Ji-Hong Li

Technical communique: Point-to-point navigation of underactuated ships

This paper considers point-to-point navigation of underactuated ships where only surge force and yaw moment are available. In general, a ships sway motion satisfies a passive-boundedness property which is expressed in terms of a Lyapunov function. Under this kind of consideration, a certain concise nonlinear scheme is proposed to guarantee the closed-loop system to be uniformly ultimately bounded (UUB). A numerical simulation study is also performed to illustrate the effectiveness of the proposed scheme.

Neural net based nonlinear adaptive control for autonomous underwater vehicles

Since the dynamics of autonomous underwater vehicles (AUVs) are highly nonlinear and their hydrodynamic coefficients vary with different operating conditions, a high performance control system of an AUV is needed to have the capacities of learning and adaptation to the variations of the AUV dynamics. In this paper, a linearly parameterized neural network is used to approximate the uncertainties of the vehicle dynamics, where the basis function vector of the network is constructed according to the vehicle physical properties. The proposed controller guarantees uniform boundedness of the vehicle trajectory tracking errors and network weights estimation errors based on the Lyapunov stability theory, where the network reconstruction errors and disturbances in the vehicle dynamics are bounded by an unknown constant. Numerical simulation studies are performed to illustrate the effectiveness of the proposed control scheme.

Multivariable optimal control of an autonomous underwater vehicle for steering and diving control in variable speed

This paper describes a multivariable optimal control for a Semi-Autonomous Underwater Vehicle (SAUV) developed in Korea Ocean Research and Development Institute (KORDI). The SAUV is a test-bed for evaluation of navigation algorithms and manipulator technologies for a mine disposal vehicle (MDV) in military use and for a light working underwater vehicle in scientific application. The vehicle was designed to control its cruising speed, heading and depth with 4 horizontal thrusters installed at the rear of the hull. The decoupled control methods are limited to be applied to the SAUV because the thrust forces are highly coupled with the surging, yawing, and pitching motion of the vehicle. The multivariable Linear Quadratic (LQ) control method is chosen to control steering and diving in variable speed motion automatically. This paper presents the results of tank-test with the controller and compares them with the simulation results to validate the performance.

Motion control of an AUV using a neural network adaptive controller

This paper presents a neural network adaptive controller for autonomous underwater vehicles (AUVs). A linearly parameterized neural network (LPNN) is used to approximate the nonlinear uncertainties of AUV dynamics, where the basis function vector of LPNN is constructed according to the physical properties of the AUV. A sliding mode control scheme is adopted to attenuate the effects of network reconstruction errors and disturbances in AUV dynamics. The asymptotic convergence of AUV tracking errors and the stability of the presented control system are guaranteed on the basis of Lyapunov theory. Numerical simulation studies for motion control of an AUV are performed to illustrate the effectiveness of the proposed controller.

Navigation and Control System of a Deep-sea Unmanned Underwater Vehicle 'HEMIRE'

This paper presents a hybrid underwater navigation and control system for positioning, guidance and control of a deep-sea unmanned underwater vehicle (UUV), HEMIRE. For precise navigation of the UUV, the hybrid navigation system is designed based on strap-down IMU (inertial measurement unit) accompanying with USBL (ultra-short base line), DVL (Doppler velocity log), range sonar, depth and heading sensors. Initial localization and position reference of the UUV are performed with the USBL when the vehicles are in stationary condition. This paper also presents the characteristics of the UUV and the system constitution of the surface control unit. HEMIRE is equipped with two hydraulic manipulators, ORION, which are remotely controlled at the surface vessel via fiber optic communication. An operator can control the manipulators with a workspace-controlled master arm as well as a parallel-type master arm. This paper describes the task-oriented control of the tele-operated robotic arms mounted on HEMIRE and its application to task-oriented joint configurations.

Stable nonlinear adaptive controller for an autonomous underwater vehicle using neural networks

In general, the dynamics of autonomous underwater vehicles (AUVs) are highly nonlinear and their hydrodynamic coefficients vary with different operating conditions. For this reason, high performance control system for an AUV usually should have the capacities of learning and adaptation to the time-varying dynamics of the vehicle. In this article, we present a robust adaptive nonlinear control scheme for an AUV, where a linearly parameterized neural network (LPNN) is introduced to approximate the uncertainties of the vehicles dynamics, and the basis function vector of the network is constructed according to the vehicles physical properties. The proposed control scheme can guarantee that all of the signals in the closed-loop system are uniformly ultimately bounded (UUB). Numerical simulation studies are performed to illustrate the effectiveness of the proposed control scheme.

An adaptive nonlinear controller for diving motion of an AUV

This paper presents an adaptive nonlinear controller for diving control of an autonomous underwater vehicle (AUV). So far, diving dynamics of an AUV has often been derived under various assumptions on the motion of the vehicle. Typically, the pitch angle of AUV has been assumed to be small in the diving plane. However, these kinds of assumptions may induce large modeling errors and further may cause severe problems in many practical applications. In this paper, through a certain simple modification, we break the above restricting condition on the vehicles pitch angle during diving motion so that the vehicle could take free pitch motion. Proposed adaptive nonlinear controller is designed by using a traditional backstepping method. Finally, numerical studies are presented to illustrate the effectiveness of proposed control scheme, and some practical features of the control law are also discussed.

Asymptotic diving control method for torpedo-type underactuated AUVs

This paper considers diving control problems for underactuated autonomous underwater vehicles (AUVs) with only surge force and pitch moment available for its 3D vertical motion. By introducing certain two polar coordinates transformations, the vehicles kinematics and dynamics can be reduced to a certain two-input-two-output (TITO) second-order nonlinear strict-feedback form, upon which the proposed control scheme is derived using general backstepping method. To avoid possible singularity problem in the recursive control design, we introduce an asymptotic modification of orientation concept instead of taking the velocity term as a virtual control input. Proposed diving scheme guarantees asymptotic stability of the position tracking error as well as the velocity and pitch angle tracking errors in the polar frame. And the same tracking property of velocity and pitch angle in the Cartesian frame is also discussed. Numerical simulation studies are also carried out to illustrate the effectiveness of proposed control scheme.

Schooling for Multiple Underactuated AUVs

In the past few decades, autonomous underwater vehicles (AUVs) have been playing one of most important roles in the applications ranging from scientific research, survey to industry and military operations. Today, there is an apparent trend that more and more underwater tasks are carrying out by cooperative operations of multiple AUVs instead of traditional method of using single AUV (Soura & Pereira, 2002; Edwards et al., 2004; Guo et al., 2004; Watanabe & Nakamura, 2005; Fiorelli et al., 2006). Multiple AUVs have cost-effective potential. However, a number of research efforts are still remained to be done before this advanced technology can be fully applied in the practice. And one of the efforts is about the efficient schooling scheme for these multiple underwater vehicles. The history of the formation or cooperative control of multiple agent systems can be traced back to the 1980’s. Reynolds (1987) introduced a distributed behavioural model for flocks of birds, herds of land animals, and schools of fishes. This model can be summarized as three heuristic rules: flock centring, collision avoidance and velocity matching. In the formation algorithm (Reynolds, 1987), each dynamic agent was modelled as certain particle system – a simple double-integrator system. This kind of agent model has been inherited in most of the following research works (Leonard & Fiorelli, 2001; Olfati-Saber & Murray, 2002, 2003; Fiorelli et al., 2006; Olfati-Saber, 2006; Do, 2007). Besides these works, another type of linear model was used in Smith et al. (2001), and certain nonlinear model was applied for underwater vehicles (Dunbar & Murray, 2002) and for wheel robots with terminal constraints (Fax & Murray, 2004). In both of Dunbar & Murray (2002) and Fax & Murray (2004), the nonlinear dynamics were all fully actuated. In this chapter, we consider the schooling problem for multiple underactuated AUVs, where only three control inputs surge force, stern plane and rudder are available for each vehicle’s six degrees of freedom (DOF) motion. For these torpedo-type underwater flying vehicles, since there are non-integrable constraints in the acceleration dynamics, the vehicles do not satisfy Brockett’s necessary condition (Brockett et al., 1983), and therefore, could not be asymptotically stabilizable to an equilibrium point using conventional time-invariant continuous feedback laws (Reyhanoglu, 1997; Bacciotti & Rosier, 2005). Moreover, these vehicles’ models are not transformable into a drift-less chained form (Murray & Sastry, 1993), so the tracking method proposed in Jiang & Nijmeiner (1999) cannot be directly applicable to these vehicles. Recently, quite a number of research works have been carried out on the tracking of underactuated surface ships (Jiang, 2002; Do et al., 2002a, 2002b, 2004, 2005; Pettersen & Nijmeijer, 2001; Fredriksen & Pettersen, 2006). However, the presented O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

Formation Control of a Group of Underactuated Autonomous Underwater Vehicles

This paper presents an asymptotic formation control scheme for a group of underactuated autonomous underwater vehicles (AUVs) where only three control inputs - surge force, yaw moment and pitch moment are available for each vehicle`s six degree of freedom (DOF) underwater motion. Usually, the dynamics agents applied in most of the formation algorithms presented so far have been modeled as particle systems, which is a simple double-integrator system. Therefore, these algorithms cannot be directly applicable to the practical systems, especially to the underwater vehicles whose dynamics are highly nonlinear. Moreover, the vehicles considered in this paper are underactuated. The formation control is derived using general potential function method, and the corresponding potential function consists of two parts: interactions between vehicles and virtual-leader following. Proposed formation scheme guarantees asymptotic local stability of closed-loop system. Numerical simulations are carried out to illustrate the effectiveness of proposed formation scheme.