhook concept. The analyses and simulation results show that a better performance can be achieved by subjecting the point of attachment of a suspension system, to the chassis, to the influence of a horizontal NES system.     

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.     

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.     

Pole location control design of an active suspension system with uncertain parameters

This paper addresses the problem of robust control design for an active suspension quarter-car model by means of state feedback gains. Specifically, the design of controllers that assure robust pole location of the closed-loop system inside a circular region on the left-hand side of complex plane is investigated. Three sufficient conditions for the existence of a robust stabilizing state feedback gain are presented as linear matrix inequalities: (i) the quadratic stability based gain; (ii) a recently published condition that uses an augmented space and has been here modified to cope with the pole location specification; (iii) a condition that uses an extended number of equations and yields a parameter-dependent state feedback gain. Unlike other parameter-dependent strategies, neither extensive gridding nor approximations are needed. In the suspension model, the sprung mass, the damper coefficient and the spring constant are considered as uncertain parameters belonging to a known interval (polytope type uncertainty). It is shown that the parameter-dependent gain proposed allows one to impose the closed-loop system pole locations that in some situations cannot be obtained with constant feedback gains.     

Pole location control design of an active suspension system with uncertain parameters

This paper addresses the problem of robust control design for an active suspension quarter-car model by means of state feedback gains. Specifically, the design of controllers that assure robust pole location of the closed-loop system inside a circular region on the left-hand side of complex plane is investigated. Three sufficient conditions for the existence of a robust stabilizing state feedback gain are presented as linear matrix inequalities: (i) the quadratic stability based gain; (ii) a recently published condition that uses an augmented space and has been here modified to cope with the pole location specification; (iii) a condition that uses an extended number of equations and yields a parameter-dependent state feedback gain. Unlike other parameter-dependent strategies, neither extensive gridding nor approximations are needed. In the suspension model, the sprung mass, the damper coefficient and the spring constant are considered as uncertain parameters belonging to a known interval (polytope type uncertainty). It is shown that the parameter-dependent gain proposed allows one to impose the closed-loop system pole locations that in some situations cannot be obtained with constant feedback gains.     

Level and attitude control of the active suspension system with integral and derivative action

A 7-DOF full-car model with optimal active control suspension is utilized to evaluate the vehicle dynamic performances which are achieved through proposed controllers. The optimal controller, which includes the integral action for the suspension deflection, considerably improves the attitude control of a vehicle because the rolling and pitching motion in cornering and braking maneuvers are reduced, respectively. In the viewpoint of level control, the integral control acting on the suspension deflection results in the zero steady-state deflection in response to static body forces and ramp road input. The dynamic characteristics of the suspension control system are evaluated in terms of time domain and frequency domain. The simulations in the time domain demonstrate the advantages of the active suspension system obtained by penalizing the integral and derivative of suspension deflections and the derivative of roll and pitch angles in the performance index. The frequency characteristic curves obtained by simulations regarding integral action or derivative action show the increase of both ride comfort and road-holding performances by maximizing the use of suspension deflections. The potential of derivative control is shown by the performances of the car traveling over a bump and braking.     

Level and attitude control of the active suspension system with integral and derivative action

A 7-DOF full-car model with optimal active control suspension is utilized to evaluate the vehicle dynamic performances which are achieved through proposed controllers. The optimal controller, which includes the integral action for the suspension deflection, considerably improves the attitude control of a vehicle because the rolling and pitching motion in cornering and braking maneuvers are reduced, respectively. In the viewpoint of level control, the integral control acting on the suspension deflection results in the zero steady-state deflection in response to static body forces and ramp road input. The dynamic characteristics of the suspension control system are evaluated in terms of time domain and frequency domain. The simulations in the time domain demonstrate the advantages of the active suspension system obtained by penalizing the integral and derivative of suspension deflections and the derivative of roll and pitch angles in the performance index. The frequency characteristic curves obtained by simulations regarding integral action or derivative action show the increase of both ride comfort and road-holding performances by maximizing the use of suspension deflections. The potential of derivative control is shown by the performances of the car traveling over a bump and braking.     

Fuzzy and adaptive fuzzy control for the automobiles' active suspension system

Two typical criteria for good vehicle suspension performance are their ability to provide good road handling and increased passenger comfort. The main disturbance affecting these two criteria is terrain irregularities. Active suspension control systems reduce these undesirable effects by isolating car body motion from vibrations at the wheels. This paper describes fuzzy and adaptive fuzzy control (AFC) schemes for the automobile active suspension system (ASS). The design objective is to provide smooth vertical motion so as to achieve the road holding and riding comfort over a wide range of road profiles. The efficacy of the proposed control schemes is demonstrated via simulations. With respect to the optimal linear quadratic regulator (LQR), it is shown that superior results have been achieved by the AFC.     

车辆悬架减振系统基于AMESIM的仿真

针对在汽车行业中的核心部件悬架系统的特性及人们越来越关注的乘坐舒适性问题,利用现有的计算机技术实现了对车辆悬架系统的动理学分析及AMESIM建立1／4车体力学模型进行仿真,从平顺性和操作稳定性两方面对系统进行分析。     

Almost disturbance decoupling control of mimo nonlinear system subject to feedback linearization and a feedforward neural network: Application to half-car active suspension system

A novel tracking and almost disturbance decoupling problem of multi-input, multi-output (MIMO) nonlinear systems based on feedback linearization and a multi-layered feedforward neural network approach has been proposed. The feedback linearization and neural network controller guarantees exponentially global uniform ultimate bounded stability and almost disturbance decoupling performance without using any learning or adaptive algorithms. The new approach renders the system to be stable with the almost disturbance decoupling property at each step when selecting weights to enhance the performance if the proposed sufficient conditions are maintained. One example, which cannot be solved by the existing approach of the almost disturbance decoupling problem because it requires the sufficient conditions that the nonlinearities that multiply the disturbances satisfy structural triangular conditions, is proposed to exploit the fact that the tracking and the almost disturbance decoupling performances are easily achieved by the proposed approach. In order to demonstrate the practical applicability, a famous half-car active suspension system is investigated.     

主动悬架系统对汽车侧翻稳定性改善分析

针对被动悬架系统侧翻稳定性比较差的问题,提出采用主动悬架系统的方法进行改善。通过汽车侧倾运动状态分析,建立了被动悬架系统、主动悬架系统和控制系统模型。模拟分析得到主动悬架系统使得汽车在弯道行驶时的侧倾角有效值下降了92.8%,侧倾角加速度有效值下降了78.2%,侧翻因子有效值下降了92.6%。结果表明:利用主动悬架系统可以有效地降低汽车非直线行驶时的侧倾角以及侧倾角加速度,提高汽车的侧翻稳定性,是提高汽车非直线行驶状态下安全性的一个合理的解决方案。     

Fault detection and isolation for a nonlinear railway vehicle suspension with a Hybrid Extended Kalman filter

Fault detection is considered to be one way to improve system reliability and dependability for railway vehicles. The secondary lateral and anti-yaw dampers are the most critical parts in railway suspension systems. So far, the dampers have been modelled as linear components in the fault detection and isolation observer design. In this work, a Hybrid Extended Kalman filter is used to capture the nonlinear characteristics of the dampers. In order to detect and isolate faults, a nonlinear residual generator is developed, which can distinguish clearly between different types of faults. A lateral half train model serves as an example for the proposed technique. The results show that failures in the nonlinear suspension system can be detected and isolated accurately.     

基于扰动观测的智能驾驶主动抗扰纵向车速控制算法

为了减少智能驾驶车辆的纵向车速控制的时滞,提高主动抗扰性,提出一种基于扰动观测的纵向车速控制算法,并进行了实车验证。模型中,采用前馈控制模块,并提前输出控制量,来提高车速跟随的响应性;以主动抗扰控制(ADRC)模块作为反馈环节,采用扩张状态观测器(ESO)在线估计内外部扰动,并在控制端进行补偿,实现了对车速的精确闭环控制。在弯道、环岛等路况下进行了实车实验。结果表明:该算法可以在5 s内控制车速从怠速快速跟踪到目标车速,总体平均误差为0.17 km/h。因而,该算法较传统的比例积分微分(PID)有更好的响应性、控制精度和抗扰性。     

Development of a systematic and practical methodology for the design of vehicles semi-active suspension control system

In this paper, a novel systematic and practical methodology is presented for design of vehicle semi-active suspension systems. Typically, the semi-active control strategies developed to improve vehicle ride comfort and stability have a switching nature. This makes the design of the controlled suspension systems difficult and highly dependent on an extensive trial-and-error process. The proposed methodology maps the discontinuous control system model to a continuous linear region, where all the time and frequency design techniques, established in the conventional control system theory, can be applied. If the semi-active control system is designed to satisfy some ride and stability requirements, an inverse mapping offers the ultimate control law. At the end, the entire design procedure is summarised in six steps. The effectiveness of the proposed methodology in the design of a semi-active suspension system for a Cadillac SRX 2005 is demonstrated with road tests results. Real-time experiments confirm that the use of the newly developed systematic design method reduces the required time and effort in real industrial problems.