Luca Massimiliano Capisani

Trajectory Planning and Second-Order Sliding Mode Motion/Interaction Control for Robot Manipulators in Unknown Environments

The problem of determining an interaction control strategy, allowing a manipulator to reach a goal point even in the presence of unknown obstacles, is faced in this paper. To this end, on the basis of position/orientation and force measurements, first, a path planning strategy is proposed. The path planning is based on an a priori trajectory, which is determined without the prior knowledge of the obstacle presence in the workspace, and on a real-time approach to generate auxiliary temporary trajectories on the basis of the properties of the obstacle surface in a vicinity of the contact point, estimated through force measurements. To determine the input laws of the manipulator, a robust hybrid position/force control scheme is adopted. First- and second-order sliding mode controllers are considered to generate the robot input laws, and the obtained performances are experimentally compared with those of classical PD control. Experiments are made on a COMAU SMART3-S2 anthropomorphic industrial manipulator.

Fault Detection for Robot Manipulators via Second-Order Sliding Modes

This paper presents a model-based fault detection (FD) and isolation scheme for rigid manipulators. A single fault acting on a specific actuator or on a specific sensor of the manipulator is detected (and, if possible, the exact location of the fault), and an estimation of the fault signal is performed. Input-signal estimator and output observers are considered in order to make the FD procedure possible. By using the suboptimal second-order sliding-mode (SOSM) algorithm to design the input laws of the observers, satisfactory stability properties of the observation error are established. The proposed algorithm is verified in simulation and experimentally on a COMAU SMART3-S2 robot manipulator.

Manipulator Fault Diagnosis via Higher Order Sliding-Mode Observers

A diagnostic scheme for actuator and sensor faults which can occur on a robot manipulator using a model-based fault diagnosis (FD) technique is addressed. With the proposed FD scheme, it is possible to detect a fault, which can occur on a specific component of the system. To detect actuator faults, higher order sliding-mode unknown input observers are proposed to provide the necessary analytical redundancy. The detection of sensor faults, instead, is made by relying on a generalized observer scheme. The observer input laws are designed according to two well-known second-order sliding-mode approaches: the so-called supertwisting and the suboptimal one. Both typologies of input laws allow to perform a satisfactory FD. The peculiarities of each input law of the observers are discussed. To make possible fault isolation, it is required that a single fault acts only on one component of the system at a time. If one knows that faults occurred only on actuators, then it is possible to isolate multiple simultaneous faults on actuators. The proposed approach is verified in simulation and experimentally on a COMAU SMART3-S2 robot manipulator.

Design and experimental validation of a second-order sliding-mode motion controller for robot manipulators

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

Second order sliding mode motion control of rigid robot manipulators

This paper presents a control strategy for robot manipulators, based on the coupling of the inverse dynamics method with the so-called second order sliding mode control approach. The motivation for using sliding mode control in robotics mainly relies on its appreciable features, such as design simplicity and robustness. Yet, the chattering effect, typical of the conventional sliding mode control, can be destructive. In this paper, this problem is suitably circumvented by adopting a second order sliding mode control approach characterized by a continuous control law. To design the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified. The proposed inverse dynamics-based second order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

MIMO Closed Loop Identification of an Industrial Robot

This paper proposes a practical multi-input multi-output (MIMO) closed loop parameters identification procedure for robot manipulators. It is based on the weighted least squares (WLS) method, coupled with particular solutions to facilitate the estimation, reducing the noise effect. More precisely, a two steps procedure to reduce the condition number of the input data matrix with optimal trajectory planning, and a method to estimate the variances matrix to be used as a weight matrix for the WLS method are illustrated. Moreover, the identification problem is solved with reference to an MIMO coupled system. A closed loop identification is needed because the system is open loop unstable, and because the robot has to track an optimal reference input so as to correctly execute the identification procedure. Some solutions are also presented to overtake common identification problems, such as the bias of the estimated parameters, the presence of outliers, the necessity of balancing the kinematics of the third link, and the reduction of the sensitivity to noise of the estimate. The presented procedure has been successfully experimentally tested on a COMAU SMART3-S2 industrial manipulator used in a planar configuration.

MIMO identification with optimal experiment design for rigid robot manipulators

This paper proposes a practical parameters identification procedure for robot manipulators. It is based on the well-known maximum likelihood method adopting particular techniques to facilitate the estimation: condition number reduction methods for the input data matrix with optimal trajectory planning, and two different methods for variances estimation. Moreover, the identification problem is solved with reference to the multi input multi output coupled system. A closed loop identification is needed because the system is open loop unstable, and, moreover, because to correctly execute the identification procedure, the robot has to track an optimal reference input. Some solutions are also presented to overtake common identification problems, such as bias of the estimated parameters, outliers detection and elimination, and noise sensitivity of the estimation. The presented procedure was successfully tested on a COMAU SMART3-S2 industrial manipulator demonstrating its efficiency.

Second-order Sliding Mode Control with Adaptive Control Authority for the Tracking Control of Robotic Manipulators

Abstract In this work, the joint position tracking control problem of industrial robots is tackled. To cope with the model uncertainties and external disturbances affecting the robot, the Inverse Dynamic Controller (IDC) is combined with an approach based on higher order Sliding Mode Control (SMC) technique. We make use, in particular, of the so-called “Twisting” Second Order Sliding Mode Controller. Higher order SMC techniques transfer the inherent discontinuities to the time derivative of the input torque and this allows to obtain a continuous profile for the input torque, which is computed through integration of an appropriate discontinuous switching signal. Despite the chattering phenomenon is strongly attenuated, some residual problems (vibration and acustical noise) are still observed during the experimental implementation of such an approach in its standard formulation. To improve the system performance we suggest in this work an adaptation mechanism to adjust on-line the authority of the SMC. The logic is driven by a “sliding-mode indicator” that detects, on line, the occurrence of a sliding mode behaviour and uses this information for adaptation purposes. When large and fast control activity is demanded (e.g. to track fast reference trajectories) the adaptation unit reacts by automatically increasing the control authority of the SMC. On the other hand when small control authority is sufficient the control magnitude is lowered. Such a bidirectional adaptation logic significantly reduces the chattering. The proposed technique is theoretically analyzed and experimentally tested, and the results of comparative experiments are discussed in the paper.

Hybrid position/force sliding mode control of a class of robotic manipulators

This paper deals with the hybrid position/force control of a class of robotic manipulators. To perform the control scheme design, it is necessary to characterize the dynamical model of the force sensor which is mounted at the end-effector of the robot. The objective is to perform reliable contact force measurements by estimating all the forces which are generated at the level of the tip which is directly connected to the sensor. A dynamical model of the sensor motion is formulated and identified, by considering also the kinematics of the robot. The proposed hybrid control scheme includes position and force controllers based on first and second order sliding modes. These kind of controllers guarantee suitable robustness properties to perform a satisfactory trajectory tracking, also allowing one to make the robot move in an environment with unknown obstacles by using the possibility of touching the obstacles as a way to pass them by. Experimental tests are performed on a COMAU SMART3-S2 anthropomorphic rigid robot manipulator with an ATI Gamma force sensor by comparing four different position/force control schemes.

An Inverse Dynamics-Based Discrete-Time Sliding Mode Controller for Robot Manipulators

In the past years an extensive literature has been devoted to the subject of motion control of rigid robot manipulators. Many approaches have been proposed, such as feedback linearization [1], model predictive control [2], as well as sliding mode or adaptive control [3], [4], [5]. The basic idea of feedback linearization, known in the robotic context as inverse dynamics control [6], [7], is to exactly compensate all the coupling nonlinearities in the dynamical model of the manipulator in a first stage so that a second stage compensator may be designed based on a linear and decoupled plant. Although global feedback linearization is possible in theory, in practice it is difficult to achieve, mainly because the coordinate transformation is a function of the system parameters and, hence, sensitive to uncertainties which arise from joint and link flexibility, frictions, sensor noise, and unknown loads. This is the reason why the inverse dynamics approach is often coupled with robust control methodologies [1].