Direct yaw-moment control of an in-wheel-motored electric vehicle based on body slip angle fuzzy observer

A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental settin

Mechatronics of a ball screw drive using a N degrees of freedom dynamic model

High performance position control in machine tools can only be achieved modelling the dynamic behavior of the mechatronic system composed by the motor, transmission and control during the design stage. In this work, a complex analytical model of a ball screw drive is presented and integrated in a mechatronic model of the actuator to predict the dynamic behaviour and analyze the impact of each component of the transmission. First, a simple 2 degrees of freedom model is presented, and is analysis sets the basis for the development of a more complex model of several degrees of freedom, whose resulting fundamental transfer functions are represented using natural and modal coordinates. The modeling in modal coordinates carries a reduction of the transfer function that reduces computational work. The two models are compared and experimentally validated in time and frequency domain by means of experimental tests carried out on a specifically developed ball screw drive test benchMinisterio de Economía y Competitividad: Project DPI2015-64450-R (MINECO/FEDER, UE) University of the Basque Country (UPV/EHU) under the program UFI 11/29 Departamento de Educación, Política Lingüística y Cultura” of the regional government of the Basque Country (IT949-16

Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration

In this paper, we present a robotic model-based reinforcement learning method that combines ideas from model identification and model predictive control. We use a feature-based representation of the dynamics that allows the dynamics model to be fitted with a simple least squares procedure, and the features are identified from a high-level specification of the robot's morphology, consisting of the number and connectivity structure of its links. Model predictive control is then used to choose the actions under an optimistic model of the dynamics, which produces an efficient and goal-directed exploration strategy. We present real time experimental results on standard benchmark problems involving the pendulum, cartpole, and double pendulum systems. Experiments indicate that our method is able to learn a range of benchmark tasks substantially faster than the previous best methods. To evaluate our approach on a realistic robotic control task, we also demonstrate real time control of a simulated 7 degree of freedom arm.Comment: 8 page

Understanding friction induced damping in bolted assemblies through explicit transient simulation

The design of joints is seeing increased interest as one of the ways of controlling damping levels in lighter and more flexible aeronautic structures. Damping induced by joint dissipation has been studied for more than a decade, mostly experimentally due to the difficulty of simulating large structures with non-linearities. Experimentally fitted meta-models were thus used for damping estimation at design stage without a possible optimization. The aim of this paper is to demonstrate that damping estimation using local friction models is feasible and that it can be usable for design. The simulation methodology is based on an explicit Newmark time scheme with model reduction and numerical damping that can be compensated for the modes of interest. Practical simulation times counted in minutes are achieved for detailed models. The illustration on a lap-joint shows how simulations can be used to predict the amplitude dependence of modal damping, answer long standing questions such as “does the modeshape change?” or analyze the evolution of pressure fields during a cycle

CAD enabled trajectory optimization and accurate motion control for repetitive tasks

As machine users generally only define the start and end point of the movement, a large trajectory optimization potential rises for single axis mechanisms performing repetitive tasks. However, a descriptive mathematical model of the mecha- nism needs to be defined in order to apply existing optimization techniques. This is usually done with complex methods like virtual work or Lagrange equations. In this paper, a generic technique is presented to optimize the design of point-to-point trajectories by extracting position dependent properties with CAD motion simulations. The optimization problem is solved by a genetic algorithm. Nevertheless, the potential savings will only be achieved if the machine is capable of accurately following the optimized trajectory. Therefore, a feedforward motion controller is derived from the generic model allowing to use the controller for various settings and position profiles. Moreover, the theoretical savings are compared with experimental data from a physical set-up. The results quantitatively show that the savings potential is effectively achieved thanks to advanced torque feedforward with a reduction of the maximum torque by 12.6% compared with a standard 1/3-profil