Optimal constraint tightening policies for robust variable horizon model predictive control

This paper develops a technique for improving the region of attraction of a robust variable horizon model predictive controller. It considers a constrained discrete-time linear system acted upon by a bounded, but unknown time-varying state disturbance. Using constraint tightening for robustness, it is shown how the tightening policy, parameterised as direct feedback on the disturbance, can be optimised to increase the volume of an inner approximation to the controller's true region of attraction. Numerical examples demonstrate the benefits of the policy in increasing region of attraction volume and decreasing the maximum prediction horizon length. © 2012 IEEE.

Design of diesel smoke feedback control using a combination of PI control algorithm and performance optimization

A novel smoke sensor was used to realize smoke feedback control on a diesel engine. The controller design based on a combination of PI control algorithm and the engine performance optimization is described. Experimental results demonstrate how this control system behave to meet both of the speed and smoke requirements during engine transients.

Engine modelling for diesel smoke feedback control system design

A novel smoke sensor was used to measure the smoke response to the fuel rack on a diesel engine. The conventional modelling methods used for engine control were investigated. The synchronization technique and Recursive Least Square method were applied to engine modelling and two models for controller design were derived.

Model-based control of thermoacoustic instabilities in partially premixed lean combustion - A design case study

Self-excited oscillation is becoming a major issue in low-emission, lean partially premixed combustion systems, and active control has been shown to be a feasible method to suppress such instabilities. A number of robust control methods are employed to obtain a feedback controller and it is observed that the robustness to system uncertainty is significantly better for a low complexity controller in spite of the norms being similar. Moreover, we demonstrate that closed-loop stability for such a complex system can be proved via use of the integral quadratic constraint method. Open- and closed-loop nonlinear simulations are provided. © 2013 Copyright Taylor and Francis Group, LLC.

Design trade-offs for energy regeneration and control in vehicle suspensions

This paper investigates the fundamental trade-offs involved in designing energy-regenerative suspensions, in particular, focusing on efficiency of power extraction and its effect on vehicle dynamics and control. It is shown that typical regenerative devices making use of linear-to-rotational elements can be modelled as a parallel arrangement of an inerter and a dissipative admittance. Taking account of typical adjustable parameters of the generator, it is shown, for a given suspension damping coefficient, that the power efficiency ratio scales with inertance. For a typical passenger vehicle, it is shown that there is a feasible compromise, namely that good efficiency is achievable with an inertance value that is not detrimental to vehicle performance. A prototype is designed and tested with a resistive termination and experimental results show good agreement between ideal and experimental admittances. The possibility to use dynamic (rather than purely resistive) loads to improve vehicle control without limiting the energy recovery is discussed. © 2013 Copyright Taylor and Francis Group, LLC.

Identification of the steering control behaviour of five test subjects following a randomly curving path in a driving simulator

The paper is concerned with the identification of theoretical preview steering controllers using data obtained from five test subjects in a fixed-base driving simulator. An understanding of human steering control behaviour is relevant to the design of autonomous and semi-autonomous vehicle controls. The driving task involved steering a linear vehicle along a randomly curving path. The theoretical steering controllers identified from the data were based on optimal linear preview control. A direct-identification method was used, and the steering controllers were identified so that the predicted steering angle matched as closely as possible the measured steering angle of the test subjects. It was found that identification of the driver's time delay and noise is necessary to avoid bias in identification of the controller parameters. Most subjects' steering behaviour was predicted well by a theoretical controller based on the lateral/yaw dynamics of the vehicle. There was some evidence that an inexperienced driver's steering action was better represented by a controller based on a simpler model of the vehicle dynamics, perhaps reflecting incomplete learning by the driver. Copyright © 2014 Inderscience Enterprises Ltd.

Design and control of a climbing robot based on hot melt adhesion

Robust climbing in unstructured environments has been one of the long-standing challenges in robotics research. Among others, the control of large adhesion forces is still an important problem that significantly restricts the locomotion performance of climbing robots. The main contribution of this paper is to propose a novel approach to autonomous robot climbing which makes use of hot melt adhesion (HMA). The HMA material is known as an economical solution to achieve large adhesion forces, which can be varied by controlling the material temperature. For locomotion on both inclined and vertical walls, this paper investigates the basic characteristics of HMA material, and proposes a design and control of a climbing robot that uses the HMA material for attaching and detaching its body to the environment. The robot is equipped with servomotors and thermal control units to actively vary the temperature of the material, and the coordination of these components enables the robot to walk against the gravitational forces even with a relatively large body weight. A real-world platform is used to demonstrate locomotion on a vertical wall, and the experimental result shows the feasibility and overall performances of this approach. © 2013 Elsevier B.V. All rights reserved.

Design and control of a pendulum driven hopping robot

In this paper a new kind of hopping robot has been designed which uses inverse pendulum dynamics to induce bipedal hopping gaits. Its mechanical structure consists of a rigid inverted T-shape mounted on four compliant feet. An upright "T" structure is connected to this by a rotary joint. The horizontal beam of the upright "T" is connected to the vertical beam by a second rotary joint. Using this two degree of freedom mechanical structure, with simple reactive control, the robot is able to perform hopping, walking and running gaits. During walking, it is experimentally shown that the robot can move in a straight line, reverse direction and control its turning radius. The results show that such a simple but versatile robot displays stable locomotion and can be viable for practical applications on uneven terrain.

Intelligent control of avalanched photodiode to get optimal state

To improve the sensitivity of our laser radar system, we provided a set of control method for APDs (Avalanched Photodiodes) based on single-chip computer together with the circuits dealing with noise and temperature. It adjusts the voltages intelligently and maintains the APD's optimal working status.

重离子加速器注入器电源控制器的设计；Design of digital power control system applied in sector focusing cyclotron

设计了一种应用于兰州重离子加速器注入器的电源控制器,该控制器基于微处理器AT-mega128,结合MAX7000系列的复杂可编程器件和RTL8019AS网关芯片来实现对电源系统的控制,并通过RS-232总线实现与上位机的串口通信。应用结果表明,该控制器具有良好的通用性、灵活性、可远程控制及性能稳定等特点,实现了注入器磁铁电源10-4量级的幅度稳定性,使注入器引出的束流强度、束流品质、束流稳定性和供束效率等得到很大的提高。

兰州重离子加速器团簇内靶装置控制系统设计；Design of a Control System for HIRFL-CSRe Internal Target Facility in Lanzhou

介绍了兰州重离子加速器冷却储存环(HIRFL-CSR)的实验环(CSRe)团簇内靶装置控制系统的设计。该内靶系统由多种设备构成,包括喷嘴测温与加热控制子系统、真空与阀门监测/控制子系统、分子泵监测与控制子系统、数据处理与流程软件子系统等部分。该系统在内靶实验中工作状态良好,满足了内靶实验的需求。在该控制系统的支持下,2010年1月第一轮辐射电子俘获物理实验顺利完成。

基于克隆选择算法的非线性优化迭代学习控制；Clonal selection algorithm based nonlinear optimal iterative learning control

为实现对模型不确定的有约束非线性系统在特定时间域上输出轨迹的有效跟踪,将改进的克隆选择算法用于求解迭代学习控制中的优化问题。提出基于克隆选择算法的非线性优化迭代学习控制。在每次迭代运算后,一个克隆选择算法用于求解下次迭代运算中的最优输入,另一个克隆选择算法用于修正系统参考模型。仿真结果表明,该方法比GA-ILC具有更快的收敛速度,能够有效处理输入上的约束以及模型不确定问题,通过少数几次迭代学习就能取得满意的跟踪效果。