Analysis and optimization of a non-time based motion controller for a nonholonomic mobile robot

As nonholonomic mobile robots have constraints imposed on motions that are not integrable, i.e. the constraints cannot be written as time derivatives of some function of the generalized coordinates, advanced techniques are needed for the tracking control. In the paper a robust control law is proposed for trajectory tracking of nonholonomic wheeled mobile robots. The state variables of the mobile robot are represented in polar coordinates, and the dynamic equation of the system is feedback-linearized by a computed-torque method. A novel sliding mode control law is derived for asymptotically stabilizing the mobile robot to a desired trajectory. It is shown that the proposed scheme is robust to bounded system disturbances. Simulation examples and experimental results are provided to show the effectiveness of the accurate tracking capability and the robust performance of the proposed controller.

The experience of the design of the nonlinear position control confirmed the remarkable potential of backstepping and fuzzy logic in the development of effective decision laws capable of overcoming the inherent limitations of model-based control strategies. This paper focuses on design of hybrid backstepping and fuzzy position logic controls of mobile robot that satisfied a good position tracking performance with simultaneously satisfactory control of velocities, which has an impact on wheel torques. In our previously designed backstepping controller a good tracking performance was obtained. However, its main shortcoming is unsatisfactory control velocities values, particularly at the beginning of tracking. Control parameters of backstepping controller and membership functions of fuzzy controller are adjusted by genetic algorithms. Advantage of the proposed fuzzy controller, and also hybrid backstepping controller, lies in the fact that control velocities (and consequently, the control torques) cannot exceed certain limits. Consequently, these controllers radically decreased the control velocities without major impact on tracking performance. Finally, from the simulation results obtained, it can be concluded that the proposed hybrid backstepping and fuzzy design achieve the desired results. Future work will include the investigation of a fuzzy stability of the proposed fuzzy logic position system.

Localization is one of the most crucial and difficult problems for motion control of mobile robots despite of tremendous research efforts made for years. This paper presents a new vision-based controller for controlling a nonholonomic mobile robot to track a desired trajectory without directly measuring its position. A novel adaptive estimator is embedded into this new controller to estimate global position of the mobile robot online using natural visual features measured by a vision system, and its orientation and velocity measured by odometry/inertia/magnetic sensors. It is proved by Lyapunov theory that the proposed controller gives rise to asymptotic tracking of a desired trajectory and convergence of the position estimation to the actual position. The experiment is conducted to validate the proposed controller.

Motivated by formation control of multiple non-holonomic mobile robots, this paper presents a trajectory tracking control scheme design for nonholonomic mobile robots that are equipped with low-level linear and angular velocities control systems. The design includes a nonlinear kinematic trajectory tracking control law and a tracking control gains selection method that provide a means to implement the nonlinear tracking control law systematically based on the dynamic control performance of the robot's low-level control systems. In addition, the proposed scheme, by design, enables the mobile robot to execute reference trajectories that are represented by time-parameterized waypoints. This feature provides the scheme a generic interface with higher-level trajectory planners. The trajectory tracking control scheme is validated using an iRobot Packbot's parameteric model estimated from experimental data.

Lateral Control for UAVs using Sliding Mode Technique

This work addresses the end-effector trajectory-tracking force and motion control of a three-dimensional three-link robot considering measurement noises. The last two links of the manipulator are considered as structurally flexible. An absolute coordinate approach is used while obtaining the dynamic equations to avoid complex dynamic equations. In this approach, each link is modeled as if there is no connection between the links. Then, joint connections are expressed as constraint equations. After that, these constraint equations are used in dynamic equations to decrease the number of equations. Then, the resulting dynamic equations are transformed into a form which is suitable for controller design. Furthermore, the dynamic equations are divided as pseudostatic equilibrium and deviation equations. The control torques resulting from the pseudostatic equilibrium and the elastic deflections are obtained easily as the solution of algebraic equations. On the other hand, the control torques corresponding to the deviations are obtained without any linearization. Encoders, strain gauges, position sensors and force and moment sensors are required for measurements. Low pass filters are considered for the sensors. For the crossover frequencies of the sensors, low and high values are chosen to observe the filtering effect on the robot output.

For a redundantly-actuated wheeled mobile robot, the squeeze force between the robot body and its wheels does not contribute to the motion of the robot, but to squeeze the related rigid bodies each other. It is good to control the squeeze force, regulate it to zero if possible, from the view of energy efficiency or life span of joint components. Thus a scheme controlling robot motion while controlling squeeze force is proposed as the following procedure: After a stable controller is presented for robot motion control, a squeeze force controller is designed to regulate the squeeze force to zero. The proposed scheme is demonstrated in robot regulation and tracking control problem. A PD+ controller is adopted for robot regulation, a modified inverse dynamics control is applied for robot tracking control. In both robot control problems, an integral feedback squeeze force controller is used to minimize the squeeze force. The presented simulation results verify the effect of the proposed scheme.

This paper deals with motion planning and control for mobile robots. The various components of an integrated architecture for the mobile robot Hilare pulling a trailer are presented. The nonholonomic path planner is based on an original steering method accounting for the small-time controllability of the system. Then the path is transformed into a trajectory by including the dynamical constraints of the system (bounded velocity and bounded acceleration). Finally, the motion control is addressed. Due to the geometric transformation for a virtual robot, we show how to reduce the problem to a classical approach of trajectory tracking for a mobile robot moving forward only. The experimental results presented include two types of robot-trailer connection systems.

In this paper, a fuzzy neural dynamics based tracking controller for nonholonomic wheeled mobile robots is proposed. The nonholonomic kinematic constraints are considered in the development of the controller. The proposed model is suitable for both continuous and discrete paths. Fuzzy rules are formulated to deal with the discontinuity in path directions. This model is capable of generating smooth velocity commands to drive the robot to track the desired paths. In the situation with large initial errors, the proposed model can automatically generate a smooth curve to reach the desired robot path from an arbitrary initial configuration without any explicit algorithms for the connection curve. At sharp turns, this model can automatically round off the sharp turns with a smooth curve. The effectiveness of the proposed tracking controller is demonstrated by simulation studies.

In high-precision fields such as advanced manufacturing, semiconductor processing, aerospace assembly, and precision machining, motion control systems often face challenges such as large tracking errors and low control efficiency due to complex dynamic environments. To address this, this paper innovatively proposes a data-driven feedforward compensation control strategy based on a Parallel Gated Recurrent Unit (GRU)–Transformer. This method does not require an accurate model of the controlled object but instead uses motion error data and controller output data collected from actual operating conditions to complete network training and real-time prediction, thereby reducing data requirements. The proposed feedforward control strategy consists of three main parts: first, a Parallel GRU–Transformer prediction model is constructed using real-world data collected from high-precision sensors, enabling precise prediction of system motion errors after a single training session; second, a nonlinear PD controller is introduced, using the prediction errors output by the Parallel GRU–Transformer network as input to generate the primary correction force, thereby significantly reducing reliance on the main controller; and finally, the output of the nonlinear PD controller is combined with the output of the main controller to jointly drive the precision motion platform. Verification on a permanent magnet synchronous linear motor motion platform demonstrates that the control strategy integrating Parallel GRU–Transformer feedforward compensation significantly reduces the tracking error and fluctuations under different trajectories while minimizing moving average (MA) and moving standard deviation (MSD), enhancing the system’s robustness against environmental disturbances and effectively alleviating the load on the main controller. The proposed method provides innovative insights and reliable guarantees for the widespread application of precision motion control in industrial and research fields.

A new golf swing robot to simulate human's motion has been developed by authors. The basic design concept of the robot is to realize high speed swing motion while by a smart structure, just like human. By the concept, the robot consists of a shoulder joint with powerful direct-drive motor and a wrist joint with small direct-drive motor. And for the reason, swing motion at high speed should be realized by a skill of motion control, so called dynamically-coupled driving, to compensate the lack of driving capability in the wrist joint. This paper deals with the motion control of the robot. First, a new model of golf swing robot with considering the flexibility of golf club is established and all parameters are identified by experiments. According to the new model, trajectories for different criteria an; generated and implemented to the robot. Experimental results show high accuracy of the motion control

This article proposes a control strategy based on dual-loop PID for the motion control of all-terrain mobile robots in complex environments. The research combines theoretical analysis and practical verification to design and implement an innovative dual-loop control system. The experimental platform adopts a spherical all-terrain robot, which achieves all-round motion control through a three-wheel omnidirectional drive structure. The system integrates a balancing loop based on PD control and a speed loop based on PI control, achieving the unity of motion stability and accuracy. The experimental results show that the optimized control system has a steady-state error of less than 1%, a response time of 150ms, and an external disturbance recovery time of no more than 0.5s. The system exhibits excellent adaptability under various terrain conditions and can adapt to a maximum tilt angle of 15 degrees. This study provides a practical solution for high-performance motion control of all-terrain mobile robots and has important reference value for developing autonomous robot systems.

The SynchronyTM Respiratory Tracking System (SRTS) component of the CyberKnife® Robotic Radiosurgery System (Accuray, Inc., Sunnyvale CA) enables real-time tracking of moving targets by modeling the correlation between the targets and external surrogate light-emitting diode (LED) markers placed on the patient's chest. Previous studies reported some cases with respiratory phase shifts between lung tumor and chest wall motions. In this study, the impacts of respiratory phase shifts on the motion-tracking accuracy of the SRTS were investigated. A plastic scintillator was used to detect the position of the x-ray beams. The scintillation light was recorded using a camera in a dark room. A moving phantom moved a U-shaped frame on the scintillator with a 4th power of sinusoidal functions. Three metallic markers for motion tracking and four fluorescent tapes were attached to the frame. The fluorescent tapes were used to identify phantom position and respiratory phase for each video frame. The beam positions collected, when considered relative to the phantom motion, represent the degree of tracking error. Beam position was calculated by adding error value to phantom position. Motions with respiratory phase shifts between the target and an extra stage mimicking chest wall motion were also tested for LED markers. Log files of the SRTS were analyzed to evaluate correlation errors. When target and LED marker motions were synchronized with a respiratory cycle of 4s, the maximum tracking errors for 90% and 95% of beam-on time were 1.0mm and 1.2mm, respectively. The frequency of tracking errors increased when LED marker motion phase preceded target motion. Tracking errors that corresponded to 90% beam-on time were within 2.4mm for 5-15% of phase shifts. In contrast, the tracking errors were very large when the LED marker delayed to the target motions; the maximum errors of 90% beam-on time were 3.0, 3.8, and 7.5mm for 5%, 10%, and 15% of phase shifts, respectively. The patterns of the tracking errors derived from the scintillation light were very similar to those of the correlation data of the SRTS derived from the log files, indicating that the tracking errors caused mainly due to the errors in modeling the correlation data. With long respiratory cycle of 6s, the tracking errors were significantly decreased; the maximum tracking errors for 95% beam-on time were 1.6mm and 2.2mm for early and delayed LED motion. We have investigated the motion-tracking accuracy of the CyberKnife SRTS for cases with the respiratory phase shift between the target and the LED marker. The maximum tracking errors for 90% probability were within 2.4mm when the target delays to the LED markers. When LED marker delays, however, very large tracking errors were observed. With a long respiratory cycle, the tracking errors were greatly improved to less than 2.2mm. Coaching slow breathing will be useful for accurate motion tracking radiotherapy.

This paper presents a trajectory tracking control scheme for a three wheeled mobile robot using sliding mode control method system. The indoor mobile robot system is subject to parameter perturbation and external interference during trajectory tracking control, and the problem of slow tracking speed and large tracking error will occur. In order to improve the tracking precision, a sliding mode control algorithm based on new approach law is proposed. Firstly, the motion control model of mobile robot is established, and a sliding mode trajectory tracking controller is designed. Then adopting MATLAB to track the linear and circular trajectories, the tracking error converges to zero around 3s. Experimental results show that sliding mode control method effectively reduces sliding mode control input chattering, and the convergence speed and tracking accuracy improve. Finally, the effectiveness of the control method is thus verified in practice.

SummaryIn this paper, we consider the transient performance of path‐following control of nonholonomic mobile robots with parametric uncertainties. By incorporating prescribed performance bound (PPB) technique, the transient performances on position and orientational tracking errors will be guaranteed with convergence rates no less than certain pre‐specified values and sufficiently small maximum overshoots. We also extend the proposed scheme to solve the formation control problem for a group of N unicycle‐type mobile robots without inter‐robot communications. It is ensured that all the robots can track their references with arbitrarily small errors and no collision will occur between any two robots. Simulation studies verify the established theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.