The high performance control of direct drive systems (DDS) requires the consideration of the full system dynamics. In this study, a permanent magnet synchronous motor (PMSM) driven single link arm is considered as an example of a direct drive system. To achieve high performance control, an adaptive linearization scheme is implemented on the system to reduce the effects of the cogging and ripple torque of the motor and to compensate for load variations. To improve the performance of the adaptive linearizing scheme, a robust controller based on sliding mode theory is designed for the outer loop. The experimental results obtained are compared to the performance of pure PD control, sliding mode control and adaptive linearizing control algorithms and a significant improvement is observed in the torque ripple spectrum and the overall performance of the direct drive system with the combined control algorithm.

In this paper, a novel instantaneous control strategy for the AC control loop of voltage-type converter is proposed in which two switching vectors are selected sequentially in one sampling period. Vector selection is based on control error minimization theorem to bring both fast response and low ripple. Switching timing is determined in real time according to the THD(Total Harmonic Distortion) minimization theorem with instantaneous THD definition as a direct evaluation function. With this algorithm, instantaneous control can be realized in almost constant switching frequency. For DC output voltage control, voltage square feedback with load power compensated algorithm is introduced to obtain global stability with fixed gain. Experimental investigation confirmed the validity of proposed control algorithms.

A number of approaches based on sliding mode control methodology are proposed in the literature for the position control of robotic manipulators. An important problem in this context is chattering, that is high frequency oscillations in the velocity. In this paper, a novel approach is considered which eliminates chattering if the controller parameters are set suitably. A fuzzy adaptation scheme is devised for the online adaptation of the parameters of this method. Simulation results show that the fuzzy rule based adaptation scheme ensures good controller performance without chattering.

Application of neural network controller design in dynamical systems with sliding mode motion is introduced to improve performance of the discrete-time sliding mode system. Neural network controller with learning rule based on sliding mode algorithm, is proposed to assure calculation of unknown part of the equivalent control in the presence of the plant uncertainties. Developed algorithm is robust to parameter variations and external disturbances. The effectiveness of the neural network sliding mode controllers is verified by experiments.

In this paper, a new adaptive type sliding mode controller is presented to avoid the problem of the chattering and the excessive switching gain. The proposed control is based on the time delay estimation used in the time delay control (TDC) presented by Youcef-Toumi (1990, 1992). The sufficient condition for satisfying the reaching condition is presented by the application of Lyapunov direct method. The proposed control can be realized with a sufficiently low switching gain. The numerical examples are shown to confirm the validity of the proposed controller.

Trajectory generation and tracking in Cartesian space are essential in many industrial robotics applications. A control method using the relation between the force applied to the tool tip and joint torques is applied in this paper to track desired trajectories specified in Cartesian space. The controlled variables are the coordinates of the tip of the robot. The coupled and nonlinear dynamics involved cause difficulties in the robot control. The dynamics equations when expressed in tip coordinates get even more complicated. Variable structure systems based control methodologies are proposed in the literature to overcome the difficulties encountered, without using elaborate models of the plants to be controlled. High frequency oscillations in the joint velocities-chattering-is a problem faced when using such methods. A chattering free sliding mode control algorithm is considered here in order to deal with the complicated dynamics without causing oscillations in the velocity. Variable structure systems and Lyapunov designs are combined in the method implemented. The controller possesses the robustness properties of sliding mode systems. Experimental results obtained with a direct drive SCARA type manipulator are presented.

A new adaptive type sliding mode controller is presented to avoid the problem of the chattering and the excessive switching gain proportional to the upper bounds of system uncertainty in the application of sliding mode control. The proposed control is composed of linear feedback control and feedforward control which is constructed from an estimated equivalent control. The estimated equivalent control is obtained from an estimation system which uses a neural network's most powerful ability, that is, function approximation. The reaching condition is assured by the application of Lyapunov design method. The numerical examples are shown to confirm the validity of the proposed controller.

A nonmodel based discrete-time chattering-free sliding mode control scheme is proposed. The distinctive feature of the scheme is its robustness to different initial condition values and parameter mismatch. Nonlinear control principles are used, namely, the combined feedforward and the robust negative feedback part based on VSS controllers. In the discrete-time expression the discontinuous operation of controllers in the sliding mode has been replaced by the continous one. In this way the chattering of the control input has been eliminated and the excitation of the dynamic system without high frequency oscillations has been achieved. The proposed control solution is near an ideal control function in the sliding mode. Unlike other algorithms intended to avoid chattering, this nonmodel based approach uses only the information about the distance from the sliding mode manifold to derive the control. The advantage of the proposed control scheme prevails over those conventional model based control schemes since no precise knowledge of the mathematical model is necessary. In order to implement the control only the structure of the input matrix and the mean values of its parameters need be known. The parameters of the control depend only on the plant's gain matrix and the gradient of the sliding mode manifold.

The theoretical development of a trajectory tracking neural network controller based on the theory of sliding-mode controllers is shown in the paper. Derived equations of the neural network controller were verified on a direct drive 2-DOF SCARA mechanism model. The new neural network controller was compared with a neural network controller based on the computed torque method. At last we made an application on a real 2-DOF SCARA robot mechanism by the neural network controller based on the computed torque method and a sliding-mode neural network controller on a real single axis direct drive robotic manipulator driven by an induction motor.

An advanced discrete-time chattering-free sliding mode control scheme is presented. The distinctive feature of the scheme is its robustness to different initial condition values and parameter mismatch. Nonlinear control principles will be used namely, the combined feedforward and the robust negative feedback part based on VSS controllers. In the discrete-time expression the discontinuous operation of controllers in the sliding mode has ben replaced by the continuous one. In this way the chattering of control input has been eliminated and the excitation of the dynamic system without high-frequency oscillations has been achieved. The proposed control solution is near an ideal control function in the sliding mode. Unlike other algorithms intended to avoid chattering, this nonmodel-based approach uses only the information about the distance from the sliding mode manifold to derive the control. The advantage of the proposed control scheme prevail over those conventional model-based control scheme since no precise knowledge of mathematical model is necessary. In order to implement the control it must be only known the structure of input matrix and the mean values of its parameters. The input-output linear behavior of the closed control loop is predominantly determined by the controller's gain matrix.

Summary In this paper sliding mode motion design is considered for nonlinear plants which are linear with respect to control input. The dynamics of the robotic manipulators is treated with and without those of the actuators. When the dynamics of the actuators is included a design of the sliding modes for the systems with discontinuous control is performed. If actuators' dynamics is negelected the control is assumed to be continuous quantity. By combining the variable structure systems and Lyapunov designs a new algorithm is developed which has all the good properties of the sliding mode systems while avoiding unnecessary discontinuity of the control thus eliminating chattering. Neither the explicit calculation of the equivalent control, nor high gain inside the boundary layer are used. The parameters of the control depend on the plant's gain matrix, and the gradients of the sliding mode manifold. This control method is then applied to develop a unified control strategy for the motion control systems including the path tracking control, the impedance control and the force control of a robotic manipulator. It is shown that all these tasks can be formulated in the same mathematical form in which selected so-called sliding mode functions must track their references. In this way the systems state is forced to remain on the selected manifold in the state space after reaching it. The solution is interpreted in both the Joint space and the Work space for n -degrees of freedom robotic manipulators.