Trajectory Tracking with Parallel Robots Using Low Chattering, Fuzzy Sliding Mode Controller

Intelligent Hybrid Control Strategy for Trajectory Tracking of Robot Manipulators

“…where Θ = Θ * − Θ,˙ Θ = −˙ Θ, matrix P is defined by (15). Differentiating V with respect to time along trajectory of error equation (8), similar to the proof of Theorem 1, we getV Using both expressions (27) and (30), and considering Assumption 4, we havė…”

“…Some theses [8,12,13] use soft computer methods to approximate the whole robot dynamics rather than its nonlinear components as done by static intelligent means. Man [7] and Qi [15] make use of intelligent systems to replace the constant switching control gain and the width of the boundary layer. However, [7] has the shortcoming that the inverse of inertia matrix needs to be calculated.…”

A Highly Accurate Model-Free Motion Control System with a Mamdani Fuzzy Feedback Controller combined with a TSK Fuzzy Feed-forward Controller

“…The 96 MFs for each input, the fuzzy learning outputs and the FIS output surfaces can be found in [24] The block diagram of the MF-PID-FLC used for simulation is shown in Fig. 6.…”

“…In the field of control, they are nonlinear mappings in the first place. Among them, FLCs [24,39] have shown that such hybrid structures not only work well but also add more robustness to the control system's design. FLCs are able to deliver a satisfactory performance in the face of uncertainty and imprecision [9,19].…”

Design and implementation of a control architecture for robot‐assisted orthopaedic surgery

“…A new discrete sliding-mode control approach for parallel robot was presented to achieve accurate servo-tracking in the presence of load variations, parameter variations and non-linear dynamic interactions (46). A fuzzy adaptive supervisory controller was combined with the fuzzy sliding mode control to demonstrate that the chattering of the sliding mode controller was greatly reduced and that the parallel robot realized the trajectory tracking with very good robustness to the parameter uncertainties and external disturbances (47). A model-based adaptive backstepping controller has also been designed for a planar parallel robot (48).…”