Rollover prevention and path following of a scaled autonomous vehicle using nonlinear model predictive control

Vehicle safety remains an important topic in the automotive industry due to the large number of vehicle accidents each year. One of the causes of vehicle accidents is due to vehicle instability phenomena. Vehicle instability can occur due to unexpected road profile changes, during full braking, obstacle avoidance or severe manoeuvring. Three main instability phenomena can be distinguished: the yaw-rate instability, the rollover and the jack-knife phenomenon. The main goal of this study is to develop a yaw-rate and rollover stability controller of an Autonomous Scaled Ground Vehicle (ASGV) using Nonlinear Model Predictive Control (NMPC). Open Source Software (OSS) known as Automatic Control and Dynamic Optimisation (ACADO) is used to design and simulate the NMPC controller based on an eight Degree of Freedom (8 DOF) nonlinear vehicle model with Pacejka tire model. Vehicle stability limit were determined using load transfer ratio (LTR). Double lane change (DLC) steering manoeuvres were used to calculate the LTR. The simulation results show that the designed NMPC controller is able to track a given trajectory while preventing the vehicle from rolling over and spinning out by respecting given constraints. A maximum trajectory tracking error of 0.1 meters (on average) is reported. To test robustness of the designed NMPC controller to model mismatch, four simulation scenarios are done. Simulation results show that the controller is robust to model mismatch. To test disturbance rejection capability of the controller, two simulations are performed, with pulse disturbances of 0.02 radians and 0.05 radians. Simulations results show that the controller is able to reject the 0.02 radians disturbance. The controller is not able to reject the 0.05 radians disturbance

Fuzzy Controllers

Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques. Bibliographic resources used to perform the work includes books and articles of present interest in the field, published in prestigious journals and publishing houses, and websites dedicated to various applications of fuzzy control. Its structure and the presented studies include the book in the category of those who make a direct connection between theoretical developments and practical applications, thereby constituting a real support for the specialists in artificial intelligence, modelling and control fields

Multi-objective scheduling and control of a nonlinear automotive powertrain

The automotive industry is faced with the challenge of ever-increasing emission legislation. This study demonstrates the effective use of nonlin­ear techniques in automotive control for the problem of fuel and emission minimisation. A review of previous work highlights the inadequacy of traditional optimisation formulations. The conflicting requirements of both low fuel and emissions is a design problem for which compromise and trade-offs are unavoidable. This study attacks the problem through powertrain scheduling, an approach ideally suited to both S.I. and diesel engines, and demonstrates how the novel application of multi-objective optimisation methods provides a solution more akin to the real physical problem. The modern control theory approach presented is a three stage pro­cess : formulation of the mathematical model, including the essential dy­namics, constraints, and objectives of the physical problem; optimisation of the control strategy with respect to the relevant performance criteria; and synthesis of the optimal control design. The optimisation model is finite-dimensional and nonlinear, the use of which demands a knowledge of nonlinear systems and available methods. These are classified. Re­sults for single and multi-objective optimisations are compared and fully demonstrate the advantages of the latter for the scheduling problem. Op­timal schedules are generated and from them, implementable rule-based control laws are derived. Performance, in terms of the ability to track a legislative test cycle and to retain the optimal design specification, is demonstrated through dynamic simulation, as is their driveability and robustness. This study specifically considers a diesel-engined vehicle incorporating a CVT. The methods tire widely applicable however, to other engine and transmissions types, and to other automotive control problems

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Emulation of haptic feedback for manual interfaces

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includes bibliographical references (p. 329-339).by Karon E. MacLean.Ph.D