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Haibo Liu,Junwei Wang,Yan Ji 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.8
Maximum likelihood methods have wide applications in system modeling and parameter estimation. For the purpose of improving the precision of parameter estimation, this paper presents a maximum likelihood recursive generalized extended least squares (ML-RLS) algorithm for a bilinear-parameter system with autoregressive moving average noise based on the over-parameterization identification model. An over-parameterization-based recursive generalized extended least squares algorithm is presented to show the effectiveness of the proposed ML-RLS algorithm for comparison. The simulation test shows that the proposed algorithm has a higher estimation accuracy than the recursive least squares algorithm.
Chen Zhang,Haibo Liu,Yan Ji 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.5
This paper studies the maximum likelihood identification problems of the bilinear-in-parameter outputerror systems with colored noise. A hierarchical maximum likelihood gradient-based iterative (H-MLGI) algorithm, a filtering hierarchical maximum likelihood gradient-based iterative (F-H-MLGI) algorithm and a filtering hierarchical maximum likelihood multi-innovation gradient-based iterative (F-H-ML-MIGI) algorithm are developed for a bilinear-in-parameter output-error system by using the data filtering technique and multi-innovation identification theory. The analysis shows that compared with the H-MLGI algorithm, the F-H-MLGI algorithm can improve the parameter estimation accuracy. Additionally, the F-H-ML-MIGI can give more accurate parameter estimates than the F-H-MLGI algorithm and can track time-varying parameters based on the dynamical window data. The performances of the proposed identification algorithms are illustrated through simulation example.
Adaptive IBVS and Force Control for Uncertain Robotic System with Unknown Dead-zone Inputs
Sihang Zhang,Haibo Ji,Hepeng Zhang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.4
This article introduces a novel control strategy for the uncertain eye-to-hand system, which is considered to work with unknown model of constraint surface and uncalibrated camera model. Besides, the uncertain dynamics and kinematics are also included in the system. In order to be closer to the real robot system, we also consider it withdead-zone inputs situation. So the parameter intervals and slopes of the dead-zone model is also unknown. Hence, anovel adaptive image-based visual servoing (IBVS) and force control approach is put forward. The control methodof unknown force and uncalibrated camera model is achieved by adaptive control. The solution of unknown deadzone inputs is completed by designing a inverse smooth model of dead-zone inputs to offset the nonlinear affect due to the actuator constraint, and the whole system is proved that the force tracking control and image position converge to zero asymptotically. Finally, the MATLAB simulation is set up and the experiment shows the validity of the proposed scheme.
Robust Control Design of A Class of Nonlinear Systems in Polynomial Lower-Triangular Form
Bing Wang,Haibo Ji,Jin Zhu 제어·로봇·시스템학회 2009 International Journal of Control, Automation, and Vol.7 No.1
This paper investigates the problem of global robust stabilization for a wide class of nonlinear systems, called polynomial lower-triangular form (pLTF), which expands LTF to a more general case. The aim is explicitly constructing the smooth controller for the class of systems with static uncertainties, by adding and modifying a power integrator in a recursive manner. The pLTF relaxes the restrictions on the structure of the normal LTF and enlarges the family of systems that are stabilizable. Examples are also provided to show the practical usage of this class of systems and the effectiveness of the design method.
A 3-prismatic-revolute-spherical compliant parallel platform for optoelectronic packaging
Hongwei Xu,Haibo Zhou,Shuaixia Tan,Zhiping Kong,Ji-An Duan 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.6
To align the optical channels of optoelectronic appliances, a 3-prismaticrevolute-spherical (3-PRS) compliant parallel platform (CPP) is proposed in this work. The platform has special large stroke compliant joints. Attention is paid to the establishment of the inverse kinematics model and the analysis of the parasitic motion (PM) of the platform. A prototype of the platform is also presented, and its accuracy is experimentally evaluated. Besides, the platform is employed as a 3 degree-of-freedom (DOF) platform for optoelectronic packaging. Furthermore, the closed-loop control strategy requires merely one optical power meter to avoid the use of complex multiple DOF detection devices. In this respect, the influence of the precision of inverse kinematics solution on the optoelectronic packaging is reduced. Moreover, a compensation rule is employed to minimize the effect of PM on the motion accuracy of the platform. The results show that the proposed 3-PRS CPP is highly efficient for optoelectronic packaging.
Robust Control for Spacecraft Rendezvous with Disturbances and Input Saturation
Yi-Ke Ma,Haibo Ji 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.2
This paper deals with the stabilization problem of spacecraft rendezvous in the presence of disturbances and input saturation. A dead zone operator based model is used to describe the saturation phenomenon. By using Lyapunov method, two groups of control laws are obtained, which ensure the input-to-state stability and the input-to-state practical stability of the closed-loop systems respect to disturbance acceleration, respectively. Simulation results are provided to illustrate the effectiveness of the proposed approaches.
Adaptive Sliding Mode Based Disturbance Attenuation Tracking Control for Wheeled Mobile Robots
Kang Liu,Hongbo Gao,Haibo Ji,Zhengyuan Hao 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.5
This paper is devoted to investigating a composite controller for wheeled mobile robots in the presence of external disturbance and parametric uncertainty. Unlike the traditional backstepping technique existing the impractical velocity jumps, the proposed neural dynamic model has the ability to generate smooth continuous signals. Subsequently, a disturbance observer based adaptive sliding mode dynamic controller is introduced to estimate disturbances online, adjust control gain automatically and eliminate chattering phenomena completely. Under the developed control law, the ultimate boundedness of all signals is guaranteed and the tracking errors can be arbitrarily small in finite time. Simulation results are carried out to demonstrate the effectiveness of the proposed scheme.
Distributed Nash Equilibrium Seeking for Aggregative Games via Derivative Feedback
Yawei Zhang,Shu Liang,Haibo Ji 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.5
In this paper, we investigate a continuous-time distributed Nash equilibrium seeking algorithm for a class of aggregative games, with application to the real-time pricing demand response. To seek the Nash equilibrium via local communication among neighbors, by combining projected gradient dynamics and consensus tracking dynamics, we propose a novel distributed algorithm for the players. We prove the convergence of the distributed algorithm via a constructed Lyapunov function and the variational inequality technique, and show an illustrative simulation related to the energy consumption control in smart grids.