Sliding Mode Control of Vehicle Dynamics
The control of the longitudinal, lateral and vertical dynamics of two and four-wheeled vehicles, both of conventional type as well as fully-electric, is important not only for general safety of vehicular traffic in general, but also for future automated driving. Sliding Mode Control of Vehicular Dynamics provides an overview of this important topic. Topics covered include an introduction to sliding mode control; longitudinal vehicle dynamicscontrol via sliding modes generation; sliding mode control of traction and braking in two-wheeled vehicles; lateral vehicle dynamics control via sliding modes generation; stability control of heavy vehicles; sliding mode approach in semi-active suspension control; and observer-based parameter identification for vehicle dynamics assessment. Each chapter introduces the problem formulation and a general overview of its physical aspects, provides a survey of the relevant literature on the topic, and reports on the authors' contributions to solving the control problem. The book is essential reading for researchers involved in vehicle control, from both industry and academia, as well as advanced students.
Inspec keywords: stability; variable structure systems; vehicle dynamics; observers; braking; parameter estimation; traction; road vehicles
Other keywords: sliding modes generation; vehicle dynamics assessment; braking control; semiactive suspension control; traction control; sliding mode control; observer-based parameter identification; longitudinal vehicle dynamics control; two-wheeled vehicles; heavy vehicles; lateral vehicle dynamics control; stability control
Subjects: Engineering mechanics; Simulation, modelling and identification; Transportation system control; Stability in control theory; General and management topics; Vehicle mechanics; Multivariable control systems
- Book DOI: 10.1049/PBTR005E
- Chapter DOI: 10.1049/PBTR005E
- ISBN: 9781785612091
- e-ISBN: 9781785612107
- Page count: 350
- Format: PDF
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Front Matter
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1 Introduction to sliding mode control
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This chapter summarizes the basic concepts used in the design of sliding mode controllers, from the definition of conventional sliding set, and the main concept of sliding motion, to the design of the advanced robust exact high-order sliding modes differentiator. These pages describe the basis on which the methodologies presented along the book are designed, with this aim a short historical background is presented in Section 1.1, the main concepts related to the sliding mode theory are presented in Section 1.2. Section 1.3 describes the design process applied to the manifold, which restricts the movement of the state trajectories during the sliding motion. The basis of the design of standard sliding mode controllers are presented in Section 1.4. The main second-order sliding-mode algorithms are presented in Section 1.5 and the robust-exact high-order sliding-mode differentiator is described in Section 1.6.
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2 Longitudinal vehicle dynamics control via sliding modes generation
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In this chapter the application of Sliding Mode Control techniques is illustrated to solve the longitudinal vehicle dynamics control problem. Sliding Mode Control is a nonlinear control method capable of offering a number of benefits, the majority of which is its robustness versus a significant class of uncertainties. It can also be profitably used to efficiently solve automotive control and observation problems, as widely testified in the literature. The aim of this chapter is to provide an overview on the longitudinal dynamics control of vehicles, in particular electric vehicles with individual motors for each wheel, focusing on recent developments based on Sliding Mode Control theory.
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3 Sliding mode control of traction and braking in two-wheeled vehicles
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Four-wheeled vehicles are being equipped with many different active control systems which enhance drivers and passengers comfort and safety. In the field of two-wheeled vehicles, instead, the development of electronic control systems is following with some delay. However, the importance of active control for traction and braking has been recently recognized also for motorcycles. The motivation for this is twofold: on the one hand, in the racing context, these systems are designed to enhance vehicle performance; on the other hand, in the production context, the same control systems are intended to enhance the safety of non-professional bikers. Within such an evolving context, this chapter addresses the control problems related to the longitudinal dynamics of two-wheeled vehicles, that is traction and braking. To do this, some preliminary material introducing the dynamics of such vehicles is provided. Furthermore, the technological issues arising from the actuation dynamics and the measured signals available on board are discussed, to better highlight the challenges of this specific control problem. Then, the traction and braking problems are formulated within a sliding-mode framework, and the performance of second-order sliding mode controllers are analyzed.
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4 Lateral vehicle dynamics control via sliding modes generation
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This chapter introduces the application of Sliding Mode Control techniques by solving the lateral Vehicle Stability Control (VSC) problem. In Section 4.1 the linearized single track model is presented, which is typically used for the design of lateral stability controllers. The formulation of the yaw rate control problem is also explained, starting from the equations of motion. In Section 4.2, we propose a survey of the different methods for the control of the vehicle lateral dynamics, which are known from the research literature. The control structure and the specific sliding mode controllers which are presented in this chapter are illustrated in Section 4.3 and assessed in Section 4.4, where the results of the simulations are reported and discussed.
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5 Stability control of heavy vehicles
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In this chapter the design of active steering assistance systems for heavy vehicles is discussed. These kinds of systems are oriented to avoid the rollover and prevent lane departure of the vehicle. The methodology herein illustrated is based on the super-twisting algorithm. An estimator relying on high order sliding mode observer is developed in order to get information on the vehicle dynamics, such as lateral acceleration limit and the height of the center of gravity. The lateral position and lateral speed are controlled using sliding mode control in order to ensure the stability of the vehicle and avoid accidents. While in standard practical situations the lateral offset and the relative yaw angle are typically measured and the road curvature can be assumed known, the identification of some relevant parameters of the model needs to be carried out in order to increase the robustness of the control system, as discussed in the chapter. Simulation and experimental results are reported, making reference to a tractor model, in order to show the quality of the presented concept.
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6 Sliding mode approach in semi-active suspension control
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Ride of the vehicle envelops the heave, pitch and rolling motion in forced vibration caused by road unevenness and roughness. Ride comfort is mainly concerned with the ability of chassis to cope with the various forms of the vertical dynamic excitation, which are unpleasant to the driver and passengers. Such excitations can be suppressed by the proper adjustment of passive suspension or control of semi-active and active suspension systems. This chapter introduces recent developments in the area of suspension control methods, overviews basics of vehicle vertical dynamics modelling, provides survey on existing control methods and proposes new hierarchical control architecture to reduce vertical, pitch and roll accelerations during driving over uneven road. This control strategy is based on application of integral sliding mode approach and optimal distribution of virtual demand between four semi-active shock absorbers. Obtained simulation results confirm positive effects in ride comfort compared to the vehicle with passive suspension and continuous Skyhook control.
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7 Observer-based parameter identification for vehicle dynamics assessment
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Assessment of the vehicle handling especially with respect to its lateral dynamics is an important aspect of the overall vehicle design and development process. However, an increasing rate of vehicle update cycles, a massively growing number of variants and a required high-quality comfort and/or driving reward render the evaluation process a challenging task. Consequently, virtual methods support the overall development process and increase time and cost efficiency significantly. The so-called model-based (objective) handling methodology aims to extract certain vehicle and/or driver model parameters from measurement data. These can then be used to simulate standard handling maneuvers, rather than performing them on a test track. State-of-the-art parameter identification mechanisms are commonly performed offline and require extensive instrumentation of the test vehicle. This chapter presents a novel approach exploiting observer-based parameter identification techniques. It introduces the advantages of online capability, time-efficient experiment execution and reduction of sensing devices due to estimation of specific system states. The joint estimation of states and parameters is formulated as an unknown input recovery problem. Using sliding mode mechanisms allows formulation of state observers that are invariant with respect to certain classes of perturbations. Furthermore, the attractiveness is increased considering the property of finite time convergence. Herein, higher-order sliding mode concepts are used for the task of parameter identification providing robustness, finite convergence time and stability even for non-persistently excited systems. Evaluation of the concepts is performed in a twofold way: (a)An industrial vehicle dynamics simulation tool provides data for the observation concepts. The resulting parameter estimates are integrated into the offline simulation of standard handling maneuvers, e.g., step input steering. Comparing these results with the reference data allows to draw conclusions on the expected accuracy of the method. (b) The selected concepts are evaluated on experimental facilities, i.e., standard vehicles and an electric power steering test bench.
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Back Matter
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