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This note presents a new analysis method to design an observer-based dynamic surface controller (ODSC) for a class of nonlinear systems. While the separation principle from linear system theory does not generally hold for nonlinear systems, a separation principle for the ODSC systems will be shown for a class of nonlinear systems, thus enabling the independent design of the observer and DSC. Furthermore, a convex optimization problem to test quadratic stability of ODSC will be formulated later. Index Terms--A separation principle, dynamic surface control, nonlinear observer.

In this paper, a new method of analyzing for the performance loss caused by faults in the systems is presented, and applied to the design of a fault tolerant longitudinal controller for a transit bus. Based on the amount of performance loss measured by a quadratic function, fault impact assessment is developed for both single and multiple faults. More specifically, ellipsoidal approximation of the tracking error bounds via dynamic surface control (DSC) is obtained via convex optimization technique for the nonlinear closed-loop system. Relying on the fault impact to the closed loop system and its isolatability on a fault detection and diagnosis system, the fault classification is proposed to provide a switching logic in the framework of a switched hierarchical structure. Finally, simulation results of the fault tolerant controller and corresponding fault classification are shown for multiple multiplicative faults. [DOI: 10.1115/1.1592188]

In this paper, a road adaptive modified skyhook control for the semi-active Macpherson strut suspension system of hydraulic type is investigated. A new control-oriented model, which incorporates the rotational motion of the unsprung mass, is introduced. The control law extends the conventional skyhook-groundhook control scheme and schedules its gains for various road conditions. Using the vertical acceleration data measured, the road conditions are estimated by using the linearized new model developed. Two filters for estimating the absolute velocity of the sprung mass and the relative velocity in the rattle space are also designed. The hydraulic semi-active actuator dynamics are incorporated in the hardware-in-the-loop tuning stage of the control algorithm developed. The optimal gains for the ISO road classes are discussed. Experimental results are included. [DOI: 10.1115/1.1434265] Keywords: Macpherson Strut Suspension, Modeling, Skyhook Control Semi-Active Damper, Gain Scheduling, Rapid Control Prototyping, Road Estimation

This paper presents reduced-order models of brake system dynamics derived from a physical modeling perspective. The vacuum booster model combines a static control valve with dynamic air flows, resulting in the ability to easily reproduce both static hysteresis effects and rapid transients. Following the assumption of incompressible flow, a four-state model of the brake hydraulics is presented and, subsequently, reduced to one or two states for certain applications. Experimental results support the simplifying assumptions made during the modeling process by demonstrating better agreement with the response from pedal force to brake pressure than previously displayed in the literature. These models are intended for use in the design and analysis of vehicle control systems and the evaluation of driver/vehicle interactions through dynamic simulation.

The control structure for automated vehicles in an Automated Highway System is based on the idea of multiple-surface sliding control. The 'upper' surface determines a desired net torque while the 'lower' surface determines the required throttle angle or brake pressure needed to achieve the desired torque. This paper presents an upper surface control law for performing longitudinal transition maneuvers. The maneuvers use desired velocity trajectories which are based on maintaining safety and comfort throughout the maneuver. The control law chosen is a sliding controller due to the nonlinearities in the dynamics and the uncertainties in the parameters. Adaptive techniques were also implemented to help improve the velocity tracking. The controller was implemented on experimental vehicles and tested at highway speeds.

This paper describes my work on nonlinear analysis and control over the last twenty years. The first part of the paper concerns the development of nonlinear analysis tools for predicting stability and forced response characteristics of high speed ground vehicles. The principal motivation was to develop an alternative to 'brute force' time domain simulation. The developed tools were extensions of 'describing function' or 'equivalent linearization' methods for both periodic and stochastic excitation. The 'statistical linearization' analysis tools were then extended and applied to design control laws for nonlinear stochastic regulators. The second part of the paper was motivated by control system design for highly nonlinear, multivariable systems, such as automotive powertrain control and aircraft flight control. For these classes of systems, statistical linearization procedures are computationally cumbersome and also provide no stability or robustness guarantees. A method which has proven extremely powerful, both theoretically and experimentally, is 'sliding control.' This technique is a form of input/output linearization that directly incorporates model error information with stability and performance measures. My students and I found several difficulties in the direct application of this method to automotive and aircraft control. This paper describes our solutions to the problems of repeated model differentiation, differentiation of model error, undesirable 'internal dynamics' and systems with saturating control inputs.

Acousto-optic (AO) devices are electronically controlled RF-driven devices related either to optical processing, or spectroscopy, including spectral imaging. These devices have been used throughout the visible and infrared regions. Optical [...]

Individual driver's driving behavior plays a pivotal role in personalized driver assistance systems. Gaussian mixture models (GMM) have been widely used to fit driving data, but unsuitable for capturing the data with a long-tailed distribution. Though the generalized GMM (GGMM) could overcome this fitting issue to some extent, it still cannot handle naturalistic data which is generally bounded. This paper presents a learning-based personalized driver model that can handle non-Gaussian and bounded naturalistic driving data. To this end, we develop a BGGMM-HMM framework to model driver behavior by integrating a hidden Markov model (HMM) in a bounded GGMM (BGGMM), which synthetically includes GMM and GGMM as special cases. Further, we design an associated iterative learning algorithm to estimate the model parameters. Naturalistic car-following driving data from eight drivers are used to demonstrate the effectiveness of BGGMM-HMM. Experimental results show that the personalized driver model of BGGMM-HMM that leverages the non-Gaussian and bounded support of driving data can improve model accuracy from 23 $ \sim$ 30% over traditional GMM-based models. [ABSTRACT FROM AUTHOR]

Byline: Xiao-Yun Lu, J. Karl Hedrick This paper is to address several points related to the design of Autonomous Road Vehicles (ARV) which are understood as those equipped with automatic control systems to perform some manoeuvres completely automatically or to a certain extent with some assistance from the driver. Emphasis is put on the improvement of vehicle driving stability and string stability through vehicle control systems design. The performance of an ARV depends largely on two factors: its physical structure and performance of its control systems. Physical structure determines a vehicle's limit for acceleration, deceleration and cornering capabilities. Control system performance can be measured by driving stability and string stability. Vehicle design problems discussed in this paper is restricted to the components (sensors, actuators and communication systems) relevant to the control systems. Control system design can be divided into two levels. The upper level includes the part from vehicle dynamics to the desired forces above the suspension system. The lower level includes all the actuators (throttle, brake, steering, and active suspension systems). Driving stability is mainly determined by vehicle dynamics and road situation. It can be abstracted as a 6DOF rigid body to dynamically interact with the road surface. To consider driving stability, the coupling between three latitude (longitudinal, lateral and vertical) motions and three rotational (yaw, pitch and roll) motions needs to be taken into consideration. However, to consider all the couplings would lead to a highly nonlinear model which causes difficulties to control design and implementation. It is shown that a 5DOF model with only roll motion relative to the road ignored is feedback linearisable. Similarly, one can prove that this is true if pitch motion is ignored, with roll motion taken into consideration. String stability is a concept for longitudinal control motion, which describes the dynamic interaction between vehicles in the same lane with short inter-vehicle distances. Practical string stability depends on control design method, following strategy, signal processing and data fusion. Driving stability in the longitudinal motion is only a necessary condition for string stability.

This paper presents the implementation and comparison of nonlinear controllers in the longitudinal control of cars for platooning. Based on the previous implementation of adaptive sliding mode controller, a dynamic sliding mode controller and a dynamic back-stepping multiple surface controller have been implemented. These three controllers have been compared with the test results. Realtime run shows that each controller has its own characteristics. Emphasis has been put on the dynamic back-stepping multiple surface controller. [DOI: 10.1115/1.1368115]

This paper presents a discrete-time adaptive sliding control method for SISO nonlinear systems with a bounded disturbance or unmodeled dynamics. Control and adaptation laws considering input saturation are obtained from approximately discretized nonlinear systems. The developed disturbance adaptation or estimation law is in a discrete-time form, and differs from that of conventional adaptive sliding mode control. The closed-loop poles of the feedback linearized sliding surface and the adaptation error dynamics can easily be placed. It can be shown that the adaptation error dynamics can be decoupled from sliding surface dynamics using the proposed scheme. The proposed control law is applied to speed tracking control of an automatic engine subject to unknown external loads. Simulation and experimental results verify the advantages of the proposed control law. [DOI: 10.1115/1.1349884]

An important aspect of an automated highway system design is the synthesis of an automatic vehicle following system. Associated with automatic vehicle following systems is the problem of the stability of a string of vehicles, i.e., the problem of spacing error propagation, and in some cases, amplification upstream from one vehicle to another, due to some disturbance at the head of the string. Realistic vehicle following designs must also address parametric uncertainties such as mass of the vehicle, aerodynamic drag, and tire drag. The mass of the vehicle varies with the number of passengers. At small intervehicular separations, aerodynamic drag force changes significantly with the distance to be maintained. In this paper, we address the problem of stability of a vehicle string in the presence of parametric uncertainty and present a Lyapunov-based decentralized adaptive control algorithm to compensate for such parametric variations. We examine this direct adaptive control algorithm for platoon performance and parameter convergence. We present the simulation results to demonstrate the effectiveness of the adaptive controller. Index Terms--Advanced cruise-control systems, decentralized adaptive control, direct adaptive control, intelligent vehicle highway system (IVHS), longitudinal control.

The invariance and robustness properties of variable structure control are lost in digital implementation. This paper presents three discrete-time variable structure control (DVSC) methods that can recover those properties for linear uncertain systems. The first method uses a disturbance compensator formulated in the variable structure framework and a decoupling law to separate the disturbance estimation dynamics from the closed loop dynamics. In the second approach, a recursive switching function is developed, which allows recovering the lost invariance and robustness properties, without using the disturbance compensator. The first method can result in slow transient dynamics, and the second can result in a large overshoot. In the third method, a new recursive switching function is developed and combined with the decoupled disturbance compensator method to recover the lost invariance and robustness properties. The three DVSC methods are applied to control the motion of an xy-stage of a CNC milling machine. In this experiment, the third method provided the best result. [S0022-0434(00)02204-8]

This paper discusses the development of a nonlinear controller design methodology and its application to an automotive control problem. The method is called the 'Multiple Sliding Surface' method and is closely related to sliding mode control, input/output linearization and integrator backstepping. The method was developed for a class of systems, typical of automotive control systems, where the uncertainties are 'mismatched' and where many of the equations contain sparse, experimentally obtained maps. The error bounds on these maps are often unknown and their sparseness makes them difficult to differentiate. The developed method does not require any derivatives and has guaranteed semi-global stability. This paper summarizes the development of the method and applies it to the design of a highly nonlinear system. The example is a combined brake/throttle controller for precision vehicle following. This controller was implemented on the California PATH vehicles in DEMO'97, an automated highway technology demonstration that occurred in San Diego, California in August of 1997. [S0022-0434(00)03004-5]

This paper presents the design and experimental implementation of a longitudinal control system for the operation of automated vehicles in platoons. The control system on each vehicle is designed to have a hierarchical structure and consists of an upper level controller and a lower level controller. The upper controller determines the desired acceleration for each vehicle in the platoon so as to maintain safe string-stable operation even at very small intervehicle spacing. The lower controller utilizes vehicle-specific parameters and determines the throttle and/or brake commands required to track the desired acceleration. A special challenge handled in the design of the lower level controller is low-speed operation that involves gear changes and torque converter dynamics. The paper also presents the design of longitudinal intra-platoon maneuvers that are required in order to allow any car in the platoon to make an exit. The paper presents extensive experimental results from the public NAHSC demonstration of automated highways conducted in August 1997 at San Diego, California. The demonstration included an eight-car platoon operating continuously over several weeks with passenger rides given to over a thousand visitors. The maneuvers demonstrated included starting the automated vehicles from complete rest, accelerating to cruising speed, allowing any vehicle to exit from the platoon, allowing new vehicles to join the platoon and bringing the platoon to a complete stop at the end of the highway. [S0022-0434(00)01903-1]

Active control of electric powertrains is challenging, due to the fact that backlash and structural flexibility in transmission components can cause severe performance degradation or even instability of the control system. Furthermore, high impact forces in transmissions reduce driving comfort and possibly lead to damage of the mechanical elements in contact. In this paper, a nonlinear electric powertrain is modelled as a piecewise affine (PWA) system. The novel receding horizon sliding control (RHSC) idea is extended to constrained PWA systems and utilised to systematically address the active control problem for electric powertrains. Simulations are conducted in Matlab/Simulink in conjunction with the high fidelity Carsim software. RHSC shows superior jerk suppression and target wheel speed tracking performance as well as reduced computational cost over classical model predictive control (MPC). This indicates the newly proposed RHSC is an effective method to address the active control problem for electric powertrains. [ABSTRACT FROM PUBLISHER]