Guangcheng Ma

Robust tracking control of space robots using fuzzy neural network

This paper proposes for space robots a robust fuzzy neural network (FNN) controller, which does not require linear parameterization necessary for standard adaptive control of fixed-base robot manipulator. With suitable modifications, this FNN tracking controller can achieve high-precision position control. Simulation results of a two-link planar space robot verify the validity of the proposed RFNN controller in the presence of uncertainties.

Multiple satellite formation based on multi-agent

Formation flying of multiple satellites is an enabling technology for many future space science missions. This paper addresses the problem of formation control and coordination of multiple satellite formation flying systems. Several coordination strategies for satellite formation flying are discussed. A new coordination framework based on multi-agent with advantages of robustness, flexibility and realization is proposed which considers not only the control of relative motion but also the interactions among multiple satellites in the formation. An LQR controller is presented for relative position control of satellites formation and a two-satellite formation simulation analysis was performed to demonstrate and validate the efficacy of the scheme

Adaptive Robust Control of Space Robot in Task Space

This paper discuses the tracking control problem of free-floating space robot in Cartesian space. Based on the augmentation dynamic equation, a robust controller is proposed considering the model uncertainties and external disturbances, using Lyapunov direct method and dissipative theory, it is proved that the proposed controller can ensure the L2 gain from disturbance to tracking error is lower than the given index gamma. Simulation results show that the control method is valid

Fault Detection Filter Design for Networked Control Systems with Networked-Induced Delay

The problem of fault detection for networked control systems with time-delay is investigated. Attention is focused on the design of fault detection filter based on states observer, which guarantees a pre-specified Hinfin performance for the closed-loop system with respect to all energy-bounded input signals. Using LMI and Lyapunov function technology, sufficient conditions for existence of such filter is established in terms of linear matrix inequalities, upon which the design of admissible filter is cast into a convex optimization problem. The proposed approach can be further extended to uncertain networked control systems. The simulation results demonstrate that the method is effective and robust.

Robust Fault Detection of Networked Control Systems: An Improved LMJ Approach

The problem of robust fault detection filter design for networked control systems with time-delay and parameter uncertainty residing in a polytope is investigated. The filtering strategies are based on a new robust performance criteria derived from a new result of parameter-dependent Lyapunov stability condition, which exhibit less conservativeness than previous results in the quadratic framework. The designed filter guaranteeing a prescribed Hinfin noise attenuation level can be obtained from the solution of convex optimization problems since it is presented in terms of linear matrix inequalities (LMI). An iterative algorithm is developed to further refine the sub-optimal controller. Numerical examples are provided to illustrate that the proposed method is effective and robust.

Robust tracking control of space robot via neural network

This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties

A ground semi-physical simulator for satellite autonomous rendezvous and space robot capture

The architecture of a ground semi-physical simulator is proposed, which can test the methodologies of the satellite formation flying, autonomous rendezvous and docking, and space robot capture. There are five subsystems in the ground simulator: the console system, the translation system, the rotation system, the target system, and the vision system. The console system is the most important part in the underlying system, which generates control commands based on the control algorithm. The translation system and the rotation system simulate 6 DOF motion of the follower, and the target system simulates 6 DOF motion of the target. The vision system is included in the feedback block. Through the Ethernet, the whole closed-loop system is developed and the provided real-time network communication for the system is introduced

A nonlinear law for the short distance tracing controller of space robot

This paper describes a relative position and attitude control method for the final phase of an autonomous rendezvous and docking system. With the estimated data given for attitude and position control by a vision system output, a relative position control methods using a phase plane based nonlinear control law with thrusters as actuators and a relative attitude control scheme based on relative quaternion PD feedback method with flywheels as actuators will be given in this article. A detailed computer simulation is also shown to testify the results can achieve the request of space rendezvous and docking mission

Robust energy-to-peak filtering for uncertain systems based on sampled measurement

The problem of robust energy-to-peak filtering based on sampled measurement for uncertain systems is studied. Based on piecewise Lyapunov stability criterion, the sample interval dependent conditions for the existence of such filters are established, which are less conservative. The admissible filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities, which can be solved via efficient interior-point algorithms. Finally, a numerical example is provided to illustrate the effectiveness of the proposed techniques.

Delay-Dependent Robust Sampled-Data Stability for Markovian Jump Systems with Time-Delay

This paper considers robust stochastic stabilizability for a class of uncertain sampled-data systems with time-delay and randomly jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. The closed-loop system is a hybrid one defined on a hybrid time space and a sample space. The delay-dependent sufficient conditions on robust stochastic stabilizability for sampled-data control systems with Markovian jumping parameters are proposed using the stochastic Lyapunov-Krasovskii stability theory. The sampled-data control problems can be constructed through a set of coupled linear matrix inequalities. Finally, the numerical example is given to demonstrate the proposed techniques.