Z.P. Wang

Robust motion/force control of uncertain holonomic/nonholonomic mechanical systems

In this paper, robust control strategies are presented systematically for both holonomic mechanical systems and a large class of nonholonomic mechanical systems in the presence of uncertainties and disturbances. First, robust control strategies are presented for both kinds of systems using the bounds of system parameters, respectively. Then, adaptive robust control strategies are presented by tuning the parameter estimates online. Proportional plus integral feedback control is used for force control for the benefit of real-time implementation. The proposed control strategies guarantee that the system motion converges to the desired manifold with prescribed performance while the constraint force remains bounded.

Robust adaptive neural network control of uncertain nonholonomic systems with strong nonlinear drifts

In this paper, robust adaptive neural network (NN) control is presented to solve the control problem of nonholonomic systems in chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive NN control laws are developed using state scaling and backstepping. Uniform ultimate boundedness of all the signals in the closed-loop are guaranteed, and the system states are proven to converge to a small neighborhood of zero. The control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. The proposed adaptive NN control is free of control singularity problem. An adaptive control based switching strategy is used to overcome the uncontrollability problem associated with x/sub 0/(t/sub 0/)=0. The simulation results demonstrate the effectiveness of the proposed controllers.

Adaptive neural network control of a wheeled mobile robot violating the pure nonholonomic constraint

In this paper, adaptive neural network control is presented for a wheeled mobile robot violating the pure nonholonomic constraints. The nonholonomic constraint of the vehicle is assumed to be violated by an unknown slippage. Under a restricted assumption of the slippage, the proposed controller is constructed at the dynamical level using backstepping. The neural network (NN) controller deals with the unmodelled dynamics in the robot and eliminates the need for the error prone process in obtaining the LIP form of the system dynamics. In addition, the time-consuming offline training process for the NN is avoided. All the system states are shown to be able to track the desired trajectory. Simulation results are given to show the effectiveness of the proposed controller.

Robust Adaptive Control of Coordinated Multiple Mobile Manipulators

In this paper, robust adaptive controls of multiple mobile manipulators carrying a common object in a cooperative manner have been investigated with unknown inertia parameters and disturbances. At first, a concise dynamics consisting of the dynamics of mobile manipulators and the geometrical constraints between the end-effectors and the object is developed for coordinated multiple mobile manipulators, Then, robust adaptive controls have been designed where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. Simulation studies on the control of coordinated two wheels driven mobile manipulators have been used to show the effectiveness of the proposed scheme.

Adaptive robust controller design for multi-link flexible robots

An energy-based robust control strategy due to Ge et al. (1996) improved the control performance of the traditional joint PD control by introducing additional control efforts through the evaluation of vibration related variables. Although the energy-based robust controller always guarantees closed-loop stability, it is not easy to find suitable gains of the terms for a satisfactory control performance. In this paper, adaptive energy-based robust control is presented for both closed-loop stability and automatic tuning of the gains of the additional control terms for desired performance. Simulation results are provided to show the effectiveness of the presented approach.

Model-free controller design for a single-link flexible smart materials robot

In this paper, controller design is investigated for a single-link flexible smart materials robot which combines the advantages of both flexible link robots and piezoelectric materials. To avoid the drawbacks resulting from model uncertainties and/or model truncations, model-free controllers (both decentralized and centralized) are proposed for tip regulation and residual vibration suppression. In contrast to traditional model-based methods, the controllers presented in the paper are derived from the basic energy-work relationship and can guarantee the asymptotic stability of the damped truncated system with arbitrarily any finite number of flexible modes. Furthermore, the controllers are easily implementable because all the signals can be chosen to be readily measurable. Simulations are carried out to show the effectiveness of the approach presented.

Robust adaptive control of a wheeled mobile robot violating the pure nonholonomic constraint

In this paper, robust adaptive control strategy is presented for a wheeled mobile robot in the presence of model perturbations that violates the nonholonomic assumption. The nonholonomic constraint of the vehicle is assumed to be violated by an unknown slippage. Consequently, a perturbed kinematic model of the system is obtained. Using backstepping, the proposed controller is constructed at the dynamical level. The robust adaptive controller is to eliminate the needs for the LIP form of the system dynamics and the exact bounds of the system dynamics. All the system states are shown to be able to track the desired trajectory. The simulation results demonstrate the effectiveness of the proposed controllers.

Model-free regulation of multi-link smart materials robots

Model-free controllers are presented for multi-link smart materials robots. The controllers are derived from the basic energy-work relationship in the absence of the system model which is complex and difficult. To obtain for multi-link smart materials robots. The smart materials bonded along the links are used to apply additional control to suppress the residue vibration effectively. One can achieve not only the closed-loop stability of the original system, but also the asymptotic stability of the truncated system, which is obtained through representing the deflection of each link by an arbitrary finite number of flexible modes. Simulation results are provided to show the effectiveness of the presented approach.

Motion/force control of uncertain constrained nonholonomic mobile manipulator using neural network approximation

In this paper, an adaptive neural network control strategy is presented for motion/force control of a class of constrained mobile manipulators with unknown dynamics. The system is subject to both holonomic and nonholonomic constraints. The control law is developed based on a simplified dynamic model. The adaptive neural network controller is proposed to deal with the unmodelled dynamics in the system and eliminate the need for the error prone process in obtaining the LIP form of the system dynamics. In addition, the time-consuming offline training process for the neural network is avoided. Proportional plus integral feedback control is used for force control for the benefit of real-time implementation. The proposed control strategy guarantees that the system motion asymptotically converges to the desired manifold while the constraint force remains bounded.

Gain adaptive nonlinear feedback control of flexible SCARA/Cartesian robots

This paper presents a class of gain adaptive nonlinear feedback control for flexible SCARA/Cartesian robots. The controller is constructed by using vibration related nonlinear variables feedback and at the same time automatically tuning the feedback gains. Firstly, the closed-loop stability is proven for the original distributed-parameter system. Then, through explicitly solving the Partial Differential Equations (PDEs) of the system, asymptotic stability is obtained for the undamped truncated system, in which the distributed flexibility of the robot link is represented by an arbitrary finite number of flexible modes. Due to the non-model-based nature of the controller, some favorable features appear such as the elimination of control spillover and simplicity of actual implementation. Computer simulations are provided to illustrate the effectiveness of the approach.