Desired Trajectories Research Articles

Trajectory Tracking Control of a Mobile Robot with the ROS System

This article provides a simulation and laboratory study of a control system for a two-wheeled differential-drive mobile robot with ROS system. The authors propose an approach to designing a control system based on a parametric model of the robot’s dynamics. The values of unknown parameters of the dynamic model have been determined by means of a Levenberg-Marguardt identification method. By comparing the desired trajectories with those obtained from simulation and laboratory tests, and based on errors analysis, the correctness of the model parameter identification process and the control system operation was then determined.

Variable admittance time-delay control of an upper limb rehabilitation robot based on human stiffness estimation

This paper proposes a new variable admittance time-delay control strategy based on human stiffness estimation for improving the effectiveness of robot-assisted cooperative rehabilitation training. This control strategy is developed and implemented on a planar upper limb rehabilitation robot. Given the minimum-jerk-based desired trajectories of human hand position, in the developed control strategy, a time-delay approximator is utilized to estimate the external disturbances and modeling errors without exact knowledge of dynamics parameters, a sliding mode admittance controller is applied to obtained objective admittance characteristics, and an iterative optimization algorithm is used to estimate human arm stiffness and adjust human-robot interaction compliance. The closed-loop stability of the proposed control method is demonstrated via Lyapunov function theory. Experimental investigations involving ten subjects are conducted to validate the feasibility of the proposed control scheme. The experimental results show that the interaction compliance during cooperative rehabilitation training can be accurately adjusted based on selected admittance parameters and human arm stiffness, and it contributes to satisfying the specific training requirements of patients with different weakness levels and promoting the effectiveness of the robot-assisted training.

Intelligent power control of wind conversion system based on Takagi–Sugeno fuzzy model

SummaryThis paper comes up with a novel fuzzy control design for a wind conversion system (WCS). To do this, a boost converter is employed to adjust the rectified voltage under different wind speed levels. Initially, the boost converter model is well presented via the Takagi–Sugeno approach. Then, a T‐S fuzzy controller is designed to promptly calculate the duty cycle required for an optimal power operation. Afterward, the optimal DC current is determined and then transferred to the reference model to instantly determine the desired trajectories. These latter should be preserved so as to reach the maximum power. Following that, linear matrix inequalities (LMIs) are also used to guarantee the stability analyses and the performance. Finally, the sound performance and the validity of the suggested control schema are both proved by a numerical and some experimental results.

Nonlinear Extended Observer-Based ADRC for a Lower-Limb PAM-Based Exoskeleton

In lower-limb rehabilitation systems, exoskeleton robots are one of the most important components. These robots help patients to execute repetitive exercises under the guidance of physiotherapists. Recently, pneumatic artificial muscles (PAM), a kind of actuator that acts similarly to human muscles, have been chosen to power the exoskeleton robot for better human–machine interaction. In order to enhance the performance of a PAM-based exoskeleton robot, this article implements an active disturbance rejection control (ADRC) strategy with a nonlinear extended state observer (NLESO). Moreover, the stability of the closed-loop system is proved by Lyapunov’s theory. Finally, the experimental results show that with the proposed control strategy, the rehabilitation robot can effectively track the desired trajectories even when under external disturbance.

Completely Distributed Affine Formation Maneuvering of Networked Marine Surface Vehicles With Cooperation Localization

This paper develops a completely distributed affine formation maneuver control (CDAFC) algorithm for networked marine surface vehicles (NMSVs). The desired trajectories are generated by the affine image. Accordingly, NMSVs are capable to achieve arbitrary preset configuration transformations, while only a small part of the formation members called leaders obtain the configuration information. Then, a synthetical constraint is designed, which can concern position and attitude configuration rigidities simultaneously. This feature enables NMSVs to achieve formation maneuvers with time-varying formation speeds and orientations. On these bases, a novel CDAFC scheme is developed. In contrast to the conventional fully distributed control schemes, the implementation requirements are completely limited to the local reference frame, i.e., not only is CDAFC designed in a node-based way, but the CDAFC implementation just depends on the local relative poses and self velocities. Thus, we call it <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">completely distributed</i> . The semi-physical simulations are conducted to illustrate the effectiveness.

Research on iterative learning control of lower limb exoskeleton of rehabilitation robot

It is difficult to establish an accurate mathematical model for the lower limb exoskeleton system of a rehabilitation robot, and there are unknown external disturbances. In this paper, an accurate model-independent closed-loop PD-type iterative learning control algorithm is adopted, which enables the system to track a given desired trajectory with uncertain dynamic models and parameters. The simulation results show that the algorithm can effectively improve the control accuracy of the trajectory tracking of the lower limb exoskeleton.

Robust Adaptive General Formation Control of a Class of Networked Quadrotor Aircraft

This article is concerned with the consensus formation control problem of a class of networked quadrotor aircraft partially bounded and state-dependent perturbations. A general distributed consensus error model is first developed to formulate the formation behavior of the networked quadrotor aircraft. Then, by using adaptive techniques, virtual position control strategies are proposed to eliminate the impacts of perturbations, so that the following quadrotor aircraft can boundedly track the desired position trajectory with a satisfying pattern. Furthermore, based on the designed virtual position control strategies, the attitude reference angles are constructed and adaptive attitude control strategies are further designed to guarantee that the attitude angles track the reference angles asymptotically. In terms of the asymptotic tracking results of attitude control systems, the bounded consensus formation results are obtained based on the Lyapunov stability theorem. Numerical simulations are carried out to verify the efficiency of the designed position formation as well as attitude tracking control strategies of the networked quadrotor aircraft.

Kinematic Modeling and Characterization of Soft Parallel Robots

Parallel robots with rigid transmission mechanisms have been widely developed to improve the speed, precision, and load capability. However, it is still challenging in promoting soft parallel robots due to the difficulty in accurate kinematic modeling of soft continuum links. In this article, we present a general framework on the design, kinematic modeling, model-based characterization, and control for a class of soft parallel robots. The designed soft parallel robot consists of three fiber-reinforced soft pneumatic actuators, a base stage, and an output stage. With the introduction of the mathematical toolkit of the absolute nodal coordinate formulation, we develop a continuum-based model to describe and parameterize both the global complex configuration and the local large deformation of the soft parallel robot. In this sense, the mappings among the defined kinematic spaces of the robot can be characterized through force analysis. Based on the developed model, we next analyze the robot’s workspace and stiffness with different design parameters, which are also verified by a set of experiments. Finally, we establish a model-based trajectory tracking controller for the soft parallel robot. The experimental results demonstrate that with the feedforward controller, the end effector of the soft parallel robot can well follow the desired trajectories under different output velocities, where the average positioning error is about 2.6–3.9% of the maximum length of the workspace.

Sliding Mode Control for Trajectory Tracking of AGV Based on Improved Fast Stationary Power Approach Law

To eliminate the position deviation and direction error of trajectory tracking for the automated guided vehicle (AGV) wheeled parking robots in underground garages, a sliding mode controller is designed with a Lyapunov direct method and an improved fast stationary power approach law. Firstly, a kinematic model of the AGV wheeled parking robot in the global coordinate system is established. In order to make the AGV wheeled parking robots transfer from the deviation state to the sliding mode switching surface quickly and track the given reference trajectory stably, a novel fast stationary power approach law is proposed. Then, the Lyapunov direct method and the fast stationary power approach law are used to design the sliding mode controller. Finally, MATLAB software is employed to conduct the simulation tests of trajectory tracking. The simulation results obtained by adopting the fast stationary power approach law and traditional power approach law are compared. The compared results show that the former performs better in tracking the desired trajectories. The effectiveness of the designed controller is verified through simulation tests.

Orbital hopping maneuvers with two Astrobee free-flyers: Ground and flight experiments.

Dynamic hopping maneuvers using mechanical actuation are proposed as a method of locomotion for free-flyer vehicles near or on large space structures. Such maneuvers are of interest for applications related to proximity maneuvers, observation, cargo carrying, fabrication, and sensor data collection. This study describes a set of dynamic hopping maneuver experiments performed using two Astrobees. Both vehicles were made to initially grasp onto a common free-floating handrail. From this initial condition, the active Astrobee launched itself using mechanical actuation of its robotic arm manipulator. The results are presented from the ground and flight experimental sessions completed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School, the Intelligent Robotics Group facility at NASA Ames Research Center, and hopping maneuvers aboard the International Space Station. Overall, this study demonstrates that locomotion through mechanical actuation could successfully launch a free-flyer vehicle in an initial desired trajectory from another object of similar size and mass.

Improving Actuator Wearing Using Noise Filtering.

Actuator, mostly valve, wearing is an important factor of the overall industrial control system operational cost. Actuator operational wear strongly depends on its operation. Highly utilized elements have a tendency to degrade faster. Therefore, the maintenance teams prefer to minimize their moves. In contrary, control engineers need the actuators to actively operate in their control loops to mitigate disturbances and follow the desired trajectories. Higher control performance is often achieved with an active use of actuators. Control loop quality depends on the controller setup and loop auxiliary functionality. Properly designed filtering not only facilitates controller action, but also impacts actuator operational wear. Industrial control templates are built using the blockware that is embedded in the existing control system. Distributed control system (DCS) and programmable logic controller (PLC) have a limited number of control algorithms. An engineer has to design the control structure and the associated sensor noise filtering using available functionality. This paper evaluates and measures the impact of noise filtering on the loop performance and on the actuator weariness. Relations between noise filtering time constant, loop performance and valve travel deliver recommendations for control engineers.

Event-triggered adaptive dynamic programming for decentralized tracking control of input constrained unknown nonlinear interconnected systems

This paper addresses decentralized tracking control (DTC) problems for input constrained unknown nonlinear interconnected systems via event-triggered adaptive dynamic programming. To reconstruct the system dynamics, a neural-network-based local observer is established by using local input–output data and the desired trajectories of all other subsystems. By employing a nonquadratic value function, the DTC problem of the input constrained nonlinear interconnected system is transformed into an optimal control problem. By using the observer-critic architecture, the DTC policy is obtained by solving the local Hamilton–Jacobi–Bellman equation through the local critic neural network, whose weights are tuned by the experience replay technique to relax the persistence of excitation condition. Under the event-triggering mechanism, the DTC policy is updated at the event-triggering instants only. Then, the computational resource and the communication bandwidth are saved. The stability of the closed-loop system is guaranteed by implementing event-triggered DTC policy via Lyapunov’s direct method. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed scheme.

Event-Triggered iterative learning control for asynchronously switched systems

Iterative learning control (ILC) is an effective control strategy for complex systems that uses trial and error to obtain desired output trajectories. This paper focuses on the issue of event-triggered ILC for switched systems with asynchronous switching. An event-triggered ILC method is designed to reduce unnecessary controller updates during iterations. The main technical contribution is that the analysis and synthesis are performed in both time and iteration domains. First, in order to solve the asynchronous switching problem in the time direction and the update problem in the iteration direction, a Lyapunov function involving both directions is adopted. Second, to prove the convergence of tracking error and the system stability in both domains, a new prove method is proposed, in which the tracking error is summed over the entire time domain and the average dwell condition is summed over the entire iteration domain. Finally, the feasibility of theoretical result is verified by simulation.

Stable Spinning Deployment Control of a Triangle Tethered Formation System.

The tethered formation system has been widely studied due to its extensive use in aerospace engineering, such as Earth observation, orbital location, and deep space exploration. The deployment of such a multitethered system is a problem because of the oscillations and complex formation maintenance caused by the space tether's elasticity and flexibility. In this article, a triangle tethered formation system is modeled, and an exact stable condition for the system's maintaining is carefully analyzed, which is given as the desired trajectories; then, a new control scheme is designed for its spinning deployment and stable maintenance. In the proposed scheme, a novel second-order sliding mode controller is given with a designed nonsingular sliding-variable. Based on the theoretical proof, the addressed sliding variable from the arbitrary initial condition can converge to the manifold in finite time, and then sliding to the equilibrium in finite time as well. The simulation results show that compared with classic second sliding-mode control, the proposed scheme can speed up the convergence of the states and sliding variables.

On Self-Learning Mechanism for the Output Regulation of Second-Order Affine Nonlinear Systems

This article studies global robust output regulation of second-order nonlinear systems with input disturbances that encompass the fully-actuated Euler–Lagrange systems. We assume the availability of relative output (w.r.t. a family of reference signals) and output derivative measurements. Based on a specific separation principle and self-learning mechanism, we develop an internal model-based controller that does not require <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge of reference and disturbance signals and it only assumes that the kernels of these signals are a family of exosystems with unknown parameters (e.g., amplitudes, frequencies, or time periods). The proposed control framework has a self-learning mechanism that extricates itself from requiring absolute position measurement nor precise knowledge of the feedforward kernel signals. By requiring the high-level task/trajectory planner to use the same class of kernels in constraining the trajectories, the proposed low-level controller is able to learn the desired trajectories, to suppress the disturbance signals, and to adapt itself to the uncertain plant parameters. The framework enables a plug-and-play control mechanism in both levels of control.

Trajectory tracking control of tracked vehicles considering nonlinearities due to slipping while skid-steering

In many applications, mobile vehicles operate over rough terrains to handle certain tasks and missions. Therefore, they are designed with tracks to deal with such irregular surfaces. Motion control and steering of tracked vehicles under the influence of slipping while skidding are still an interesting topic for many specialists and researchers and need further investigation. In fact, modelling and control of skid-steered tracked vehicles with slipping are very challenging. In this paper, various control schemes are proposed to investigate the closed-loop dynamical performance of tracked vehicles using different desired trajectories. Three control strategies are formulated and tuned to handle the undesirable effect of slipping while skidding: (i) robust nonlinear controller, (ii) speed compensation-based fuzzy logic controller, and (iii) speed compensation-based proportional–integral controller. The proposed control schemes are designed to explore new methods of skid-steering control with slipping. Preliminary simulation results are introduced to verify the effectiveness of the proposed controllers, using different desired trajectories, and to demonstrate the feasibility of utilizing such controllers.

Finite-Time Neuro-Sliding-Mode Controller Design for Quadrotor UAVs Carrying Suspended Payload

Due to the quadrotor’s underactuated nature, suspended payload dynamics, parametric uncertainties, and external disturbances, designing a controller for tracking the desired trajectories for a quadrotor that carries a suspended payload is a challenging task. Furthermore, one of the most significant disadvantages of designing a controller for nonlinear systems is the infinite-time convergence to the desired trajectory. In this paper, a finite-time neuro-sliding mode controller (FTNSMC) for a quadrotor with a suspended payload that is subject to parametric uncertainties and external disturbances is designed. By constructing a finite-time sliding mode controller, the quadrotor can follow the reference trajectories in finite time. Furthermore, despite time-varying nonlinear dynamics, parametric uncertainties, and external disturbances, a neural network structure is added to the controller to effectively reduce chattering phenomena caused by high switching gains, and significantly reduce the size of the control signals. Following the completion of the controller design, the system’s stability is demonstrated using the Lyapunov stability criterion. Extensive numerical simulations with various scenarios are run to demonstrate the effectiveness of the proposed controller.

Robust tracking for functional electrical stimulation cycling with unknown time-varying input delays: A switched systems approach.

Motorized functional electrical stimulation (FES) cycling has been demonstrated to have numerous health benefits for individuals suffering from neurological disorders. FES-cycling is usually designed to track the desired trajectories in real time. However, there are input delays between the exertion of the stimulation and the corresponding muscle contraction that potentially destabilize the system and undermine training efforts. Meanwhile, muscle fatigue gives rise to a time-varying input delay and decreased force. Moreover, switching between FES and motor control can be chattering and destabilizing owing to the high frequency. This article constructs Lyapunov-Krasovskii functionals to analyze the stability and robustness of the nonlinear cycling system with time-varying input delay. A new average dwell time condition is then provided to ensure the input-to-state stability of the considered systems. Finally, numerical simulations are illustrated to verify the effectiveness of the developed controller.

High‐order robust command filtered backstepping design for strict‐feedback systems: A high‐order fully actuated system approach

AbstractA high‐order fully actuated (HOFA) system approach is invoked to construct a high‐order robust command filtered backstepping (HORCFB) controller to track a feasible desired output trajectory for the second‐ and high‐order strict‐feedback systems (SFSs) subjected simultaneously to nonlinear uncertainties, where the subsystems of the SFSs possess a common full‐actuation structure. Unlike the existing classical first‐order state‐space approach, the proposed HORCFB scheme avoids converting the high‐order systems into first‐order ones, and thus simpler to implement and needs fewer steps. Moreover, the presented result avoids the complexity arising due to repeatedly differentiating, namely, the problem of “explosion of complexity.” Stability analysis of the closed‐loop system shows that all the states of the closed‐loop system are kept uniformly ultimately bounded, and the output is driven to track a feasible desired output trajectory with an arbitrarily small error by proper selection of the design parameters. Finally, the effectiveness of the proposed scheme is demonstrated by the trajectory tracking control problem of a single‐link robot arm with the elastic revolute joint.

Trajectory tracking and formation of quadrotors using a backstepping control and coupling with intermediary system

In this work, a trajectory-tracking scheme is proposed by using a backstepping control with a dynamic coupling used as an intermediary system of quadcopters in a master-salve configuration. The desired trajectories for the master quadcopter are conventional, concentric and chaotic trajectories. By means of a proper mathematical analysis and extensive numerical simulations, we show the correct performance of proposed scheme presented.