Design of nonlinear controllers for active vehicle suspension with state constraints

Design of active vehicle suspension has tradeoffs between three main performance metrics (passenger comfort, suspension deflection and road holding ability). It has been known that each performance can be achieved by H _∞ controller and they can be gathered by LPV (Linear Parameter Varying) method. However, because the suspension deflection limit was not explicitly considered, this limit may be exceeded. In this paper, the authors propose a “reference shaping“ based method in order to improve the control performance. In this approach, a “virtual reference” signal is imposed to the system such that the suspension deflection is kept small. The effectiveness of the approach is examined by numerical simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Subspace identification of MIMO LPV systems using a periodic scheduling sequence

A novel subspace identification method is presented which is able to reconstruct the deterministic part of a multivariable state-space LPV system with affine parameter dependence, in the presence of process and output noise. It is assumed that the identification data is generated with the scheduling variable varying periodically during the course of the identification experiment. This allows to use methods from LTI subspace identification to determine the column space of the time-varying observability matrices. It is shown that the crucial step in determining the original LPV system is to ensure the obtained observability matrices are defined with respect to the same state basis. Once the LPV model has been identified, it is valid for other nonperiodic scheduling sequences as well.     

A delay‐dependent bounded real lemma for singular LPV systems with time‐variant delay

This paper is concerned with establishing a delay‐dependent bounded real lemma (BRL) for singular linear parameter‐varying (LPV) systems with time‐variant delay. In terms of linear matrix inequality, a delay‐dependent BRL is presented to ensure singular time‐delay LPV systems to be admissible and satisfy a prescribed H_∞ performance level. The BRL is obtained based on the construction of a parameter‐dependent Lyapunov–Krasovskii functional. The effectiveness of the proposed approach is shown by several numerical examples. Copyright © 2011 John Wiley & Sons, Ltd.     

Design of a two‐level controller for an active suspension system

The paper focuses on a control design for a vehicle suspension system in which a balance between different performance demands is achieved. The starting point of the control design is a full–car model which contains nonlinear components, i.e. the dynamics of the dampers and springs and nonlinear actuator dynamics. In order to handle the high complexity of the problem this paper proposes the design of a two‐level controller of an active suspension system. The required control force is computed by applying a high‐level controller, which is designed using a linear parameter varying (LPV) method. For the control design the model is augmented with weighting functions specified by the performance demands and the uncertainty assumptions. The actuator generating the necessary control force is modelled as a nonlinear system for which a low‐level force‐tracking controller is designed. To obtain the low‐level controller a backstepping method is proposed. As an alternative solution a feedback linearization method is also presented. The operation of the controller is illustrated through simulation examples. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Robust stabilizer design for linear time-varying internal model based output regulation and its application to an electrohydraulic system

This paper focuses on the design of a low order robust stabilizer for the tracking/disturbance rejection problem based on the internal model principle in the time-varying setting and its application to the hydraulic pressure tracking with varying frequency. The problem of this kind known as output regulation generally consists of two major parts: internal model unit construction and stabilizer design. While the construction of the time-varying internal model unit is non-trivial by itself and a very recent research outcome enables its synthesis for a class of linear time-varying systems, the effective stabilization of the augmented system (internal model unit and plant) for practical applications remains a challenge. This is due to the need to stabilize the high order time-varying augmented system using a low order stabilizer in a robust fashion and with desirable transient performance. While directly applying the stabilization approaches for a general LTV system will result in a high order stabilizer, a new method is proposed in this paper that overcomes this bottleneck by taking advantage of the unique structure of the internal model based control system. Instead of using a dynamic stabilizer with high order, this approach uses a sequence of time-varying gains that are directly injected into the internal model unit. A critical issue addressed is how to avoid the non-convex optimization associated with the time-varying gain synthesis and then convert the stabilizer design into a series of Linear Matrix Inequalities (LMIs). The proposed control approach is then demonstrated on an electrohydraulic system.     

风力机的线性变参数主动容错控制

针对风力机具有非线性和参数的不确定性的特征,提出了基于线性变参数(linear parameter varying,LPV)增益调度的风力机主动容错控制方法,降低故障对机组动态特性的影响.基于LPV凸分解方法,将风力机的非线性模型转化为具有凸多面体结构LPV模型,利用线性矩阵不等式(linear matrix inequalities,LMIs)技术对凸多面体各个顶点分别设计满足性能要求的控制器,再利用各顶点设计的反馈控制器得到具有凸多面体结构LPV容错控制器.仿真结果表明,LPV增益调度技术可以成功地应用于风力机系统的容错控制.     

基于参数依赖滚动时域H∞控制的高超声速飞行器控制

针对输入受限的高超声速飞行器强耦合、强非线性以及严重不确定性的特点,提出一种参数依赖滚动时域?∞控制(PD-RHHC)的方法.首先在考虑控制输入约束的条件下,引入参数依赖Lyapunov函数和松弛因子并提出了基于LMI优化的PD-RHHC;然后采用函数替换方法,结合张量积模型转换方法实现高超声速飞行器(HSV)纵向非线性弹性模型的LPV描述,并将PD-RHHC应用到高超声速飞行器纵向控制中,以实现HSV在大飞行包线内的机动飞行;最后通过仿真实验验证了所提出算法的有效性.     

具有积分测量和时延的离散线性变参数系统故障与状态估计

故障检测与诊断(FDD)技术可以有效地提高系统的安全性和可靠性,因此受到越来越多的关注.目前,关于离散系统的状态和故障估计问题的研究还不够充分.本文针对具有积分测量和时延的线性变参数(LPV)系统,提出了一种同时估计执行器/传感器故障和状态的方法.首先,系统当前状态、系统延迟状态和传感器故障构造一个扩维状态,得到广义离散LPV系统.其次,给出了该观测器存在的充分条件并证明观测器是H∞稳定的.然后,将系统状态、执行器和传感器故障的同时估计转化为矩阵不等式的求解问题,给出了观测器待设计矩阵的计算过程.最后,通过仿真验证了该方法的有效性.     

A robust observer‐based stabilization method for systems with uncertain parameters and Lipschitz nonlinearities

This paper deals with the robust observer‐based control design for a class of Lipschitz nonlinear discrete‐time systems with parameter uncertainties. Based on the use of a reformulated Lipschitz property combined with the slack variable techniques and some mathematical artifacts, it is shown that the solution of the discrete‐time output feedback stabilization problem is conditioned by a set of bilinear matrix inequalities, which become linear matrix inequalities by freezing some scalars. Furthermore, we show that some existing and elegant results reported in the literature can be regarded as particular cases of the stability conditions presented here. Numerical examples are provided to show the validity and superiority of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

Robust linear parameter‐varying control of induction motors

The paper deals with the motion control of an induction motor. Because the nonlinear state equations describing the dynamics of such a machine can be embedded into a linear model with the rotor speed ω as a varying parameter, advantage is taken of some recent results on the control of linear parameter‐varying systems, thus ensuring stability independently of how the varying parameter changes in time within a compact set. The adopted control structure consists of a fast inner electric loop that controls the stator currents and an outer mechanical loop that generates the torque acting on the motor shaft. Of crucial importance is the design of the internal model controller for the current loop. In particular, it is proved that an algebraically equivalent electric motor model admits a Lyapunov function that, together with its Lyapunov derivative, is independent of ω and of all motor parameters. This result allows us to find an upper bound on the norm of the Youla–Kucera parameter that ensures robust stability against speed measurement errors. Simulations carried out on a benchmark motor model show that the adopted control strategy performs well. Copyright © 2014 John Wiley & Sons, Ltd.