Hierarchical Control Law Research Articles

An overactuated aerial robot based on cooperative quadrotors attached through passive universal joints: Modeling, control and 6-DoF trajectory tracking

This article discusses a novel aerial robot architecture that overcomes the underactuation of conventional multirotor systems without adding dedicated rotor tilting actuators. The proposed system is based on four quadrotors cooperatively carrying a central body to which they are attached through passive universal joints. While conventional parallel axis multirotors are underactuated, the proposed mechanism makes the system overactuated, enabling independent position and orientation control of the main body. This implies that the payload can be carried in the minimum drag orientation, it enables take-off and landing on inclined surfaces and it provides thrust-vectoring capabilities to the system, leading to high control authority. A detailed dynamic model is derived making use of Lagrangian formalism and a hierarchical control law based on such model is proposed to stabilize the system. This control law is designed to ensure good tracking while minimizing power consumption. The proposed control law and the capabilities of the architecture are evaluated in simulation and in outdoor experimental flights, where the aerial robot shows autonomous tracking of the six degrees of freedom (DoF) of the main body, an inherently unfeasible maneuver for conventional underactuated multirotors.

Design, Assembly and Control of a Differential/Omnidirectional Mobile Robot through Additive Manufacturing

Although additive manufacturing is a relatively new technology, it has been widely accepted by industry and academia due to the wide variety of prototypes that can be built. Furthermore, using mobile robots to carry out different tasks allows greater flexibility than using manipulator robots. In that sense, and based on those above, this article focuses on the design and assembly of a multi-configurable mobile robot that is capable of changing from a differential to an omnidirectional configuration. For this purpose, a sequential mechatronic design/control methodology was implemented to obtain an affordable platform via additive manufacturing which is easily scalable and allows the user to change from one configuration to another. As a proof of concept, this change is made manually. Fabrication, construction, and assembly processes for both structures are presented. Then, a hierarchical control law is designed. In this sense and based on Lyapunov’s method, a low-level controller is developed to control the angular speed of the wheels to a desired angular speed, and a medium-level controller controls the robot’s attitude to follow a desired Cartesian trajectory. Finally, the control strategies are implemented in both prototype configurations, and through experimental results, the theoretical analysis and the construction of the mobile robot are validated.

Model-Based Coordinated Trajectory Tracking Control of Skid-Steer Mobile Robot with Timing-Belt Servo System

Four-wheel, independently driven skid-steer mobile robots have been widely used in some fields, such as indoor product shipping and outdoor inspection and exploration. Traditional skid-steer mobile robot controllers often use a kinematics controller to obtain the desired speed of each wheel, complete speed closed-loop control of each wheel and achieve the robot’s trajectory tracking control. However, the controller based on kinematics may lead to robot chattering and wheel spin from being directly driven by the motor on uneven grounds. To solve these problems, we developed a four-wheel, independently driven skid-steer mobile robot with a damping module for the timing-belt servo system and proposed a model-based coordinated trajectory tracking control method with the timing-belt servo system. First, the kinematics and dynamics of the mobile robot are established, including the chassis kinematics and dynamics, as well as the dynamics of the timing-belt servo system. Secondly, the hierarchical control law is designed, which has adaptive robust control of the upper-level robot chassis, middle-level control allocation approach, and adaptive robust control of the bottom-level timing-belt servo system. Finally, the proposed method is verified by the robot’s trajectory tracking control comparison simulation experiments and has a better control performance.

Hierarchical Control of DC Motor Coupled with Cuk Converter Combining Differential Flatness and Sliding Mode Control

This paper proposes a hierarchical control law for DC motor fed by DC–DC power Cuk Converter. The control is divided into two parts: Firstly, the property of differential flatness associated with the mathematical model of the DC motor is studied to design a robust control that achieves the task of tracking the reference angular speed trajectory for the motor. It also gives the voltage profile $$\vartheta $$ which must be followed by the Cuk converter. The second independent controller, based on cascade control, is proposed for the Cuk converter, which allows the converter output voltage to follow the specified trajectory $$\vartheta $$ . Sliding mode control is used in the inner loop, whereas proportional integral control is used in the proposed cascade controller’s outer loop. Numerical simulation of the hierarchical control technique is carried out in MATLAB/Simulink, and results under parametric variation show robustness. Finally, a comparison is drawn for speed trajectory tracking by the DC motor coupled with DC–DC buck and Cuk converter to show the performance improvement in case of using Cuk converter for angular speed trajectory tacking of a DC motor.

Sea star inspired crawling and bouncing.

The oral surface of sea stars is lined with arrays of tube feet that enable them to achieve highly controlled locomotion on various terrains. The activity of the tube feet is orchestrated by a nervous system that is distributed throughout the body without a central brain. How such a distributed nervous system produces a coordinated locomotion is yet to be understood. We develop mathematical models of the biomechanics of the tube feet and the sea star body. In the model, the feet are coupled mechanically through their structural connection to a rigid body. We formulate hierarchical control laws that capture salient features of the sea star nervous system. Namely, at the tube foot level, the power and recovery strokes follow a state-dependent feedback controller. At the system level, a directionality command is communicated through the nervous system to all tube feet. We study the locomotion gaits afforded by this hierarchical control model. We find that these minimally coupled tube feet coordinate to generate robust forward locomotion, reminiscent of the crawling motion of sea stars, on various terrains and for heterogeneous tube feet parameters and initial conditions. Our model also predicts a transition from crawling to bouncing consistently with recent experiments. We conclude by commenting on the implications of these findings for understanding the neuromechanics of sea stars and their potential application to autonomous robotic systems.

Uncalibrated Visual Servo for Unmanned Aerial Manipulation

This paper addresses the problem of autonomous servoing an unmanned redundant aerial manipulator using computer vision. The overactuation of the system is exploited by means of a hierarchical control law, which allows to prioritize several tasks during flight. We propose a safety-related primary task to avoid possible collisions. As a secondary task, we present an uncalibrated image-based visual servo strategy to drive the arm end-effector to a desired position and orientation by using a camera attached to it. In contrast to the previous visual servo approaches, a known value of camera focal length is not strictly required. To further improve flight behavior, we hierarchically add one task to reduce dynamic effects by vertically aligning the arm center of gravity to the multirotor gravitational vector, and another one that keeps the arm close to a desired configuration of high manipulability and avoiding arm joint limits. The performance of the hierarchical control law, with and without activation of each of the tasks, is shown in simulations and in real experiments confirming the viability of such prioritized control scheme for aerial manipulation.

Output feedback hierarchical control for nonlinear systems

SummaryIn this paper, we address the problem of hierarchical control for nonlinear systems and design two dynamic output feedback hierarchical control laws in a semiglobal sense and in a global sense, respectively. With the controllers applied to a class of nonlinear systems, some transient and steady properties of the system output trajectories can be satisfied simultaneously. Furthermore, the corresponding result in the global sense for linear systems is naturally derived. Finally, the effectiveness of our approach is illustrated by a single‐link robot arm system. Copyright © 2017 John Wiley & Sons, Ltd.

Hierarchical control for nonlinear systems by partial-state feedback

In this paper, the hierarchical control problem is rephrased and addressed that systematically tackles the design of hierarchical control law between the concrete system and the abstract system. The proposed way to this problem, on one hand, incorporates simulation function technique, and on the other hand, allows us to design a partial-state feedback hierarchical control law. Following this approach, we design two hierarchical control laws for nonlinear systems. Finally, an example illustrates this approach.

An anti-disturbance PD control scheme for attitude control and stabilization of flexible spacecrafts

This paper studies the attitude control problem of spacecrafts with flexible appendages. It is well known that the unwanted vibration modes, model uncertainty and space environmental disturbances may cause degradation of the performance of attitude control systems for a flexible spacecraft. In this paper, the vibration from flexible appendages is modeled as a derivative-bounded disturbance to the attitude control system of the rigid hub. A disturbance-observer-based control (DOBC) is formulated for feedforward compensation of the elastic vibration. The model uncertainty and space environmental disturbances as well as other noises are merged into an “equivalent” disturbance. We design a composite controller with a hierarchical architecture by combining DOBC and PD control, where DOBC is used to reject the vibration effect from the flexible appendages. Numerical simulations are performed to demonstrate that by using the composite hierarchical control law, disturbances can be effectively attenuated and the robust dynamic performances be enhanced.

Hierarchical control system design using approximate simulation

In this paper, we present a new approach for hierarchical control based on the recent notions of approximate simulation and simulation functions, a quantitative version of the simulation relations. Given a complex system that needs to be controlled and a simpler abstraction, we show how the knowledge of a simulation function allows us to synthesize hierarchical control laws by first controlling the abstraction and then lifting the abstract control law to the complex system using an interface. For the class of linear control systems, we give an effective characterization of the simulation functions and of the associated interfaces. This characterization allows us to use algorithmic procedures for their computation. We show how to choose an abstraction for a linear control system such that our hierarchical control approach can be used. Finally, we show the effectiveness of our approach on an example.

A parallel‐hierarchical neural network model for motor control of a musculo‐skeletal system

AbstractThis paper proposes a new parallel‐hierarchical neural network model to enable motor learning for simultaneous control of both trajectory and force, by integrating Hogan's control method and the author's previous neural network control model using a feedback‐error‐learning scheme. Furthermore, two hierarchical control laws which apply to the model are derived by using the Moore‐Penrose pseudo‐inverse matrix: one is related to the minimum muscle‐tension‐change trajectory; and the other is related to the minimum motor‐command‐change trajectory. The human arm is redundant at the dynamics level since joint torque is generated by agonist and antagonist muscles. Therefore, acquisition of the inverse model is an ill‐posed problem. However, the combination of these control laws and feedback‐error‐learning resolves the ill‐posed problem. Finally, the efficiency of the parallel‐hierarchical neural network model is shown by learning experiments using an artificial muscle arm and computer simulations.