An MPC-based Optimal Motion Control Framework for Pendulum-driven Spherical Robots

Motion control is essential for all autonomous mobile robots, and even more so for spherical robots. Due to the uniqueness of the spherical robot, its motion control must not only ensure accurate tracking of the target commands, but also minimize fluctuations in the robot's attitude and motors' current while tracking. In this paper, model predictive control (MPC) is applied to the control of spherical robots and an MPC-based motion control framework is designed. There are two controllers in the framework, an optimal velocity controller ESO-MPC which combines extend states observers (ESO) and MPC, and an optimal orientation controller that uses multilayer perceptron (MLP) to generate accurate trajectories and MPC with changing weights to achieve optimal control. Finally, the performance of individual controllers and the whole control framework are verified by physical experiments. The experimental results show that the MPC-based motion control framework proposed in this work is much better than PID in terms of rapidity and accuracy, and has great advantages over sliding mode controller (SMC) for overshoot, attitude stability, current stability and energy consumption.Comment: This paper has been submitted to Control Engineering Practic

Unmanned Robotic Systems and Applications

This book presents recent studies of unmanned robotic systems and their applications. With its five chapters, the book brings together important contributions from renowned international researchers. Unmanned autonomous robots are ideal candidates for applications such as rescue missions, especially in areas that are difficult to access. Swarm robotics (multiple robots working together) is another exciting application of the unmanned robotics systems, for example, coordinated search by an interconnected group of moving robots for the purpose of finding a source of hazardous emissions. These robots can behave like individuals working in a group without a centralized control

The Kinematics and Dynamics Motion Analysis of a Spherical Robot

Mobile robot application has reach more aspect of life in industry and domestic. One of the mobile robot types is a spherical robot whose components are shielded inside a rigid cell. The spherical robot is an interesting type of robot that combined the concept of a mobile robot and inverted pendulum for inner mechanism. This combination adds to more complex controllerdesignthantheothertypeofmobilerobots.Asidefrom these challenges, the application of a spherical robot is extensive, from being a simple toy, to become an industrial surveillance robot. This paper discusses the mathematical analysis of the kinematics and dynamics motion analysis of a spherical robot. The analysis combines mobile robot and pendulum modeling as the robot motion generated by a pendulum mechanism. This paper is expected to give a complete discussion of the kinematics and dynamics motion analysis of a spherical robot

Safety-critical model predictive control with control barrier function for dynamic obstacle avoidance

In this paper, a safety critical control scheme for a nonholonomic robot is developed to generate control signals that result in optimal obstacle-free paths through dynamic environments. A barrier function is used to obtain a safety envelope for the robot. We formulate the control synthesis problem as an optimal control problem that enforces control barrier function (CBF) constraints to achieve obstacle avoidance. A nonlinear model predictive control (NMPC) with CBF is studied to guarantee system safety and accomplish optimal performance at a short prediction horizon, which reduces computational burden in real-time NMPC implementation. An obstacle avoidance constraint under the Euclidean norm is also incorporated into NMPC to emphasize the effectiveness of CBF in both point stabilization and trajectory tracking problem of the robot. The performance of the proposed controller achieving both static and dynamic obstacle avoidance is verified using several simulation scenarios.Comment: 6 pages, 6 figures, IFAC World Congress 202

Flat systems, equivalence and trajectory generation

Flat systems, an important subclass of nonlinear control systems introduced via differential-algebraic methods, are defined in a differential geometric framework. We utilize the infinite dimensional geometry developed by Vinogradov and coworkers: a control system is a diffiety, or more precisely, an ordinary diffiety, i.e. a smooth infinite-dimensional manifold equipped with a privileged vector field. After recalling the definition of a Lie-Backlund mapping, we say that two systems are equivalent if they are related by a Lie-Backlund isomorphism. Flat systems are those systems which are equivalent to a controllable linear one. The interest of such an abstract setting relies mainly on the fact that the above system equivalence is interpreted in terms of endogenous dynamic feedback. The presentation is as elementary as possible and illustrated by the VTOL aircraft

Rotary-wing MAV Modeling & Control for indoor scenarios

This paper is about modeling and control of Miniature Aerial Vehicles ¿MAVs for indoor scenarios, specially using, micro coaxial and quadrotor systems. Mathematical models for simulation and control are introduced and subsequently applied to the commercial aircraft: the DraganFlyer quadrotor and the Micro-Mosquito coaxial flying vehicle. The MAVs have been hardware-modified in order to perform experimental autonomous flight. A novel approach for control based on Hybrid Backstepping and the Frenet-Serret theory is used for attitude stabilization (Backstepping+FST), introducing a desired attitude angle acceleration function dependent on aircraft velocity. Results of autonomous hovering and tracking are presented based on the scheme we propose for control and attitude stabilization when MAV is maneuvering at moderate speeds

Formation control of a group of micro aerial vehicles (MAVs)

Coordinated motion of Unmanned Aerial Vehicles (UAVs) has been a growing research interest in the last decade. In this paper we propose a coordination model that makes use of virtual springs and dampers to generate reference trajectories for a group of quadrotors. Virtual forces exerted on each vehicle are produced by using projected distances between the quadrotors. Several coordinated task scenarios are presented and the performance of the proposed method is verified by simulations

Novel Lyapunov - based autonomous controllers for Qquadrotors

In this paper, we look into the dynamic motion planning and control of an unmanned aerial vehicle, namely, the quadrotor, governed by its dynamical equations. It is shown for the first time that the Direct or the Second Method of Lyapunov is an effective tool to derive a set of continuous nonlinear control laws that not only provide smooth trajectories from a designated initial position to a designated target, but also continuously minimise the roll and pitch of the quadrotor en route to its targets. The latter successfully addresses the challenging problem of a quadrotor autonomously transporting valuable and fragile payloads safely to the designated target. Computer simulations are used to illustrate the effectiveness of the proposed control laws