Constrained control algorithm for non-linear control problems

The general non-linear control model presented by Kendrick (1981) is extended to cases where there are both unconstrained and constrained controls. The resulting algorithm is based on the unconstrained control algorithm, so it can be implemented without difficulty in the existing software. Moreover, the algorithm does not require much additional computation, which makes the algorithm rather efficient. An application to a complicated, but practical, economic problem concerning exchange-rate policy illustrates the relevance of the extension of the control model.     

线性不确定时滞系统的可靠保性能鲁棒控制

研究了含有故障执行器的线性不确定时滞系统的可靠保性能鲁棒控制问题.执行器故 障模型概括了执行器正常、执行器部分退化和执行器完全失效三种情况,系统的性能函数是带 有故障输入项的积分二次函数.利用Lyapunov稳定理论及矩阵不等式方法,得到了系统存在可 靠保性能鲁棒控制器的代数矩阵不等式(AMI)形式的充分条件和控制器的设计方法,给出了系 统的一个可保性能的表达式.基于LMI方法,给出了AMI的一个求解算法.一个数值例子说明 结论的可行性.     

基于C8051F920的超空泡通气系统压力控制研究

为了形成精确可控的超空泡形态,在超空泡技术研究中,需要精确控制多路气体流量.提出了以压力直接控制,实现流量间接控制的通气系统控制方案,建立了通气系统的数学模型.提出了通气系统的控制算法,对压力控制环和阀芯开度控制环分别采用比例积分算法和比例算法实现控制压力的目的.以C8051F920单片机为控制器核心,采用压力传感器作为传感元件,调节阀为执行元件,设计出一套压力控制的硬件和软件系统.仿真结果表明,所设计的控制系统鲁棒性好,响应速度快.系统为水下航行体超空泡形态研究提供了可靠的试验平台.     

Constrained multivariable stable predictive control based on Toeplitz equation

A stable constrained multivariable predictive control algorithm based on the Toeplitz predictive equation is presented. An analytical method for transformation between left and right coprime factorization of multivariable system is put forward, and then an unconstrained control law and its stable condition are given. Furthermore, for the constrained multivariable controlled system, a predictive controller and its asymptotically stable condition are presented and proved. Finally, the constrained receding horizon optimization is transformed into a typical linear matrix inequality (LMI) problem and solved. The detailed control algorithm is depicted in a numerical example, and the simulation results reveal the effectiveness and practicability of the presented algorithm. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

An optimal control algorithm for nuclear reactor load cycling

An optimal control algorithm for reactor reactivity controls during CANDU4 nuclear station load cycling is presented. The minimized performance index is reactor operating cost during a load cycling interval. The algorithm is developed using Pontryagin's Maximum principle. A novel non-iterative technique for determining the adjoint multiplier initial values in the resulting two point boundary value problem is used. The analysis considers standard fuel, booster fuel, moderator poison and liquid zone controllers as available reactivity control devices.     

Robust pole placement direct adaptive control

A pole-placement direct adaptive control for not necessarily minimum-phase plants is presented, which is robust with respect to unmodeled dynamics and bounded disturbances. The robustness is achieved by using both a normalized least-squares algorithm with dead zone and appropriate nonlinear feedback. The resulting closed-loop system is shown to be globally stable subject to standard assumptions     

Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators

A stable decentralized adaptive fuzzy sliding mode control scheme is proposed for reconfigurable modular manipulators to satisfy the concept of modular software. For the development of the decentralized control, the dynamics of reconfigurable modular manipulators is represented as a set of interconnected subsystems. A first‐order Takagi–Sugeno fuzzy logic system is introduced to approximate the unknown dynamics of subsystem by using adaptive algorithm. The effect of interconnection term and fuzzy approximation error is removed by employing an adaptive sliding mode controller. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that resulting closed‐loop system is stable and the trajectory tracking performance is guaranteed. The simulation results are presented to show the effectiveness of the proposed decentralized control scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

Adaptive weighted suboptimal control for linear dynamic systems having a polynomial input

Introducing a cost term on the highest power of the nonlinear polynomial, we derive a simple direct adaptive control weighted suboptimal control algorithm which is very useful for the control of all stable nonminimum-phase and some unstable nonminimum-phase linear systems having a polynomial input. Both stochastic and deterministic situations are considered and the global convergence of the proposed algorithm has been established.     

Input-to-state stable finite horizon MPC for neutrally stable linear discrete-time systems with input constraints

MPC or model predictive control is representative of control methods which are able to handle inequality constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global asymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. Furthermore, it is proved that the closed-loop system resulting from the proposed MPC is ISS (Input-to-State Stable), provided that the external disturbance is sufficiently small. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.     

Mechatronic design of the Twente humanoid head

This paper describes the mechatronic design of the Twente humanoid head, which has been realized in the purpose of having a research platform for human-machine interaction. The design features a fast, four degree of freedom neck, with long range of motion, and a vision system with three degrees of freedom, mimicking the eyes. To achieve fast target tracking, two degrees of freedom in the neck are combined in a differential drive, resulting in a low moving mass and the possibility to use powerful actuators. The performance of the neck has been optimized by minimizing backlash in the mechanisms, and using gravity compensation. The vision system is based on a saliency algorithm that uses the camera images to determine where the humanoid head should look at, i.e. the focus of attention computed according to biological studies. The motion control algorithm receives, as input, the output of the vision algorithm and controls the humanoid head to focus on and follow the target point. The control architecture exploits the redundancy of the system to show human-like motions while looking at a target. The head has a translucent plastic cover, onto which an internal LED system projects the mouth and the eyebrows, realizing human-like facial expressions.     

Adaptive,high precision,satellite attitude control for microprocessor implementation

A control system is presented for three-axis, gas jet, satellite attitude control having application to any spacecraft where precise pointing is required within stringent mass and power limitations. Several novel features are incorporated as follows: parabolic switching boundaries are employed with parameters which adapt to a disturbing acceleration estimate in order to achieve a zero offset steady-state limit cycle of preset amplitude in the arcsecond region which minimizes both fuel consumption and thruster operation frequency. The disturbing acceleration estimate is obtained from a third-order state estimator, together with angle error and rate estimates using an angle error measurement from a rate integrating gyro and a jet drive input. Time optimal recovery from large initial angle errors and rapid response to step changes in disturbing acceleration are achieved. In addition, stable control is obtained with disturbing acceleration approaching the control jet acceleration. A slew control algorithm is incorporated which enables the same control law to be utilized for fuel optimal slewing through unlimited angles, one axis at a time. Simulation results are presented, including demonstration of stochastic performance with gyro and jet noise.     

基于龙格库塔法的弹塑性有限元并行计算

基于MPI集群环境对弹塑性区域分解有限元并行计算进行研究。提出了基于三阶和四阶的龙格库塔（Runge-Kutta）方法对应力-应变关系进行积分的算法。积分过程中自动调整子步大小来控制积分过程中的误差。研制了采用最小残余平滑法的子结构预处理共轭梯度并行求解算法。算法在基于工作站机群的并行环境下实现。计算结果表明：该算法具有良好的并行加速比和效率,是一种有效的并行求解算法。     

冷带轧机液压伺服位置系统的鲁棒输出反馈控制

载力的干扰项视为未知输入, 构造未知输入观测器, 然后基于所构造的观测器设计鲁棒输出反馈控制器. 理论分析表明, 所提出的控制方法能够保证闭环系统是一致有界稳定的, 并具有鲁棒H1性能. 最后对某个650mm可逆冷带轧机液压伺服位置系统进行仿真研究, 结果验证了所提出方法的有效性.     

Stabilising feedback control schemes of dynamical systems with completely unknown saturated inputs: an adaptive design method

The objective of this paper is mainly to present a simple design method to synthesise the stabilising feedback control schemes for dynamical systems with input saturations. In this paper, such a simple design method, called an adaptive design method, is presented so that (i) the presented design method is easy to understand for the system designers; (ii) it is not necessary to know any information on the saturated input nonlinearities; and (iii) the resulting control schemes are simple and easy to implement in practical control problems. Here, a linear dynamical system with any unknown saturated input nonlinearities is used to describe this method. For such dynamical systems, by making use of the presented design method, the resulting feedback control schemes consist of a conventional optimal control law and an adaptive control gain, and the resulting closed-loop control dynamical systems are globally stable. By combining the presented adaptive design method with other control ones, a number of interesting results can be expected for a rather large class of dynamical systems with saturation in the actuators. Finally, some illustrative numerical examples are provided to demonstrate the validity of the presented adaptive design method.     

On feedback identification of unknown characteristics: a bioreactor case study

The problem of dynamical identification of unknown characteristics (states/parameters) in a biochemical model of a fed-batch bioreactor system given observations of some states is considered. An algorithm that solves this simultaneous state and parameter estimation problem and that is stable with respect to bounded informational noises and computational errors is presented. The algorithm is based on the principle of auxiliary models with adaptive controls. Convergence of the algorithm is proven and a convergence rate is derived. The performance of the algorithm is illustrated to a typical single-species bioreactor example.     

离散混沌系统的参数自适应控制

提出多重参数离散混沌系统的参数自适应控制的新方法,利用可调系统与参考模型之间的耦合关系,给出基于系统变量作为观测量的参数自适应控制算法,采用Ｌｙａｐｕｎｏｖ函数方法证明了参数控制系统是渐近稳定的。仿真结果表明文中给出的控制算法具有较快的收敛速度,并讨论了系统参数是非线性形式的一般系统及其不确定的外界噪声扰动对系统的影响。     

Sequential synthesis of the time-optimal control in real time

The paper considers the sequential synthesis method for time-optimal control of linear systems. The method is based on piecewise constant finite controls that ensure approximate solutions for time-optimal control problems. A sequence of finite controls is thereafter transformed into the optimal control. The appropriate computations are reduced to a sequence of linear algebraic equation problems and the integration of a matrix differential equation over the intervals of control switching points and final point change. It is proven that the sequence of finite controls converge to the optimal control. The sliding mode conditions are obtained, as well as the control structure modifications for the motions on switching manifolds. The initial approximations reducing considerably computational complexity are considered. The computational algorithm, together with the modelling and numerical results, are presented.     

不确定系统的稳定广义预测控制

针对一类有界不确定线性离散被控对象,采用Min-Max优化方法,提出一种新的稳定广义预测控制(MMSGPC)算法.引入内模控制结构,将干扰和不确定性从被控对象中分离出来,并利用局部反环节对其进行补偿;采用Min-Max优化方法,将终端约束条件转化为有界不确定性最差情况时应的线性方程;通过引入矩阵的Moore-Penrose逆,得到了终端约束线性方程的通解,并结合性能指标函数求得了最优控制律.通过仿真实例验证了该方法的稳定效果.