Position control of shape memory alloy actuators using self tuning fuzzy PID controller

Shape Memory Alloy (SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

Lovastatin biosynthesis depends on the carbon-nitrogen proportion: model development and controller design

Lovastatin biosynthesis depends on the relative concentrations of dissolved oxygen and the carbon and nitrogen resources. An elucidation of the underlying relationship would facilitate the derivation of a controller for the improvement of lovastatin yield in bioprocesses. To achieve this goal, batch submerged cultivation experiments of lovastatin production by Aspergillus flavipus BICC 5174, using both lactose and glucose as carbon sources, were performed in a 7 liter bioreactor and the data used to determine how the relative concentrations of lactose, glucose, glutamine and oxygen affected lovastatin yield. A model was developed based on these results and its prediction was validated using an independent set of batch data obtained from a 15-liter bioreactor using five statistical measures, including the Willmott index of agreement. A nonlinear controller was designed considering that dissolved oxygen and lactose concentrations could be measured online, and using the lactose feed rate and airflow rate as process inputs. Simulation experiments were performed to demonstrate that a practical implementation of the nonlinear controller would result in satisfactory outcomes. This is the first model that correlates lovastatin biosynthesis to carbon-nitrogen proportion and possesses a structure suitable for implementing a strategy for controlling lovastatin production.

Adaptive backstepping droop controller design for multi-terminal high-voltage direct current systems

Wind power is one of the most developed renewable energy resources worldwide. To integrate offshore wind farms to onshore grids, the high-voltage direct current (HVDC) transmission cables interfaced with voltage source converters (VSCs) are considered to be a better solution than conventional approaches. Proper DC voltage indicates successive power transfer. To connect more than one onshore grid, the DC voltage droop control is one of the most popular methods to share the control burden between different terminals. However, the challenges are that small droop gains will cause voltage deviations, while higher droop gain settings will cause large oscillations. This study aims to enhance the performance of the traditional droop controller by considering the DC cable dynamics. Based on the backstepping control concept, DC cables are modelled with a series of capacitors and inductors. The final droop control law is deduced step-by-step from the original remote side. At each step the control error from the previous step is considered. Simulation results show that both the voltage deviations and oscillations can be effectively reduced using the proposed method. Further, power sharing between different terminals can be effectively simplified such that it correlates linearly with the droop gains, thus enabling simple yet accurate system operation and control.