Xuzhi Lai

Comprehensive Unified Control Strategy for Underactuated Two-Link Manipulators

This paper presents a unified treatment of the motion control of underactuated two-link manipulators, including acrobots and pendubots. The motion space is divided into two areas: swing-up and attractive; and control laws are designed for each. First, a control law based on a weak-control Lyapunov function (WCLF) is employed to increase the energy of and control the posture of the actuated link in the swing-up area. Next, one parameter of the WCLF is chosen to be a nonlinear function of the state to avoid singularities. Then, another parameter of the control law is adjusted based on the state to improve the control performance. Finally, an optimal control law is designed for the attractive area. Stability is guaranteed in the swing-up area by the use of a WCLF based on LaSalles invariance principle. Moreover, the global stability of the control system is guaranteed by integrating the WCLF and a nonsmooth Lyapunov function.

An efficient neural network approach to tracking control of an autonomous surface vehicle with unknown dynamics

This paper proposes an efficient neural network (NN) approach to tracking control of an autonomous surface vehicle (ASV) with completely unknown vehicle dynamics and subject to significant uncertainties. The proposed NN has a single-layer structure by utilising the vehicle regressor dynamics that expresses the highly nonlinear dynamics in terms of the known and unknown dynamic parameters. The learning algorithm of the NN is simple yet computationally efficient. It is derived from Lyapunov stability analysis, which guarantees that all the error signals in the control system are uniformly ultimately bounded (UUB). The proposed NN approach can force the ASV to track the desired trajectory with good control performance through the on-line learning of the NN without any off-line learning procedures. In addition, the proposed controller is capable of compensating bounded unknown disturbances. The effectiveness and efficiency are demonstrated by simulation and comparison studies.

Stabilization of underactuated two-link gymnast robot by using trajectory tracking strategy

This paper concerns the stabilization of an underactuated two-link gymnast robot called acrobot. A trajectory tracking control strategy is presented. First, we carry out a homeomorphous coordinate transformation on the acrobot system that transforms it into a new simplified nonlinear system. And then, a desired motion trajectory is designed for the new system. Finally, we use an equivalent-input-disturbance (EID) method to design a controller that makes the new system asymptotically track the desired trajectory. This enables the acrobot to be swung up from the downward position and to be stabilized at the upright position. The proposed strategy changes the stabilization of the nonlinear acrobot system into that of a linear time-invariant error dynamic system with an artificial disturbance. And it uses a single controller to accomplish the motion control objective of the acrobot. These makes the strategy simple and efficient. Simulation results demonstrate its validity and its superiority over others.

Stable Control Strategy for Planar Three-Link Underactuated Mechanical System

A stable-control strategy for a planar three-link passive-active-active underactuated mechanical system not subject to gravity constraints has been devised. The control objective is to move the end effector from any initial position to any target position. First, a dynamic model of the system is built, and its properties are analyzed. Next, based on the complete integrability of an underactuated planar acrobot (UPA), the control of a planar three-link system is divided into two stages. In each stage, keeping the angle of one active link constant reduces the planar three-link system to a UPA, thereby enabling the use of quadrature to obtain the angle constraint relationships between the passive and active links. Then, the target angles associated with the target position are calculated by particle swarm optimization based on the angle constraint relationships. Finally, a controller for each stage is designed, ensuring that the control objective will be reached. Simulation results demonstrate the validity of this control method.

Singularity avoidance for acrobots based on fuzzy-control strategy

This paper presents a fuzzy-control method for the motion control of an acrobot. First, an explanation is given of the singularity that arises when a motion control law based on a Lyapunov function has an integrated control objective for energy and posture. Then, a fuzzy controller is designed that solves the singularity problem through regulation of a design parameter in the control law. Finally, an additional fuzzy controller is designed that improves the control performance through regulation of another design parameter in the control law. Simulation results demonstrate the effectiveness of this integrated fuzzy-control strategy.

A biologically inspired approach to tracking control of underactuated surface vessels subject to unknown dynamics

The tracking control problem of underactuated surface vessels is studied.A biologically inspired approach is proposed using backstepping, neurodynamics model and NN.The control algorithm is efficient as no time derivatives of virtual controls are needed.The NN learning algorithm derived from Lyapunov theory is computationally efficient.The control performance is shown to be faster and better than other approaches. In this paper, a novel biologically inspired approach is proposed for the tracking control of an underactuated surface vessel subject to unknown dynamics. The tracking control algorithm is first derived from the error dynamics analysis of the vessel using backstepping. Then, three shunting neural dynamics derived from biological membrane equation are employed to avoid the inherent complexity of numerical derivatives of virtual control signals in the backstepping design. A single-layer neural network (NN) is finally used to approximate the unknown dynamics including uncertain model parameters and hydrodynamics coefficients. Unlike some existing tracking methods for surface vessel whose control algorithms suffer from requiring high computational effort, the proposed tracking control algorithm is computationally efficient as no derivative calculations on virtual controls are required. In addition, it is capable of tracking any smooth trajectories without any prior knowledge of the dynamics parameters. The effectiveness and efficiency of the proposed control approach are demonstrated by simulation and comparison studies.

Motion planning and tracking control for an acrobot based on a rewinding approach

This paper concerns motion planning and tracking control for an acrobot. We first introduce an artificial friction torque in order to construct a downward trajectory, and rewind it to make an upward trajectory. Then, we combine the upward trajectory with a stabilizing trajectory to make a complete trajectory. Finally, we use the pole assignment method to design a tracking controller that makes the acrobot exponentially track the whole trajectory. This enables the acrobot to be swung up from the straight-down position and stabilized at the straight-up position. Unlike the most commonly used switching stabilization control methods, the strategy presented here features a single controller for motion control in the whole motion space. It is simple and efficient. Simulation results demonstrate the validity of the method.

A rewinding approach to motion planning for acrobot based on virtual friction

Based on the concept of kinematical controllability, we can decouple the trajectory planning of an acrobot into two steps: finding a path in a configuration space and time-scaling it. In this paper, we apply this concept and plan the swing-up motion of an acrobot based on its falling-down motion. First, the initial state of the acrobot is set to the unstable upright equilibrium position, and the movement from this state to the stable downward equilibrium position is produced by introducing an artificial damping torque. A method to obtaining an optimal damping torque is presented. Then, the reference trajectory for the swing-up motion is taken to be the reverse of the falling-down motion. The validity of this method is demonstrated through simulations.

A bioinspired neural dynamics-based approach to tracking control of autonomous surface vehicles subject to unknown ocean currents

This paper addresses the trajectory tracking control problem of an autonomous surface vehicle (ASV) subject to unknown ocean currents, where smooth and continuous velocity commands are desirable for safe and effective operation. A novel bioinspired approach is proposed by integrating three neural dynamics models into the conventional Lyapunov synthesis. The tracking controller is derived from the error dynamics analysis of the ASV and the stability analysis of the control system. A simple observer is proposed to estimate the unknown ocean currents, which only requires the position of the ASV. The overall control system under the controller and observer is rigorously proved to be asymptotically stable by a Lyapunov stability theory for cascaded systems. The most contribution is that the proposed tracking controller is capable of eliminating the sharp velocity jumps due to sudden tracking error changes and generating smooth and continuous control signals. In addition, it can deals with the situation with unknown ocean currents. The effectiveness and efficiency of the proposed approach are demonstrated through simulation and comparison studies.

BIOINSPIRED NEURODYNAMICS-BASED POSITION-TRACKING CONTROL OF HOVERCRAFT VESSELS

This paper proposes a novel bioinspired neurodynamics-based position-tracking control approach for hovercrafts, where smooth and continuous velocity commands are desirable for safe steering control. The control algorithm is derived from the tracking error dynamics by incorporating backstepping technique and neurodynamics model derived from biological membrane equation. The tracking error is proved to converge to a small neighbourhood of the origin by a Lyapunov stability theory. The proposed approach is capable of generating smooth and continuous control signals with zero initial velocities, dealing with the velocity-jump problem. In addition, it can track any sufficiently smooth-bounded curves with constant or time-varying velocities. The effectiveness and efficiency of the proposed approach are demonstrated by simulation and comparison results.