An optimal control design for the uncertain Delta robot is proposed in the paper. The uncertain factors of the Delta robot include the unknown dynamic parameters, the residual vibration disturbances and the nonlinear joints friction, which are (possibly fast) time-varying and bounded. A fuzzy set theoretic approach is creatively used to describe the system uncertainty. With the fuzzily depicted uncertainty, an adaptive robust control, based on the fuzzy dynamic model, is established. It designs an adaptation mechanism, consisting of the leakage term and the dead-zone, to estimate the uncertainty information. An optimal design is constructed for the Delta robot and solved by minimizing a fuzzy set-based performance index. Unlike the traditional fuzzy control methods (if-then rules-based), the proposed control scheme is deterministic and fuzzily optimized. It is proven that the global solution in the closed form for this optimal design always exists and is unique. This research provides the Delta parallel robot a novel optimal control to guarantee the system performance regardless of the uncertainty. The effectiveness of the proposed control is illustrated by a series of simulation experiments. The results reveal that the further applications in other robots are feasible.

In order to stabilize the engine speed, increase the dynamic performance, save the energy, this paper presents a speed sensing control method for an EFI engine. The best operating points of an engine were discussed according to the static characteristics of an engine. Based on the best operating points and the load, the engine speed could be controlled by a double-closed loop control method, which could obtain the feedback signal from the engine speed and the throttle position. The model of a 161kW diesel engine and the control method were built, and the simulation was calculated based on the best working conditions. The results showed that the method could maintain the actual speed of an engine close to the goal speed, and achieve the requirements of the maximum torque, maximum power and the most economical output using the best operation points.