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.

Multiple Input Governor Control for a Diesel Generating Set

The paper presents a multiple input single output fuzzy logic governor algorithm that can be used to improve the transient response of a diesel generating set, when supplying an islanded load. The proposed governor uses the traditional speed input in addition to voltage and power factor to modify the fuelling requirements during various load disturbances. The use of fuzzy logic control allows the use of PID type structures that can provide variable gain strategies to account for non-linearities in the system. Fuzzy logic also provides a means of processing other input information by linguistic reasoning and a logical control output to aid the governor action during transient disturbance. The test results were obtained using a 50 kVA naturally aspirated diesel generator testing facility. Both real and reactive load tests were conducted. The complex load test results demonstrate that, by using additional inputs to the governor algorithm, enhanced generator transient speed recovery response can be obtained.

Phase I Study Of The Poly(ADP-Ribose) Polymerase Inhibitor, AG014699, In Combination With Temozolomide in Patients with Advanced Solid Tumors

Purpose: One mechanism of tumor resistance to cytotoxic therapy is repair of damaged DNA. Poly(ADP-ribose) polymerase (PARP)-1 is a nuclear enzyme involved in base excision repair, one of the five major repair pathways. PARP inhibitors are emerging as a new class of agents that can potentiate chemotherapy and radiotherapy. The article reports safety, efficacy, pharmacokinetic, and pharmacodynamic results of the first-in-class trial of a PARP inhibitor, AG014699, combined with temozolomide in adults with advanced malignancy.

Experimental Design: Initially, patients with solid tumors received escalating doses of AG014699 with 100 mg/m2/d temozolomide × 5 every 28 days to establish the PARP inhibitory dose (PID). Subsequently, AG014699 dose was fixed at PID and temozolomide escalated to maximum tolerated dose or 200 mg/m2 in metastatic melanoma patients whose tumors were biopsied. AG014699 and temozolomide pharmacokinetics, PARP activity, DNA strand single-strand breaks, response, and toxicity were evaluated.

Results: Thirty-three patients were enrolled. PARP inhibition was seen at all doses; PID was 12 mg/m2 based on 74% to 97% inhibition of peripheral blood lymphocyte PARP activity. Recommended doses were 12 mg/m2 AG014699 and 200 mg/m2 temozolomide. Mean tumor PARP inhibition at 5 h was 92% (range, 46-97%). No toxicity attributable to AG014699 alone was observed. AG014699 showed linear pharmacokinetics with no interaction with temozolomide. All patients treated at PID showed increases in DNA single-strand breaks and encouraging evidence of activity was seen.

Conclusions: The combination of AG014699 and temozolomide is well tolerated, pharmacodynamic assessments showing proof of principle of the mode of action of this new class of agents.

COLREGs-based collision avoidance strategies for unmanned surface vehicles

The aim of this paper is to report the preliminary development of an automatic collision avoidance technique for unmanned marine craft based on standardised rules, COLREGs, defined by the International Maritime Organisation. It is noted that all marine surface vessels are required to adhere to COLREGs at all times in order to minimise or eliminate the risk of collisions. The approach presented is essentially a reactive path planning algorithm which provides feedback to the autopilot of an unmanned vessel or the human captain of a manned ship for steering the craft safely. The proposed strategy consists of waypoint guidance by line-of-sight coupled with a manual biasing scheme. This is applied to the dynamic model of an unmanned surface vehicle. A simple PID autopilot is incorporated to ensure that the vessel adheres to the generated seaway. It is shown through simulations that the resulting scheme is able to generate viable trajectories in the presence of both stationary and dynamic obstacles. Rules 8 and 14 of the COLREGs, which apply to the amount of manoeuvre and to a head-on scenario respectively are simulated. A comparison is also made with an offline or deliberative grid-based path planning algorithm which has been modified to generate COLREGs-compliant routes.

Feedforward Control of Shape Memory Alloy Actuators Using Fuzzy-Based Inverse Preisach Model

This brief investigates a possible application of the inverse Preisach model in combination with the feedforward and feedback control strategies to control shape memory alloy actuators. In the feedforward control design, a fuzzy-based inverse Preisach model is used to compensate for the hysteresis nonlinearity effect. An extrema input history and a fuzzy inference is utilized to replace the inverse classical Preisach model. This work allows for a reduction in the number of experimental parameters and computation time for the inversion of the classical Preisach model. A proportional-integral-derivative (PID) controller is used as a feedback controller to regulate the error between the desired output and the system output. To demonstrate the effectiveness of the proposed controller, real-time control experiment results are presented.

Optimal proportional-integral-derivative control of shape memory alloy actuators using genetic algorithm and the Preisach model

Shape memory alloy (SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications in aeronautics, surgical tools, robotics, and so on. Although the number of applications is increasing, there has been limited success in precise motion control owing to the hysteresis effect of these smart actuators. The present paper proposes an optimization of the proportional-integral-derivative (PID) control method for SMA actuators by using genetic algorithm and the Preisach hysteresis model.

Trajectory Control of Electro Hydraulic Excavator using Fuzzy Self Tuning Algorithm with Neural Network

This paper presents the trajectory control of a 2DOF mini electro-hydraulic excavator by using fuzzy self tuning with neural network algorithm. First, the mathematical model is derived for the 2DOF mini electro-hydraulic excavator. The fuzzy PID and fuzzy self tuning with neural network are designed for circle trajectory following. Its two links are driven by an electric motor controlled pump system. The experimental results demonstrated that the proposed controllers have better control performance than the conventional controller.