Predictive control of aircraft control systems for maneuverable target

A new aircraft guidance law utilizing predictive control algorithm is proposed. Compared with extended proportional navigation guidance law, this guidance law is designed specifically for using against a maneuverable target. It can track the target maneuver effectively. Uncertainty in the predicted target's future maneuvering is handled by constructing a stochastic predictive cost function and utilizing the stochastic minimum principle to deduce a predictive control algorithm. The guidance law is established by adopting the continuous approximation method into the continuous predictive control algorithm. The simulation results demonstrate that the stochastic predictive guidance law has the ability of trajectory prediction. Compared with the PID proportional navigation guidance law, the stochastic predictive guidance law has smaller overload and can intercept the maneuvering target more effectively.     

Event-triggered adaptive target tracking control for an underactuated autonomous underwater vehicle with actuator faults

In this paper, the target tracking control problem is investigated for an underactuated autonomous underwater vehicle (AUV) in the presence of actuator faults and external disturbances based on event-triggered mechanism. Firstly, the five degrees-of-freedom kinematic and dynamic models are constructed for an underactuated AUV, where the backstepping method is introduced as the major control framework. Then, radial basis function neural network (RBFNN) and adaptive control method are made full use of estimating and compensating the influences of uncertain information and actuator faults. Besides, the relative threshold event-triggered strategy is integrated into the tracking control to further reduce communication burden from the controller to the actuator. Moreover, through Lyapunov analysis, it is proved that the designed controllers guarantee that the tracking error variables of the underactuated AUV are uniformly ultimately bounded and can converge to a small neighborhood of the origin. Finally, the effectiveness and reasonableness of the designed tracking controllers are illustrated by comparative simulations.     

Fast fixed-time vertical plane motion control of autonomous underwater gliders in shallow water

In this paper, a fast fixed-time vertical plane motion controller is proposed for autonomous underwater gliders (AUGs) gliding in shallow water. The influence of speed-sensorless conditions, model uncertainties, unknown time-varying external disturbances, input saturations, and state delay are taken into account. To improve control performance, a fast fixed-time stable system is first presented. Based on the system, an adaptive extended state observer (ESO) is developed for estimating speed, model uncertainties, and external disturbances. A fast fixed-time controller is designed for improving the gliding efficiency and reducing the risk of hitting the ocean floor. Moreover, an input saturation auxiliary system and an advance compensation method are presented to cope with input saturations and state delay. According to Lyapunov theory, it is proved that the AUG states can converge into a small neighborhood within a fixed time. Finally, simulation results demonstrate the rapidity and effectiveness of the designed control method.     

Scaled telerobotic control of a manipulator in real time with laser assistance for ADL tasks

In this paper we present a novel concept of shared autonomous and teleoperation control of a remote manipulator with a laser-based assistance in a hard real-time environment for people with disabilities to perform activities of daily living (ADL). The laser pointer enables the user to make high-level decisions, such as target object selection, and it enables the system to generate a trajectories and virtual constraints to be used for autonomous motion or scaled teleoperation. Autonomous, position-teleoperation and velocity-teleoperation control methods have been implemented in the control code. Scaling and virtual fixtures have been used in the teleoperation based control depending on the user preference.A real-time QNX operating system has been used to control a PUMA 560 robotic arm using a Phantom Omni master through a TCP/IP port. A SICK laser range finder was used to for the telerobotic control. The system was implemented with different control modes, and three healthy human subjects were trained to use the system for a pick-and-place task. Data were collected and presented for different control modes, and a comparison between these modes based on the time to complete the task was presented.     

A general motion control framework for an autonomous underwater vehicle through deep reinforcement learning and disturbance observers

This paper investigates the application of deep reinforcement learning (RL) in the motion control for an autonomous underwater vehicle (AUV), and proposes a novel general motion control framework which separates training and deployment. Firstly, the state space, action space, and reward function are customized under the condition of ensuring generality for various motion control tasks. Next, in order to efficiently learn the optimal motion control policy in the case that the AUV model is imprecise and there are unknown external disturbances, a virtual AUV model composed of the known and determined items of an actual AUV is put forward and a simulation training method is developed on this basis. Then, in the given deployment method, three independent extended state observers (ESOs) are designed to deal with the unknown items in different directions, and the final controller is obtained by compensating the estimated value of ESOs into the output of the optimal motion control policy obtained through simulation training. Finally, soft actor-critic is chosen as deep RL algorithm of the framework, and the generality and effectiveness of the proposed method are verified in four different AUV motion control tasks.     

Switching fault-tolerant control of a moving vehicle-mounted flexible manipulator system with state constraints

In this brief, a switching fault-tolerant control (FTC) scheme is presented for a moving vehicle-mounted flexible manipulator subject to state constraints. The dynamic characteristics of the system are represented by coupled ordinary differential equations and partial differential equations (ODEs–PDEs). When actuators are healthy, vibration control and position regulations can be realized without violation of the given constraints based on a Barrier Lyapunov Function (BLF). Moreover, a switching strategy is introduced to prevent the transgression of constraints even under actuator failure by detecting actuator faults as-assisted by the proposed monitoring functions. The closed-loop states are kept within the given bounds under FTC laws. By extending LaSalle's Invariance Principle to an infinite dimension, the asymptotic stability of the fault-free closed-loop system is strictly verified. Simulation results demonstrate the effectiveness of the proposed approach.     

Biofunctionalized nanoslits for wash-free and spatially resolved real-time sensing with full target capture

We propose biofunctionalized nanofluidic slits (nanoslits) as an effective platform for real-time fluorescence-based biosensing in a reaction-limited regime with optimized target capture efficiency. This is achieved by the drastic reduction of the diffusion length, thereby a boosted collision frequency between the target analytes and the sensor, and the size reduction of the sensing element down to the channel height comparable to the depletion layer caused by the reaction. Hybridization experiments conducted in DNA-functionalized nanoslits demonstrate the analyte depletion and the wash-free detection ∼10 times faster compared to the best microfluidic sensing platforms. The signal to background fluorescence ratio is drastically increased at lower target concentrations, in favor of low-copy number analyte analysis. Experimental and simulation results further show that biofunctionalized nanoslits provide a simple means to study reaction kinetics at the single-pixel level using conventional fluorescence microscopy with reduced optical depth.     

Cooperative output feedback control of a mobile dual flexible manipulator

This paper addresses the cooperative output feedback control of a mobile dual flexible manipulator, which is mounted at a moving platform to grasp and move a rigid object. We derive the distributed parameter model with geometric constraints for the dual flexible manipulator system by utilizing the Lagrange multiplier method and the Hamilton’s principle, which avoids the problem of control spillover. This paper considers a case where the states of system are difficult to measure directly and exploits the high gain observer theory to design the state observers for estimating the unavailable states. Then the cooperative output feedback control scheme is developed by the Lyapunov’s method, which enables the cooperative control of the flexible manipulator system. Furthermore, under the cooperative output feedback control scheme, we prove that the states of the system are uniformly bounded. Finally, the feasibility of the designed cooperative output feedback controllers is verified by numerical simulation.     

Hybrid position/force control of a flexible parallel manipulator

In this paper, simultaneous position/force control of a closed-chain planar manipulator with the last link flexible is studied when the manipulator is in contact with an environment. The proposed manipulator consists of a flexible link connected to three rigid linkages whichare optimized for kinematic and force manipulability in the region of interest. The flexible link is modeled as a series of rigid links connected by virtual torsion springs. A hybrid position/force control algorithm is developed and implemented on the manipulator. Experimental results are presented to verify the performance of the controller.     

Multi-objective output feedback control for autonomous spacecraft rendezvous

In this paper, the problem of robust output feedback control for a class of spacecraft rendezvous systems is investigated, which contains parameter uncertainty, external disturbance, poles assignment, _H∞-norm$H_{\infty }\mathrm{-}\mathrm{norm}$, variance and input constraints. The aim of this problem is to design a dynamic output feedback controller such that the closed-loop poles are placed within a specified disc, the _H∞$H_{\infty }$ norm of the transfer function from disturbance to output is ensured to be less than a prespecified disturbance attenuation level, the steady-state variance for each state of spacecraft rendezvous system is guaranteed to be less than the prespecified individual upper bound, and the actual control input is confined into a certain range simultaneously. Based on the Lyapunov theory, the existence conditions of such controller are derived in terms of linear matrix inequalities (LMIs). An illustrative example is given to demonstrate the effectiveness of the proposed control design method.     

Prescribed performance adaptive control for an uncertain robotic manipulator with input compensation updating law

This paper investigates an adaptive prescribed performance control strategy with specific time planning for trajectory tracking of robotic manipulator subject to input constraint and external disturbances. By constructing an accumulated error vector embedded with a performance enhancement function and introducing an input auxiliary function, a specified-time control framework with built-in prescribed performance is further designed to ensure that the trajectory tracking performance. More particularly, the proposed control law is compatible with the control input saturation suppression algorithm, which is capable of improving the robustness of closed loop system. Under the framework of the proposed control strategy, it is proved by theory that all the signals in the closed-loop system are bounded, and moreover the tracking error can reach the exact convergence domain in a given time. At last, a numerical example is presented to indicate the feasibility and effectiveness of the proposed method.     

Dual terminal sliding mode control design for rigid robotic manipulator

This paper proposes a dual terminal sliding mode control scheme for tracking tasks of rigid robotic manipulators. As a significant novelty, the presented design technique integrates the individual sliding mode surfaces to achieve the finite time convergence of tracking errors utilizing specially designed construct, and accordingly the convergence time is easily obtained due to the integral design. The underactuated issue and input limitation are specially considered in this paper, i.e., the underactuated issue is solved by introducing the hierarchical methodology into the basic dual sliding mode controller. The proposed method can easily combine with the adaptive technique to eliminate the negative effect caused by the input limitation in the rigorous stability analysis. These newly proposed methods also have the characteristics of nonsingularity and chattering suppression, and the effectiveness and high efficiency are verified by stabilizing the motions of the overhead crane and the tracking tasks of the rigid robotic manipulator. Simulation results validate the theoretical analyses about the proposed method.     

Intelligent control for robotic manipulator with adaptive learning rate and variable prescribed performance boundaries

The purpose of this study is to enhance the transient performance and mitigate the possible boundary-crossing issue during the design of a neural network-based intelligent prescribed performance control for robotic manipulators that suffer from input saturation. Initially, an auxiliary system is created utilizing the saturation signal, which is then used to modify the prescribed performance boundaries when saturation takes place. This ensures that the tracking errors adhere to the performance constraints even if the available control effort is limited. To further enhance the transient performance of the closed-loop system, a composite learning-based online identification scheme employing a Gaussian function to adaptively adjust the learning rate is utilized instead of a fixed-learning-rate weight updating law to train the neural network. This approach facilitates the reduction of the undesired weight oscillations at the beginning of the control process when the neural network is not sufficiently trained. Lastly, the stability of the closed-loop system is demonstrated by applying the Lyapunov approach, and simulation results support the effectiveness of the identification and control schemes proposed in this study.     

Predefined-time control for free-floating space robots in task space

This work mainly studies the position and attitude tracking control of a free-floating space robot. With the attitude represented in modified Rodrigues parameters (MRPs), a task-space controller with predefined-time stability is developed considering the external disturbance. The tuning parameters of a predefined-time controller can be formulated as functions of the prescribed upper bound of the stabilization time. Based on the backstepping technique and a novel predefined-time stabilizing function, a predefined-time control scheme is designed for the space robot system. Moreover, to avoid ’explosion of terms’, an auxiliary variable is introduced such that the controller is independent of the derivative of the virtual control law. Numerical simulations are presented to demonstrate the effectiveness of the proposed method.     

基于模糊控制的机械臂控制系统设计与实现

文章针对传统机械臂操作过程中存在的问题,设计一种解决机械手操作的控制系统,该系统能够适应机械手操作过程中灵活多样的轨迹路线和操作动作的应用需求。实现对机械手操作过程的精确控制,并能够根据机械手操作过程中所处的位置以及操作运动轨迹,实时的调整机械手的运动路线。     

Adaptive backstepping trajectory tracking control of robot manipulator

An adaptive backstepping control scheme is proposed for task-space trajectory tracking of robot manipulators in the presence of uncertain parameters and external disturbances. In the case of external disturbance-free, the developed controller guarantees that the desired trajectory is globally asymptotically followed. Moreover, taking disturbances into consideration, the controller is synthesized by using adaptive technique to estimate the system uncertainties. It is shown that L₂ gain of the closed-loop system is allowed to be chosen arbitrarily small so as to achieve any level of L₂ disturbance attenuation. The associated stability proof is constructive and accomplished by the development of a Lyapunov function candidate. Numerical simulation results are included to verify the control performance of the control approach derived.     

Circular formation control for cooperative target tracking with limited information

This paper addresses the problem of encircling and tracking a moving target with a fleet of unicycle-like vehicles. A new control law is developed to steer the vehicles to an evenly spaced formation along a circumference, the center of which tracks the motion of the target. The strategy proposed relies only on the relative positions of the agents with respect to the target, expressed in the local frame of each vehicle. The absolute position, velocity and acceleration of the target are unknown. Additionally, the robustness of the proposed control law in the presence of external disturbances is analyzed. Communication among agents is used to maintain the vehicles equally spaced in the circular formation. Simulation results illustrate the effectiveness of the proposed strategies.     

New modeling approach of secondary control layer for autonomous single-phase microgrids

In a microgrid (MG) topology, the secondary control is introduced to compensate for the voltage amplitude and frequency deviations, mainly caused by the inherent characteristics of the droop control strategy. This paper proposes an accurate approach to derive small signal models of the frequency and amplitude voltage at the point of common coupling (PCC) of a single-phase MG by analyzing the dynamics of the second-order generalized integrator-based frequency-locked loop (SOGI-FLL). The frequency estimate model is then introduced in the frequency restoration control loop, while the derived model of the amplitude estimate is introduced for the voltage restoration loop. Based on the obtained models, the MG stability analysis and proposed controllers’ parameters tuning are carried out. Also, this study includes the modeling and design of the synchronization control loop that enables a seamless transition from island mode to grid-connected mode operation. Simulation and practical experiments of a hierarchical control scheme, including traditional droop control and the proposed secondary control for two single-phase parallel inverters, are implemented to confirm the effectiveness and the robustness of the proposal under different operating conditions. The obtained results validate the proposed modeling approach to provide the expected transient response and disturbance rejection in the MG.     

Robust visual servoing control for quadrotors landing on a moving target

In this paper, a robust visual servoing control approach is proposed to address the landing problem for quadrotors on a moving platform. A vision system is implemented to estimate the position and velocity of the quadrotor. A robust cascade controller is proposed by following backstepping-like fundamentals and robust compensating theory. The effects of time-varying uncertainties, including parameter uncertainties and external disturbances, and time-varying delays resulted from image acquisition, image processing, and sensor measurement delays can be restrained. Experimental results using a quadrotor to land on a ground moving target illustrate the effectiveness of the proposed approach.     

Formation control for a string of interconnected second-order systems via target feedback

This paper investigates the formation control of interconnected second-order systems. Each agent is assumed to be capable of measuring its own absolute velocity and the relative positions with respect to its neighboring agents, whereas the target formation is described by absolute positions of all agents in a global coordinate. For such formation control problems, no distributed control policy was reported in existing literature. This paper focuses on the string connection structure of the agents and proposes a distributed control policy that takes the form of purely state feedback without incorporating any feed-forward component. The closed-loop system equation is characterized by an oscillation matrix whose entries are the feedback controller gains. Formation control is accomplished by formulating the agents’ target positions as feedback controller gains. Moreover, it is shown that for agent models described by double integrators, each of the agents located at the two endpoints of the string structure should know its own absolute position. For a class of agent models where each agent’s acceleration depends on its own position, the control laws do not need to use the absolute position. For both system models, the target formations that are asymptotically reachable by the proposed control laws are specified explicitly. Numerical simulations have been conducted to illustrate the effectiveness of the theoretical results.