Hybrid force/position control of robotic arms manipulating in uncertain environments based on adaptive fuzzy sliding mode control

Coupled Force–Position Control for Dynamic Contact Force Tracking in Uncertain Environment

Both the position and force control of robots are needed in industrial manufacturing, such as in assembly and grinding, etc. In this paper, we concentrate on two issues. One is the system oscillation in traditional hybrid force–position control (HFPC) during switching between force and position control because the diagonal elements in the selection matrix are either 0 or 1. Another issue is the poor force-tracking performance of conventional impedance control, which depends on accurate environmental models. To address these issues, a coupled force–position control (CFPC) method is presented in this paper by combining the proposed adaptive impedance control method with a modified HFPC method. The selection matrix S of HFPC is replaced with a weighted matrix Sw. A weighted matrix regulator is designed to realize smooth switching between position and force control by adjusting the matrix weights in real time, and an adaptive impedance control algorithm is proposed to improve the force-tracking performance in complex environments. To verify the feasibility of the CFPC method proposed in this paper, simulations and physical experiments were conducted. The results show that the CFPC method has the advantages of a better force-tracking performance and a smoother switching between position and force control compared to the traditional HFPC method. A grinding experiment was conducted to further compare the performances of the HFPC and CFPC methods. The roughness values of the ground plates were 0.059 μm for the HFPC method and 0.031 μm for the proposed CFPC method, which demonstrates that the proposed CFPC method has a better performance.

Elasto-Geometrical Model-Based Control of Industrial Manipulators Using Force Feedback: Application to Incremental Sheet Forming

This paper aims to improve the positioning accuracy of serial industrial manipulators using force feedback in manufacturing processes by implementing an elasto-geometrical model-based control. Initially, the real-time position control strategy using a force feedback to elastically correct the Tool Center Point (TCP) pose of serial industrial manipulators is detailed. To continue, an efficient model structure identification and calibration is proposed to shorten the elasto-geometrical modeling process. The Virtual Joint Method (VJM) is chosen to iterate and complete the robot stiffness modeling. This method considers that the elastic deformations are only localized at the joints of the robot. An appropriate and original test-model approach allows a minimum of optimization iterations to find the best compromise between complexity and accuracy of the modeling. The proposed approach is illustrated in detail by the Stäubli TX200 robot modeling. Finally, the reliability and responsiveness of the developed control framework is then evaluated through experimental tests in an Incremental Sheet Forming (ISF) context. An average improvement of 70% in trajectory-tracking accuracy is achieved during these tests. Overall, the high accuracy and responsiveness of the developed system demonstrate a promising potential for deploying industrial manipulators to a cost-effective manufacturing processes in industry 4.0.

State Machine-Based Hybrid Position/Force Control Architecture for a Waste Management Mobile Robot with 5DOF Manipulator

When robots are built with state-driven motors, task-planning increases in complexity and difficulty. This type of actuator is difficult to control, because each type of control position/force requires different motor parameters. To solve this problem, we propose a state machine-driven hybrid position/force control architecture (SmHPFC). To achieve this, we take the classic hybrid position/force control method, while using only PID regulators, and add a state machine on top of it. In this way, the regulators will not help the control architecture, but the architecture will help the entire control system. The architecture acts both as a parameter update process and as a switching mechanism for the joints’ decision S-matrix. The obtained control architecture was then applied to a 5DOF serial manipulator built with Festo motors. Using SmHPFC, the robot was then able to operate with position or force control depending on its designated task. Without the proposed architecture, the robot joint parameters would have to be updated using a more rigid approach; each time a new task begins with new parameters, the control type would have to be changed. Using the SmHPFC, the robot reference generation and task complexity is reduced to a much simpler one.

Adaptive Position/Force Control of a Robotic Manipulator in Contact with a Flexible and Uncertain Environment

The present paper concerns the synthesis of robot movement control systems in the cases of disturbances of natural position constraints, which are the result of surface susceptibility and inaccuracies in its description. The study contains the synthesis of control laws, in which the knowledge of parameters of the susceptible environment is not required, and which guarantee stability of the system in the case of an inaccurately described contact surface. The novelty of the presented solution is based on introducing an additional module to the control law in directions normal to the interaction surface, which allows for a fluent change of control strategy in the case of occurrence of distortions in the surface. An additional module in the control law is perceived as a virtual viscotic resistance force and resilient environment acting upon the robot. This interpretation facilitates intuitive selection of amplifications and allows for foreseeing the behavior of the system when disturbances occur. Introducing reactions of virtual constraints provides automatic adjustment of the robot interaction force with the susceptible environment, minimizing the impact of geometric inaccuracy of the environment.

Safety Operation of n-DOF Serial Hydraulic Manipulator in Constrained Motion with Consideration of Contact-Loss Fault

In consideration of accidental contact-loss due to step-change or accidentally moving out of a constrained framework, this paper focuses on solving this problem during working processes of an n-degree-of-freedom hydraulic manipulator (n-DOF manipulator). In order to overcome this phenomenon, a fault detection methodology-based virtual energy tank is employed with a shaping function to prevent the end-effector from damage or unexpected motion. This technique helps to detect when the contact-loss happens by a virtual energy variable; thus, decoupling a force control regulation. Moreover, a new trajectory for smooth motion after contact-loss detection is also discussed to increase system robustness. Additionally, to enhance tracking performance, adaptive laws are designed to compensate for system uncertainties. Comparative simulations are given on the n-DOF hydraulic manipulator to evaluate effectiveness of the impedance-based energy tank methodology under the sudden step-changed environment. Moreover, influences of control gains and setup energy parameters to the system behaviors when contact-loss happens are remarkably discussed as indispensable criteria for further development. The simulated results certified the superior effectiveness and reliability of the suggested methodology over the conventional impedance control for safe operation.

New development of the dynamic modeling and the inverse dynamic analysis for flexible robot

When a segment of a flexible link of a flexible robot is currently sliding through a prismatic joint, it is usually assumed that the elastic deformation of the segment equals to zero. This is a kind of time-dependent boundary condition when formulating the dynamics model of a flexible robot consisting of prismatic joints. Hence, the dynamic modeling and especially the inverse dynamic analysis of the flexible robots with the prismatic joints are challenging. In this article, we present a new development of the dynamic modeling method for a generic two-link flexible robot that consists of a prismatic joint and a revolute joint. Moreover, a new bisection method-based algorithm is proposed to analyze the inverse dynamic responses of the flexible robots. Since the bisection method is a rapid converging method in mathematics, the proposed algorithm is effectively applicable to solving the inverse dynamic problem of a flexible robot in a robust manner. Last, the numerical simulation results show the effectiveness and the robustness of the proposed method.

Robust Position/Force Control of Constrained Flexible Joint Robots with Constraint Uncertainties

A novel robust control method for simultaneous position/force control of constrained flexible joint robots is proposed. The facts that the uncertainties make the usual control task unsolvable and that the equations of the controlled system are differential-algebraic make the problem dealt with considerably demanding. In order to overcome the unsolvability problem due to the constraint uncertainties the position control task is redefined in a practical way such that only a suitable subgroup of the link positions are driven to their desired trajectories. To determine the elements of the subgroup a simple algorithm of practical relevance is proposed. Under certain smoothness conditions to the contact surfaces, it is demonstrated that the position control problem can dynamically be isolated from the force control. Thus, it becomes possible to handle the position and force control tasks separately. The most significant advantage of the separation of the position and force control tasks is that it makes possible to adapt the position control methods known from free robots. Each joint is used in either position control or force control. The proposed position controller has a cascaded structure: First, trajectories for joint positions that drive the link positions to their desired values are calculated. Then, the joint torques that drive the joint positions to their calculated values are determined. A further significant benefit of the separation of the position and force control tasks arises in the force control such that the transformed equations are linear and any linear robust control approach can be used for the force control. The whole controller requires the measurement of the link and joint positions, the link and joint velocities and the contact forces, and allows modeling uncertainties in the equations of both the robot dynamics and the contact surfaces. The proposed control method is also confirmed by simulations.

Adaptive Fuzzy-Based Fault-Tolerant Control of a Continuum Robotic System for Maxillary Sinus Surgery

Continuum robots represent a class of highly sensitive, multiple-degrees-of-freedom robots that are biologically inspired. Because of their flexibility and accuracy, these robots can be used in maxillary sinus surgery. The design of an effective procedure with high accuracy, reliability, robust fault diagnosis, and fault-tolerant control for a surgical robot for the sinus is necessary to maintain the high performance and safety necessary for surgery on the maxillary sinus. Thus, a robust adaptive hybrid observation method using an adaptive, fuzzy auto regressive with exogenous input (ARX) Laguerre Takagi–Sugeno (T–S) fuzzy robust feedback linearization observer for a surgical robot is presented. To address the issues of system modeling, the fuzzy ARX-Laguerre technique is represented. In addition, a T–S fuzzy robust feedback linearization observer is applied to a fuzzy ARX-Laguerre to improve the accuracy of fault estimation, reliability, and robustness for the surgical robot in the presence of uncertainties. For fault-tolerant control in the presence of uncertainties and unknown conditions, an adaptive fuzzy observation-based feedback linearization technique is presented. The effectiveness of the proposed algorithm is tested with simulations. Experimental results show that the proposed method reduces the average position error from 35 mm to 2.45 mm in the presence of faults.

Advanced Adaptive Fault Diagnosis and Tolerant Control for Robot Manipulators

In this paper, an adaptive Takagi–Sugeno (T–S) fuzzy sliding mode extended autoregressive exogenous input (ARX)–Laguerre proportional integral (PI) observer is proposed. The proposed T–S fuzzy sliding mode extended-state ARX–Laguerre PI observer adaptively improves the reliability, robustness, estimation accuracy, and convergence of fault detection, estimation, and identification. For fault-tolerant control in the presence of uncertainties and unknown conditions, an adaptive fuzzy sliding mode estimation technique is introduced. The sliding surface slope gain is significant to improve the system’s stability, but the sliding mode technique increases high-frequency oscillation (chattering), which reduces the precision of the fault diagnosis and tolerant control. A fuzzy procedure using a sliding surface and actual output position as inputs can adaptively tune the sliding surface slope gain of the sliding mode fault-tolerant control technique. The proposed robust adaptive T–S fuzzy sliding mode estimation extended-state ARX–Laguerre PI observer was verified with six degrees of freedom (DOF) programmable universal manipulation arm (PUMA) 560 robot manipulator, proving qualified efficiency in detecting, isolating, identifying, and tolerant control for faults inherent in sensors and actuators. Experimental results showed that the proposed technique improves the reliability of the fault detection, estimation, identification, and tolerant control.