Leader-follower Control Strategy Research Articles

Finger-Individuating Exoskeleton System with Non-Contact Leader-Follower Control Strategy.

This paper proposes a novel finger-individuating exoskeleton system with a non-contact leader-follower control strategy that effectively combines motion functionality and individual adaptability. Our solution comprises the following two interactive components: the leader side and the follower side. The leader side processes joint angle information from the healthy hand during motion via a Leap Motion Controller as the system input, providing more flexible and active operations owing to the non-contact manner. Then, as the follower side, the exoskeleton is driven to assist the user's hand for rehabilitation training according to the input. The exoskeleton mechanism is designed as a universal module that can adapt to various digit sizes and weighs only 40 g. Additionally, the current motion of the exoskeleton is fed back to the system in real time, forming a closed loop to ensure control accuracy. Finally, four experiments validate the design effectiveness and motion performance of the proposed exoskeleton system. The experimental results indicate that our prototype can provide an average force of about 16.5 N for the whole hand during flexing, and the success rate reaches 82.03% in grasping tasks. Importantly, the proposed prototype holds promise for improving rehabilitation outcomes, offering diverse options for different stroke stages or application scenarios.

Fuzzy Cooperative Control for the Stabilization of the Rotating Inverted Pendulum System

The rotating inverted pendulum is a nonlinear, multivariate, strongly coupled unstable system, and studying it can effectively reflect many typical control problems. In this paper, a parameter self-tuning fuzzy controller is proposed to perform the balance control of a single rotating inverted pendulum. Particle swarm optimization is used to adjust its control parameters, and simulation experiments are performed to show that the system can achieve stability with the designed parametric self-tuning fuzzy controller, with control performance better than that of the conventional fuzzy controller. Furthermore, the leader-follower control strategy is used to realize the cooperative control of multiple rotating inverted pendulums. Two QUBE-Servo 2 rotating inverted pendulums are used for a cooperative pendulum swing-up experiment and stabilization experiment, and the effectiveness of the proposed cooperative control strategy is verified.

A Dual Aircraft Maneuver Formation Controller for MAV/UAV Based on the Hybrid Intelligent Agent

This paper proposes a hybrid intelligent agent controller (HIAC) for manned aerial vehicles (MAV)/unmanned aerial vehicles (UAV) formation under the leader–follower control strategy. Based on the high-fidelity three-degrees-of-freedom (DOF) dynamic model of UAV, this method decoupled multiple-input-multiple-output (MIMO) systems into multiple single-input-single-output (SISO) systems. Then, it innovatively combined the deep deterministic policy gradient (DDPG) and the double deep Q network (DDQN) to construct a hybrid reinforcement learning-agent model, which was used to generate onboard desired state commands. Finally, we adopted the dynamic inversion control law and the first-order lag filter to improve the actual flight-control process. Under the working conditions of a continuous S-shaped large overload maneuver for the MAV, the simulations verified that the UAV can achieve accurate tracking for the complex trajectory of the MAV. Compared with the traditional linear quadratic regulator (LQR) and DDPG, the HIAC has better control efficiency and precision.

A Leader-Follower Control Strategy for Input-Delay Stochastic Systems

This paper designs an optimal open-loop leader-follower control strategy of input-delay stochastic systems. The leader-follower control problem is described as an optimal problem based on Stackelberg strategies. A control strategy of the leader is given to minimize the function of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{2}$ </tex-math></inline-formula> norm, while a control strategy of the follower in worst case maximizing the function of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> norm is applied to the systems. Then the optimal leader-follower control strategy is obtained by establishing the information relationship of the forward and the backward variables with augmentation of the variables and solving several Riccati equations. At last, an example illustrates the effectiveness of the proposed strategy.

Affine formation control for multi-agent systems with prescribed convergence time

In this paper, the affine formation control problem for multi-agent systems with prescribed convergence time is investigated. Firstly, on the basis of a time-varying scaling function, a distributed continuous control algorithm is designed, under which a stationary affine formation of the nominal configuration is able to be achieved within a prescribed time. Secondly, to track a time-varying formation within the prescribed time, a distributed control protocol is proposed by employing a leader–follower control strategy. Furthermore, the boundary layer technique is adopted to avoid chattering effect. Finally, simulation examples are provided to demonstrated the effectiveness of the proposed design.

Distributed Control Strategy of the Leader-Follower for Offshore Wind Farms under Fault Conditions

Because of the complexity and severity of the marine environment, the probability of failure of offshore wind farms is much higher than that of onshore wind farms. The original control might fail under a single-machine and the network communication faults of wind turbines. In this study, centralized control is replaced with distributed control, the leader-follower distributed control strategy under two types of fault conditions is proposed to reduce the adverse effect of failure on the system and improve the tolerance of the system. First, the single-machine system is expanded into a wind turbine cluster system model based on Hamiltonian energy theory. Then, a leader-follower distributed control strategy is proposed to ensure the stable operation of wind turbines under a single-machine fault of the leader or follower unit. Next, considering communication failure, the leader-follower control strategy in the weakly connected topology is designed to make the system and the active power output stable. Finally, the simulation results confirm that the leader-follower control strategy system can enhance the stability and reliability of the system in the case of a unit shut down and network communication faults.

Biologically-Inspired Learning and Adaptation of Self-Evolving Control for Networked Mobile Robots

This paper presents a biologically-inspired learning and adaptation method for self-evolving control of networked mobile robots. A Kalman filter (KF) algorithm is employed to develop a self-learning RBFNN (Radial Basis Function Neural Network), called the KF-RBFNN. The structure of the KF-RBFNN is optimally initialized by means of a modified genetic algorithm (GA) in which a Lévy flight strategy is applied. By using the derived mathematical kinematic model of the mobile robots, the proposed GA-KF-RBFNN is utilized to design a self-evolving motion control law. The control parameters of the mobile robots are self-learned and adapted via the proposed GA-KF-RBFNN. This approach is extended to address the formation control problem of networked mobile robots by using a broadcast leader-follower control strategy. The proposed pragmatic approach circumvents the communication delay problem found in traditional networked mobile robot systems where consensus graph theory and directed topology are applied. The simulation results and numerical analysis are provided to demonstrate the merits and effectiveness of the developed GA-KF-RBFNN to achieve self-evolving formation control of networked mobile robots.

Flocking Control of Multiple AUVs Based on Fuzzy Potential Functions

This paper presents the formulation of a flocking control algorithm for a group of autonomous underwater vehicles (AUVs). A leader–follower control strategy is employed to flock a group of AUVs along a predefined desired path. In this approach, leader AUVs are assumed to have global knowledge of the desired trajectory and the follower AUVs are not provided with this information. For keeping all the AUVs connected in a group, a flocking center is estimated. This flocking center is a virtual point whose position at any instant of time can be predicted by using a consensus algorithm. The controllers for the leader and follower AUVs are developed by implementing mathematical and fuzzy artificial potential functions. A group of four AUVs is considered for analyzing the efficacy of the developed control algorithm. Simulations are carried out both in obstacle-free and obstacle-rich environments. From the obtained results, it is observed that the proposed fuzzy flocking control algorithm provides effective cooperative motion control of multiple AUVs along the desired paths and avoid obstacles successively. It is also observed that the flocking controller developed based on fuzzy artificial potential function outperforms the controller with mathematical potential functions despite uncertainties owing to external disturbances.

Robust and adaptive chatter free formation control of wheeled mobile robots with uncertainties

This paper addresses the robust formation control of non-holonomic mobile robots with homogeneous system architecture and decentralized control structure. Therefore, it was necessary the mathematical modeling of mobile robots, from which, the Separation-Bearing variant of Leader-Following control strategy was implemented. The stability proof were based on the Lyapunov theory. The sliding mode control (SMC) strategy was used in the controller design to make the control robust to the incidence of uncertainties and disturbances. The Fuzzy Adaptive Formation Control is designed to eliminate the previous bounding knowledge of these uncertainties and disturbances. The proposed control effectiveness is demonstrated by results obtained with simulations in Matlab/Simulink. The pure kinematic and kinematic with disturbances is also analyzed. The results shows the controllers effectiveness to formation of multi-robots systems to the eight-shaped trajectory.

Coordinated path tracking of two vision-guided tractors for heavy-duty robotic vehicles

Abstract Heavy-duty robotic vehicles are increasingly required to transport and position large-quantity and large-scale objects in the manufacturing process. The load-carrying capacity of vehicles can be enhanced by configuring multiple automated guided tractors and coordinating their motions. A vision-guided tractor is developed by using an on-board camera in order to improve the guidance accuracy. Each tractor can recognize the guide paths, measure its path deviations and control the speeds of driving motors independently. A coordinated path tracking technique is proposed for two vision-guided tractors of a robotic vehicle, in order to make them move along a guide path accurately and smoothly. The finite area of the vision field, the actuation capacity of driving motors and the motion conflict of two tractors are considered as control constraints of path tracking. Six path deviation states and their relevant approaching trajectories are classified based on deviation properties and control constraints. The general law of mutual conversion of six approaching trajectories is analyzed. Other approaching trajectories should be converted into the tangent-arc trajectory that can eliminate two path deviations synchronously. Expected tracking distance is a coupled parameter that influences control efficiency, safety margin of trajectory conversion and coordination degree of two tractors. A fuzzy logic regulator is used in the leader-follower control strategy to adjust this parameter, by taking two path deviations and the difference of attitude angles of two tractors into account. Numerical simulation and prototype experiment show that two vision-guided tractors can move along the straight and curvilinear guide paths with high tracking accuracy, control efficiency and motion coordination, which enhanced the load-carrying capacity of robotic vehicles significantly.

The Effect of Remote Center Compliance Parameters on Formation Control of Cooperative Wheeled Mobile Robots for Object Manipulation

Formation control is a potential advanced technology for aircrafts, spacecrafts and space robots. This paper, for the first time, studies several methods of passive and semi-active Remote Center Compliance (RCC) in order to examine their effects on formation control of a group of Wheeled Mobile Robots (WMRs) for object manipulation during space/terrestrial explorations. To this end, first, the dynamics model of the constrained non-holonomic robots, object and RCC system have been derived precisely. A leader-follower control strategy is then utilized for trajectory tracking of the desired path by the cooperative robots. Finally, the passive and semi active RCC are optimized to make the formation robust in the presence of significant disturbances. The results obtained reveal that the semi-active RCC system, combined with a PID controller, reduces the effect of the disturbances experienced as compared to the other passive RCC modules.

Leader-Follower Control Strategy with Rigid Body Behavior

Abstract This work presents a control strategy for a leader-follower formation distance-based model of two single order kinematic model of robots. It uses feedback linearization techniques to derive the control action on the follower robot to maintain a desired distance and orientation with respect to the leader robot. Besides, it is shown that a suitable selection of the desired parameters make the formation behave as a rigid body. The control strategy is applied in a laboratory environment with two omnidirectional robots to show its performance.

Bas Multi-Robot Formation Coordination Control For Collective Missions

The paper presents a study of a mobile multi-robot formation (MRF) control problem. The robots are nonholonomic car-like vehicles and perform their mission while coordinating the formation shape when needed. The MRF control problem consists then of tracking reshaping a formation. Control design is based upon the centralized strategy assuming that information from a leader robot can be distributed to formation members. The main motivations for the work are that control strategies designed for single robots when applied to formations become complex and grow in terms of computational time, many of new control algorithms are dedicated to different formation coordination schemes and many of them were never verified experimentally. Two control levels are considered, i.e. kinematics and dynamics. Kinematics controllers applied are the input-output linearization and the Samson algorithm. They are simple in implementation and proved good performance in controlling single car-like robots. We examine them with regard to their potential applications for MRF. The dynamics controllers are based upon the generalized programmed motion equations method used successfully for a leader-follower control strategy for a fixed shape formation. Results of simulation studies, comparisons and discussions of implemented control algorithms are presented.

Synchronization Control of High Speed Tracked Vehicle with Hydrostatic Drive

A synchronization control strategy with cross-coupling concept for tracked vehicle with hydrostatic drive is developed and compared with a leader-following control strategy, aiming to achieve stable straight running. Associating with the basic controller, the two kinds of synchronization controllers are designed. Dynamic system model containing the control strategy for entire tracked vehicle is modeled in MATLAB/Simulink, the results of simulation indicate that, compared with leader-following control strategy, the cross-coupling strategy can restrain synchronization error more effectively and make the system more stable obviously under external disturbances by coordinates the motion of two drive loops simultaneously.