Kang-Bark Park

Comments on "A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators"

The authors state that there are two errors in the above paper ( Zhihong et al., ibid., vol.39, no.12, p.2464-9, 1994). The purpose of this note is to give correct versions of Remark 2.1 and Remark 3.3.

Sliding mode controller with filtered signal for robot manipulators using virtual plant/controller

Abstract A sliding mode control scheme that guarantees smoothness of the control signal and exponential error convergence is proposed for robot manipulators. The proposed method inserts a low pass filter (LPF) in front of the plant, and the virtual controller is designed for the virtual plant—the combination of the LPF and the robot manipulator. The virtual control signal contains high frequency components because of a switching function. The real control signal, however, always shows a smooth curve since it is an output of the LPF. In addition to the smoothness of the control signal always being assured, the overall system is in sliding mode at all times, i.e. its performance is always invariant under the existence of parameter uncertainties and external disturbances. The closed-loop system is shown to be globally exponentially stable.

Redundancy resolution of robot manipulators using optimal kinematic control

Globally optimal redundancy resolution in robot manipulators is considered. Some researchers have approached the redundancy resolution with optimization techniques and others with Pontryagins principle. In this paper, as another approach we propose the optimal kinematic control. The formulation is: first to convert the redundancy resolution problem to an optimal control problem, and to obtain the globally optimal resolution of redundancy by using the necessary conditions of optimal control. As a result, we get 2n first-order partial differential equations and corresponding boundary conditions. It is shown that these 2n equations are equivalently converted to n second-order differential equations resolving the redundancy in joint acceleration level.<<ETX>>

Robust adaptive control for robot manipulators using regressor-based form

In this paper, a robust adaptive control scheme is proposed for robot manipulators. The structure of controller is based on the regressor-based form of the robot model. The presented control scheme does not require a priori any knowledge for uncertainty bounds. The global stability of the closed-loop system is guaranteed by using the Lyapunov stability approach. Furthermore, in the presence of the measurement noise, it is shown that the tracking errors are uniformly ultimately bounded. Consequently, it is found that the proposed control scheme guarantees global boundedness of the tracking errors under parameter variations, disturbances and measurement noises. Simulation-results are presented to show the feasibility and the effectiveness of the proposed control scheme.<<ETX>>

Local motion planner for nonholonomic mobile robots in the presence of the unknown obstacles

This paper deals with the problem of motion planning for a unicycle-like robot. A simple local planner for unicycle model, based on an approximation of the desired configuration generated by local holonomic planner that ignores motion constraints, is presented. To guarantee a collision avoidance, we propose an inequality constraint, based on the motion analysis with the constant control input and time interval. Consequently, we formulate the problem as a constrained optimization problem, and a feedback scheme based on local sensor information is established by simply solving this problem. Through simulations, we confirm the validity and effectiveness of our algorithm.

Variable structure controller for robot manipulators using time-varying sliding surface

The authors propose a variable-structure controller with a time-varying sliding surface for robot manipulators. The time-varying sliding surface ensures the existence of a sliding mode from an initial state, whereas the conventional sliding surface cannot achieve performance robust against parameter variations and disturbances before the sliding mode occurs. Therefore, the error transient can be fully prescribed in advance for all time. The overall system is globally exponentially stable. The efficiency of the proposed method for trajectory tracking has been demonstrated by simulations.<<ETX>>

Comments on "Some conditions on zeros to avoid step-response extrema". II [with reply]

The commenters give a correct version of Theorem 2 of the above-mentioned paper (Rachid, ibid., vol.40, p.1501-3, 1995). In reply Rachid accepts one of their points and gives a new statement of Theorem 2.

The problem of stability in the application of neural network to continuous-time dynamic systems

Using a neural network to identify a function in the dynamic equation brings about additional difficulties which are not generic in other function approximation problems. First, training samples can not be arbitrarily chosen due to hard nonlinearity, so are apt to be nonuniform over the region of interest. Second, the system may become unstable while attempting to obtain the samples. This paper deals with these problems in continuous-time systems and suggests an effective solution, which provides stability and uniform sampling by the virtue of a supervisory controller. The supervisory control algorithm can be applied to robot system dynamics. The algorithm can be applied to an n-th order robot system, a simulation result is given for a simple two link robot.

Adaptive sliding mode controller with monotonically nonincreasing gain for nonlinear uncertain systems

In this paper, the adaptive sliding mode controller (ASMC) is proposed for a class of nonlinear uncertain systems. Conventional adaptive robust control system and/or adaptive sliding mode control system could not give when the system shows invariance property against parameter uncertainties and external disturbances. Thus, although the initial system state is on the sliding surface, one can not ensure the occurrence of the sliding mode for the conventional adaptive sliding mode control systems; that is, the system state may leave the sliding surface even if the state hits the sliding surface. For the proposed ASMC, no a priori knowledge of the exact bounds for parameter uncertainties and external disturbances is needed because the proposed control scheme uses adaptive algorithm for bounds of the uncertainty. The overall system is shown to be globally asymptotically stable.

Continuous sliding mode control system using virtual reconstruction

In this paper, a sliding mode control scheme that guarantees the smoothness of the control signal and the exponential error convergence is proposed for robot manipulators. The proposed method inserts a low-pass filter (LPF) in front of the plant, and the virtual controller is designed for the virtual plant-the combination of the LPF and the robot manipulator. The virtual control signal contains high frequency components because of a switching function. The real control signal, however, always shows a smooth curve since it is an output of the LPF. In addition to the smoothness of the control signal is always assured, the overall system is in the sliding mode at all times, that is, its performance is always invariant under the existence of parameter uncertainties and external disturbances. The closed-loop system is shown to be globally exponentially stable.