The closed-loop human–robot system requires developing an effective robotic controller that considers models of both the human and the robot, as well as human adaptation to the robot. This paper develops a mid-level controller providing assist-as-needed (AAN) policies in a hierarchical control setting using two novel methods: model-based and fuzzy logic rule. The goal of AAN is to provide the required extra torque because of the robot’s dynamics and external load compared to the human limb free movement. The human–robot adaptation is simulated using a nonlinear model predictive controller (NMPC) as the human central nervous system (CNS) for three conditions of initial (the initial session of wearing the robot, without any previous experience), short-term (the entire first session, e.g., 45 min), and long-term experiences. The results showed that the two methods (model-based and fuzzy logic) outperform the traditional proportional method in providing AAN by considering distinctive human and robot models. Additionally, the CNS actuator model has difficulty in the initial experience and activates both antagonist and agonist muscles to reduce movement oscillations. In the long-term experience, the simulation shows no oscillation when the CNS NMPC learns the robot model and modifies its weights to simulate realistic human behavior. We found that the desired strength of the robot should be increased gradually to ignore unexpected human–robot interactions (e.g., robot vibration, human spasticity). The proposed mid-level controllers can be used for wearable assistive devices, exoskeletons, and rehabilitation robots.
SUMMARYThis paper presents a solution for optimal trajectory planning problem of robotic manipulators with complicated dynamic equations. The main goal is to find the optimal path with maximum dynamic load carrying capacity (DLCC). Proposed method can be implemented to problems of both motion along a specified path and point-to-point motion. Dynamic Programming (DP) approach is applied to solve optimization problem and find the positions and velocities that minimize a pre-defined performance index. Unlike previous attempts, proposed method increases the speed of convergence by using the sequential quadratic programming (SQP) formulation. This formulation is used for solving problems with nonlinear constraints. Also, this paper proposes a new algorithm to design optimal trajectory with maximum DLCC for both fixed and mobile base mechanical manipulators. Algorithms for DLCC calculations in previous works were based on indirect optimization method or linear programming approach. The proposed trajectory planning method is applied to a linear tracked Puma and the mobile manipulator named Scout. Application of this algorithm is confirmed and simulation results are compared with experimental results for Scout robot. In experimental test, results are obtained using a new stereo vision system to determine the position of the robot end-effector.
Atomic force microscope (AFM) is one of the most powerful tools for surface scanning, force measurement, and nano‐manipulation. To improve its performance, vibration and control of AFM micro‐cantilever (MC) should be studied. Hysteresis, as an undesired phenomenon affecting vibration amplitude and phase, is also another important issue to be examined. In this paper, vibration analysis and control of a ZnO non‐uniform multi‐layered piezoelectric MC has been investigated in non‐contact mode. A modified couple stress theory has been used to obtain the strain energy for modeling the MC. In order to control the amplitude, a sliding mode controller (SMC) has been utilized on AFM, due to its application in uncertain and nonlinear systems. For applying the control signal, two methods of piezo and base actuation are studied. The results are compared with proportional integral derivative (PID) control method and it is demonstrated that SMC method reduces the control input close to the surface and increases the accuracy near the surface. In addition to MC control, hysteresis amplitude and phase differences are investigated by applying the Prandtl–Ishlinskii model. Also, surface topography is studied with hysteresis. The simulations show backward phase difference and an increase in amplitude, accordingly.
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