Interaction control of robotic manipulators via second‐order sliding modes

Robotic manipulators are widely used in space endeavors nowadays. For space applications, usually lightweight robotic manipulators are preferred. Hence, the system can be made underactuated intentionally. Also, one or more actuators may fail in space. Therefore, the system is highly uncertain and less actuated. The sliding mode control strategy does not depend on exact knowledge of the system model but chattering in states and control is observed. The present work showcases two different control techniques for achieving finite-time convergence and continuous control. The first technique is to choose a zero-error sliding function with a higher order sliding mode control and the second technique is to use a terminal sliding function with appropriate higher order sliding mode control for tracking control of an underactuated manipulator. A comparison is presented for the same.

A self-organizing fuzzy controller to augment a sliding-mode control (SOFSMC) scheme for a class of nonlinear systems is proposed. The motivation behind this scheme is to combine the best features of self-organizing fuzzy control and sliding-mode control to achieve rapid and accurate tracking control of a class of nonlinear systems. The chatter encountered by most sliding-mode control schemes is greatly alleviated without sacrificing invariant properties. A stability analysis is presented; the design guidelines and the class of applicable systems are clearly identified. To verify the scheme, the authors performed experiments on its implementation in a magnetic levitation system. The results show that both alleviation of chatter and robust performance are achieved; the advantages of the scheme are indicated in comparison with the conventional sliding-mode design. >

The paper investigates a modified adaptive super-twisting sliding mode control (ASTSMC) for robotic manipulators with input saturation. To avoid singular perturbation while increasing the convergence rate, a modified sliding mode surface (SMS) is developed in this method. Using the proposed SMS, an ASTSMC is developed for robot manipulators, which not only achieves strong robustness but also ensures finite-time convergence. The boundary of lumped uncertainties cannot be easily obtained. A modified adaptive law is developed such that the boundaries of time-varying disturbance and its derivative are not required. Considering input saturation in practical cases, an ASTSMC with saturation compensation is proposed to reduce the effect of input saturation on tracking performances of robot manipulators. The finite-time convergence of the proposed scheme is analyzed. Through comparative simulations against two other sliding mode control schemes, the proposed method has been validated to possess strong adaptability, effectively adjusting control gains; simultaneously, it demonstrates robustness against disturbances and uncertainties.

In this paper, the time-delayed control (TDC) scheme with a sliding mode controller for a robot manipulator is presented. Since TDC suffers from the selection of an inertia matrix of a robot manipulator, the effect of the constant matrix on the performance is investigated. TDC is designed with the sliding mode controller (SMC) to improve the control performance. For the performance comparison between several control schemes, PD control, SMC, TDC, and TDC-SMC are presented. The performances are compared by simulating the same trajectory tracking task of a three link robot manipulator u nder different control schemes.

This paper presents a comparison study of performances and characteristics of two types of state observer based state feedback control schemes, including Sliding Mode Observer (SMO) based Sliding Mode Controller (SMC) scheme and Luenberger observer (LO) based Sliding Mode Control scheme. The effectiveness of the schemes are simulated and implemented on Two Conical Tank Interacting Level System (TCTILS) which exhibits dynamic nonlinearity and coupling dynamics. The results show that, over all, the SMO based SMC scheme is much superior in dealing with dynamic uncertainties, disturbances and sensor noise.

The following topics are dealt with: renewable energy sources; energy conservation; computer aided engineering; thermal power stations; solar power stations; solar absorber-convertors; distributed power generation; photovoltaic power systems; domestic appliances; humidity.

This paper describes a dual-loop control scheme for fault tolerant flight control system design. The dual-loop controller consists of an outer loop controller–so-called adaptive neural sliding mode control (ANSC) and an inner loop controller designed by using nonlinear dynamic inversion (NDI) technique. The merits of adaptive neural network and sliding mode control scheme are that 1) the ability of adaptive neural network control to deal with unstructured uncertainty and 2) the ability of sliding mode control to guarantee transient response. Using timescale separation principal, the aircraft dynamics can be decomposed into fast and slow dynamics and the decomposed dynamics are inversed for NDI controllers. For real-time pilot simulation, one-stage inverse dynamics is used and the pilot inputs are translated to roll, pitch and yaw rate commands. For cascade NDI, two-stage dynamic inversion is used. The stability analysis of the proposed controller is performed using Lyapunov theory. To verify the effectiveness of the proposed control scheme, numerical simulation is performed for six degree-of-freedom nonlinear aircraft model while a failure occurs in longitudinal control surface. Simulation results demonstrate that closedloop system has good performance while encountering lock-in-place, partial destruction and floating actuator failures. Nomenclature stick long δ , stick lat δ , stick dir δ = pilot inputs for longitudinal, lateral and directional command dir lon lat K K K , , = sticks and pedal gains ref p , ref q , ref r = reference model rate commands cmd z n , cmd y n = normal and lateral acceleration command

This brief presents a contouring control scheme for robotic manipulators. The geometric properties of the desired contour are incorporated in the controller design phase, and the resulting controller has been structured as a two-layered hierarchical control scheme that consists of an outer loop and an inner loop. The outer loop is formed by kinematic control system in operational space, which can be designed to assign different dynamics to the tangential, normal, and binormal direction of the desired contour. It is shown that the outer loop can provide a joint velocity reference signal to the inner one. The inner loop is used to implement a velocity servo control system at the robot joint level. Meanwhile, a radial basis function network is adopted to compensate for the nonlinear dynamics of the robotic manipulator, where a robust control strategy is used to suppress the modeling error of neural networks. Experimental results on the Zebra-Zero robotic manipulator have demonstrated the effectiveness of the proposed control scheme in comparison with other control strategies.

A finite time synergetic control scheme for robot manipulators

Scheme of Sliding Mode Control based on Modified Particle Swarm Optimization

A sliding mode control based on motor angular speed control has been presented for a robot manipulator grasping a payload with mass variation. In order to guarantee the continuity of the control signals applied to the actuators of the robot manipulator, a sliding mode control with integral compensation is adopted. Improvement of robustness of the control system against payload mass variation is obtained by introducing a sliding mode feedforward signal. The control scheme is applied to a three joint robot manipulator, control performance both with payload torque compensation and without payload torque compensation are investigated. Simulation results show that the control scheme presented, is robust against payload mass variation and has satisfactory control performance.

In this paper, the dynamic model of the engine clutch engagement process is studied and a sliding mode control scheme is then developed. It is shown that the relationship between the chamber pressure and the clutch piston displacement during the engine clutch engagement process can be modeled as a second-order system. A sliding mode controller can then be designed based on the bound information of the uncertain system parameters and load force, in the sense that not only the strong robustness with respect to system uncertainties and non-linearities but also good tracking performance can be obtained. Finally, the comparative simulation results are presented to verify the good performance and effectiveness of the proposed control scheme.

This paper suggests a new hybrid control strategy, called Optimal Type II Fuzzy Sliding Mode (OT2FSM) control scheme, to realize the control of general uncertain chaotic systems. The proposed controller not only guaranties the stability and robustness against the lumped uncertainties caused by unmodeled dynamics and external disturbances, but also can significantly reduce the control chattering inherent in conventional sliding mode control. In the proposed controller, a novel heuristic algorithm namely particle swarm optimization with random inertia weight (RNW–PSO) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input and output membership functions are optimized simultaneously by RNW–PSO. The globally asymptotic stability of the closed-loop system is mathematically proved. To evaluate the performance of the proposed controller, the results are compared with those obtained by Optimal H-infinity Adaptive PID (OHAPID) controller and an optimal Type-2 fuzzy proportional integral derivative (OT2FPID), which are the latest researches in the problem in hand. Simulation results show the effectiveness of the OT2FSM controller.

In many industrial applications, the end-effectors of robotic manipulators are required to move from one place to the other and follow some desired trajectories accurately. This paper proposes the nonlinear backstepping design with sliding mode control (SMC) scheme for the trajectory tracking of a robotic manipulator. The main control objective here is not only to track the desired trajectory, but also to cope with the system uncertainty. For realization, the motor dynamics would be considered in our system model. In general, the backstepping with SMC controller can be successfully developed to achieve our control goals for the robot arm system with N links. In addition, an adaptive backstepping design method is proposed to deal with the system uncertainty for the position tracking control of this robotic manipulator. Finally, some comparative simulations are given to illustrate the good performance of the proposed control schemes applied to a two-link robot arm.

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.