Immersion and invariance adaptive tracking control for robot manipulators with a novel modified scaling factor design

The robot manipulators' tracking control problem in the presence of inertia uncertainties is addressed in this paper, and a novel dynamic scaling–based immersion and invariance (I&I) adaptive tracking controller is utilized to stabilize the proposed system. By virtue of the reconstruction method of the parameter regression matrix, this paper provides a new perspective on how to overcome the integrability obstacle typically arising in the I&I controller design through dynamic scaling and presents a new controller design method. What is more, a novel modified scaling factor is proposed as well so that the controller can be implemented without the prior knowledge of the inertia matrix's lower bound, and only the saturation function involving the scaling factor is included in the feedback gains. Finally, the numerical simulations show the validity of the proposed controller.     

Adaptive robust output feedback control for attitude tracking of quadrotor unmanned aerial vehicles

This work proposes a new adaptive robust output feedback control method for attitude reference tracking of a quadrotor unmanned aerial vehicle without using the angular velocity measurements. By using the K-filters well known in the adaptive control community, the necessity of velocity measurements or estimating is avoided. The attitude system model is transformed into a second-order model where the angular velocity measurements are not involved. However, the model includes mismatched uncertainties which should be estimated and compensated by the disturbance observers (DOBs). The controller is designed in a backstepping manner, and the dynamic surface technique is adopted to avoid the explosion of the controller complexity. For each Euler angle axis, the prescribed performance control technique is adopted to ensure a prescribed performance, the lumped disturbance is compensated by a DOB, and furthermore an adaptive law is introduced to adaptively update the corresponding uncertain inertia parameter which affects the control performance significantly. The control performance of the overall control system is analyzed rigorously from the viewpoint of input-to-state practical stability. In addition, it is shown how the adaptive laws contribute to improving the control performance. And simulation examples are provided to demonstrate the performance of the proposed method.     

无角速度测量的姿态跟踪动态PD控制

针对太阳帆板展开过程中存在系统切换和外部未知干扰的航天器姿态跟踪控制问题,提出了角速度可测和角速度不可测的姿态跟踪自适应动态比例微分(PD)控制器。本文先设计自适应更新律补偿外部复合干扰,提出了姿态角及角速度全状态可测的自适应PD控制器;接着针对角速度不可量测,基于无源控制理论给出估算角速度的动态观测器,提出一种仅有姿态角跟踪误差信息的变增益动态PD控制器,并理论证明了闭环系统的全局渐近稳定性;数值仿真验证了变增益动态PD控制器对太阳帆板展开过程中,航天器的姿态跟踪控制的鲁棒性和有效性。     

Distributed adaptive neural network fixed-time leader-follower attitude consensus control for multiple rigid spacecraft

In this paper, the problem of fixed-time attitude consensus control is addressed for a group of rigid spacecraft in the presence of inertia uncertainties and external disturbances. By applying the adaptive technique and neural network approximation technique to handle the disturbances and uncertainties, an adaptive neural network-based distributed protocol is proposed to achieve attitude consensus control for multiple rigid spacecraft. The proposed distributed attitude consensus protocol is composed of a group of distributed fixed-time observers for followers to estimate the leader's information and an adaptive neural network-based fixed-time sliding mode control law to realize attitude tracking control. Rigorous proofs are provided to demonstrate that the estimation errors of the proposed observers are convergent in a fixed time. Further, it is also proven that attitude tracking errors reach some adjustable regions in a fixed time under the proposed attitude consensus protocol. Numerical simulations are conducted to illustrate the performance of the proposed distributed attitude consensus protocol.     

Anti-unwinding adaptive attitude tracking control for spacecraft with quantized torques

The adaptive attitude tracking control with limited communication to actuators is addressed in this paper. To avoid unwinding, a rotation matrix rather than a quaternion is used to describe the attitude, for which the stability is proved by Morse-Lyapunov function. To meet the need of restricted communication, two different quantizers, logarithmic quantizer and hysteres quantizer, are used to quantize the control torque signal. Two robust adaptive control techniques, indirect and direct, are proposed to deal with the impacts of quantization error and external disturbances. The proposed control schemes, in conjunction with quantizers, guarantee the global boundedness of all signals in the closed-loop system, allowing the attitude tracking error to converge toward an ultimately bounded region. Finally, numerical simulations are conducted to illustrate the performance of the proposed controllers.     

Output feedback adaptive fault-tolerant compensation tracking control for linear systems based on the closed-loop reference model

This paper investigates the problem of output feedback adaptive compensation tracking control for linear systems subject to external disturbances and actuator failures including loss of effectiveness faults and bias faults. The impact of actuator faults on the transient performance of systems can be mitigated predicated on the closed-loop reference model with an additional degrees of design freedom. Using the estimation information provided by the adaptive mechanism, an output feedback adaptive fault-tolerant control strategy is developed to track closed-loop reference model systems. It is shown that all the signals of the resulting closed-loop system are bounded. Finally, simulation results are given to demonstrate the effectiveness of the proposed fault-tolerant tracking control method.     

挠性航天器姿态机动和振动抑制的自适应控制

针对挠性航天器姿态机动控制中存在的参数不确定性、外部干扰、挠性附件振动及挠性模态不易直接测量的问题,提出一种具有干扰抑制的自适应输出反馈机动控制器设计方法.设计中无需忽略挠性附件和中心刚体的耦合,利用挠性附件固有物理特性构造一种结构简单的开环模态观测器,然后用以此获得的模态估计信息及可测量的姿态四元数和角速度信息,基于...     

Adaptive fault‐tolerant attitude tracking control for spacecraft formation with unknown inertia

In this paper, an adaptive fault‐tolerant attitude coordinated tracking problem for spacecraft formation is investigated under a directed communication topology containing a spanning tree with the leader as the root, where inertia matrices and external disturbances are unknown time‐varying. With no prior knowledge of faults and inertia, an adaptive approach is proposed to reject the influence of disturbances and uncertainties. Meanwhile, combining with a consensus algorithm and graph theory, an adaptive fault‐tolerant attitude synchronization tracking control law is presented to regulate the attitude to a common time‐varying reference state. Aiming at optimizing the control law, a dynamic adjustment function is introduced to adjust the control gain according to the attitude tracking error. The effectiveness of the proposed control approach is demonstrated through simulation results.     

Adaptive fault-tolerant tracking control for nonlinear systems with unknown control coefficient and input saturation

In this article, the tracking control problem is investigated for a class of nonlinear systems in the presence of unknown disturbance, input saturation, actuator fault, and unknown control coefficient. A novel disturbance observer-based adaptive fault-tolerant tracking control strategy is proposed with regard to nonlinear systems. Based on the Gaussian error function, the auxiliary dynamic system is designed to offset effects caused by the input saturation. Moreover, the Nussbaum-type function is employed to avert control singularity and deal with the unknown control coefficient. A theoretical analysis indicates that the boundedness of all signals in the closed-loop system can be guaranteed. Finally, two examples with one concerning the dynamic point-the-bit rotary steerable drilling tool system are given to confirm the validity of the method.     

Output feedback control of supercapacitors parallel charging system for EV applications: Theoretical design and experimental validation

In this paper, the problem of controlling parallel charging system with supercapacitors for electric vehicle applications is considered. When the vehicle parks at the station, the charging process of supercapacitors needs to be completed in less than 30 seconds. The control objective is then to tightly regulate the supercapacitors state of charge (SOC) to a given reference constant and to ensure an adequate current sharing between different parallel chargers. Indeed, the current sharing is a critical issue for parallel charging system with supercapacitors, which is a nonlinear system with control inputs constraints. Besides, the SOC depends on the supercapacitors internal voltage, which is not accessible for measurement. Therefore, based on a large‐signal model of the parallel‐chargers‐supercapacitors system, an output feedback controller (combining a state observer and a nonlinear control laws) is designed. The controller is formally shown to meet all objectives, namely, closed‐loop stability, SOC reference tracking, and equal current sharing. The effectiveness of the proposed output feedback controller approach is verified both by simulation and by experimental tests.     

Online optimal and adaptive integral tracking control for varying discrete-time systems using reinforcement learning

Conventional closed-form solution to the optimal control problem using optimal control theory is only available under the assumption that there are known system dynamics/models described as differential equations. Without such models, reinforcement learning (RL) as a candidate technique has been successfully applied to iteratively solve the optimal control problem for unknown or varying systems. For the optimal tracking control problem, existing RL techniques in the literature assume either the use of a predetermined feedforward input for the tracking control, restrictive assumptions on the reference model dynamics, or discounted tracking costs. Furthermore, by using discounted tracking costs, zero steady-state error cannot be guaranteed by the existing RL methods. This article therefore presents an optimal online RL tracking control framework for discrete-time (DT) systems, which does not impose any restrictive assumptions of the existing methods and equally guarantees zero steady-state tracking error. This is achieved by augmenting the original system dynamics with the integral of the error between the reference inputs and the tracked outputs for use in the online RL framework. It is further shown that the resulting value function for the DT linear quadratic tracker using the augmented formulation with integral control is also quadratic. This enables the development of Bellman equations, which use only the system measurements to solve the corresponding DT algebraic Riccati equation and obtain the optimal tracking control inputs online. Two RL strategies are thereafter proposed based on both the value function approximation and the Q-learning along with bounds on excitation for the convergence of the parameter estimates. Simulation case studies show the effectiveness of the proposed approach.     

Adaptive interconnection and damping assignment passivity-based control for linearly parameterized discrete-time port controlled Hamiltonian systems via I&I approach

In this paper, discrete-time adaptive control of linearly parameterized fully actuated Port-controlled Hamiltonian systems with parameter uncertainties in energy function is considered. A discrete-time adaptive interconnection and damping assignment passivity-based control (IDA-PBC) method, utilizing the immersion and invariance (I&I) approach, for the considered uncertain Hamiltonian system, is presented. A discrete-time parameter estimator based on the immersion and invariance approach is derived to obtain an automatic tuning mechanism for the IDA-PBC controller. The stability analysis for the estimator and the closed-loop system is done using the Lyapunov theory. The proposed method is applied to two fully actuated physical systems and its performance is tested by simulations. Simulation results show that the proposed I&I-based adaptive IDA-PBC controller successfully preserves the performance of the IDA-PBC controller designed with true parameters under a large amount of uncertainty.     

一种船舶清洗ROV姿态控制方法研究与实现

为了减少因海生物附着形成污底对船舶航行造成的阻力,提高船舶的运输效率,研究设计了一种基于六推进器的船舶清洗ROV;首先对该机器人进行了相应软硬件方案设计,且依据实际应用需求选择了机器人驱动与测量元件,进而使用Solidworks三维机械制图软件完成了ROV结构外形设计,同时对ROV样机进行了结构组装与系统测试;同时在此基础上,为了提高船舶清洗ROV姿态控制过程的性能指标,提出一种改进型变积分PID控制算法,根据偏差量的变化将整个姿态控制过程规划为不同阶段,通过调节积分项的开关量系数以满足不同阶段的需求;最后通过MATLAB仿真软件对改进型ROV姿态控制系统进行仿真并完成实际水池实验,通过设定不同目标角度测试控制系统的性能,结果表明,该算法比传统单闭环与双闭环PID控制算法具有更短的过渡时间及更加优良的稳定性,是一种稳定高效的ROV姿态控制方式。     

提高燃煤机组调频调峰性能的综合控制技术

为了应对电网对燃煤机组并网性能指标的考核,深入优化燃煤机组的并网性能,提出了基于理论分析与试验技术相结合的燃煤机组综合优化方案。该方案在全面分析了影响燃煤机组并网性能因素的基础上,通过采用汽轮机调节阀特性参数测试及整定优化、基于分项动态前馈技术的协调控制优化、综合一次调频优化和主蒸汽温度控制优化4项技术使燃煤机组的调频调峰性能达到最优化。在600MW机组的应用结果表明,该综合优化方案可有效提高机组的并网性能指标。