一种有限时间响应复合数字控制算法

本文提出一种对于设定值扰动和受控系统扰动都能适用的有限时间响应复合数字控制算法,可有效的抑制扰动,使系统获得理想的控制效果。根据该算法设计控制器简单且便于微机实现,可用于一般的工业过程控制。     

基于抗干扰的Smith预估控制改进方法研究

针对工业过程控制系统设计的核心之一抗干扰问题,就自平衡对象,对Smith预估控制提出了三种循序渐进的改进方案,分别从不同角度讨论了如何提高系统的抗干扰性能和模型失配时的稳定性问题。针对干扰进入系统的位置不同,主要找到Smith预估器在定值系统中调节效果不明显的原因,对其结构进行改进并选取一阶典型环节加上纯滞后环节进行研究和Simulink仿真。改进方案实现了将设定值和扰动响应分离,使得跟踪控制器和扰动器可以独立设计,从而可同时获得良好的设定值跟踪和抑制扰动的能力。     

大时滞工业过程的双控制器结构

提出一种简单实用的双控制器方案,用于大时滞工业过程控制.该方案含两个独立 的控制器,即跟踪控制器和扰动控制器,使设定值响应得以与扰动响应分离,从而可同时获得 良好的设定值跟踪性能和抗干扰能力.双控制器系统含过程模型,但对过程模型不敏感,因而 鲁棒性好.文中将两个控制器设计为比例加积分(PI)类型,给出了具体的参数整定方法.     

非自衡时滞对象的改进内模控制

针对化工生产中常见的具有积分和时滞特性的过程对象，采用一种改进的两自由度内模控制方案．其中一个新增的控制器用于设定值跟踪响应的期望极点配置，利用直接合成法设计设定值跟踪控制器；另一个新增的控制器用于稳定对象和抑制扰动，并采用期望闭环余灵敏度法确定控制器．设定值跟踪控制器和扰动抑制控制器可通过性能参数独立调节，并保证系统具有较好的鲁棒稳定性．最后，通过仿真实例验证了控制方案的有效性．     

用比例控制器实现对扰动的全补偿

为了获得用比例控制器实现对可测量扰动的全补偿和将扰动响应与设定值响应分别处理，本文提出了一种多控制器策略。它由四个控制器，即：一个设定值控制器、两个扰动控制器和一个比例前馈控制器。这四个控制器可以分别独立设计获得好的设定值跟踪和抗扰动性能，特别是其前馈控制器是比例型的，可实现对可测量扰动的全补偿并保证了前馈控制器的可实现性。最后将该控制策略应用于压力槽的实时控制中，获得了良好的控制性能。     

非自衡时滞对象的改进内模控制

针对化工生产中常见的具有积分和时滞特性的过程对象,采用一种改进的两自由度内模控制方案．其中一个新增的控制器用于设定值跟踪响应的期望极点配置,利用直接合成法设计设定值跟踪控制器;另一个新增的控制器用于稳定对象和抑制扰动,并采用期望闭环余灵敏度法确定控制器．设定值跟踪控制器和扰动抑制控制器可通过性能参数独立调节,并保证系统具有较好的鲁棒稳定性．最后,通过仿真实例验证了控制方案的有效性．

     

基于改进Smith预估控制结构的二自由度PID控制

针对工业过程中的二阶不稳定时滞过程, 基于改进史密斯预估控制结构提出了一种简单的两自由度控制方案.设定值跟踪控制器和扰动抑制控制器采用同一设计程序, 并基于内模控制原理提出了控制器解析设计方案.设定值跟踪控制器和抗扰动控制器可分别通过单性能参数独立调节和优化, 每个控制器都具有PID形式, 给出了控制器调整参数的选择范围和扰动抑制闭环保证鲁棒稳定性的条件.仿真实例验证了提出方法对于近期其他方法的优越性.     

化工不稳定时滞对象的改进内模控制

针对化工过程中典型不稳定时滞对象,基于传统内模控制提出了两自由度控制方案,新增两个控制器分别用于稳定控制对象和抑制扰动,在镇定不稳定过程的基础上,设定值跟踪控制器和扰动抑制控制器可独立调节而无需再取折衷,同时保证系统具有较好的鲁棒稳定性.最后通过仿真实例验证了该控制方案的有效性.     

不稳定时滞对象的二自由度控制器设计

在工业生产过程中,特别是化工领域,许多单元属于开环不稳定过程,特别还存在时滞特性;针对此情况,提出了一种二自由度响应控制结构,该结构优点是设定值跟踪与扰动响应完全解耦,分别对设定值跟踪控制器和扰动控制器两个参数进行独立调节,而无需进行折中,保证了系统的稳定性和鲁棒性;最后对一阶二阶不稳定时滞系统的仿真结果表明,所提出的二自由度控制结构能够有效地解决系统的稳定鲁棒性和扰动抑制作用。     

基于阶跃响应的非自衡对象预测控制

针对现有非自衡对象DMC算法预测模型不易建立的局限性,提出一种基于非自衡对象阶跃响应的DMC算法。分析与仿真结果表明,该算法对于设定值变化和输入扰动均无控制余差,且预测模型易于建立。     

Optimal control of non-minimum phase integrating processes with time delay using disturbance observer-based control scheme

A systematical design method of optimal control for non-minimum phase integrating processes with time delay using disturbance observer-based (DOB) control scheme is presented. All stabilising controllers and the filter of DOBs for integrating plants are developed. Then the optimal set-point tracking controller and the optimal filter of DOB are systematically derived by minimising the H₂ norm performance specifications. The proposed design method has three main advantages. First, the design procedure is systematical and simple. Specified weight functions are chosen for step inputs and inputs similar to steps. The designed set-point tracking controller and the filter of DOB are given in analytical forms. Second, the designed set-point tracking controller and the filter of the DOB are optimal. They are derived from minimising the performance indexes of set-point tracking and input load disturbance rejection (ILDR). Finally, the set-point tracking performance specification and ILDR specification can be quantitatively achieved by conveniently tuning the adjustable parameters. Numerical simulations are given to illustrate the effectiveness of the proposed method.     

Design and implementation of a neuro-adaptive backstepping controller for buck converter fed PMDC-motor

A neuro-adaptive backstepping control (NABSC) method using single-layer Chebyshev polynomial based neural network is proposed for the angular velocity tracking in buck converter fed permanent magnet dc (PMDC)-motor. Owing to their universal approximation property, neural networks have been utilized for approximating the unknown nonlinear profile of instantaneous load torque. The inherent computational complexity of the neural network based adaptive scheme has been circumvented through the use of orthogonal Chebyshev polynomials as basis functions. A detailed stability and transient performance analysis has been conducted using Lyapunov stability criteria. The proposed control scheme is shown to yield a superior output performance with enhanced robustness for wide variations in load torque and set-point changes, compared to existing conventional approaches based on adaptive backstepping. The theoretical propositions are verified on an experimental prototype using dSPACE, Control Desk DS1103 setup with an embedded TM320F240 Digital Signal Processor proving its applicability to real-time electrical systems. The efficiency of the proposed strategy is quantified using performance measures and are evaluated against the conventional adaptive backstepping control (ABSC) methodology. Ultimately, this investigation confirms the effectiveness of the proposed control scheme in achieving an enhanced output transient performance while faithfully realizing its control objective in the event of abrupt and uncertain load variations.     

Adaptive nonlinear control of pH neutralization processes using fuzzy approximators

In this paper, an adaptive control scheme, based on fuzzy logic systems, for pH control is addressed. For implementation of the proposed scheme no composition measurement is required. Stability of the closed-loop system is established and it is shown that the solution of the closed-loop system is uniformly ultimately bounded and under a certain condition, asymptotical stability is achieved. Effectiveness of the proposed controller is tested through simulation and experimental studies. Results indicate that the proposed controller has good performances in set-point tracking and load rejection and much better than that of a tuned PI controller.     

A double two-degree-of-freedom control scheme for improved control of unstable delay processes

A double two-degree-of-freedom control scheme is proposed for enhanced control of unstable delay processes. The scheme is motivated by the modified Smith predictor control in [IEE Proc. Control Theory Appl. 16(5) (1999) 359] and devised to improve in the following ways: (i) one more freedom of control is introduced in our scheme to enable manipulation of disturbance transient response, and is tuned based on minimization of the integral squared error criterion; (ii) four controllers in the scheme are well placed to separately tune the denominators and numerators of closed-loop transfer functions from the set-point and disturbance. This allows easy design of each controller and good control performance for both set-point and disturbance responses. Especially, improvement of disturbance response is extremely great, compared with [IEE Proc. Control Theory Appl. 16(5) (1999) 359; Automatica 36 (2000) 1651]. Internal stability of the proposed structure is analyzed, which has not been reported in the literature on modified Smith predictor control before. Examples are provided for illustration.     

Two degree-of-freedom design for a send-on-delta sampling PI control strategy

A complete event-based two-degree-of-freedom PI controller is presented. The architecture of the control system is based on two decoupled PI controllers, one for the set-point following and one for the load disturbance rejection task. The distinctive feature of the proposed approach is that the two controllers have the same parameters and the reference tracking performance is improved by suitably modifying the reference signal applied to the set-point following controller. Examples of the technique are given. In particular, the control strategy has been applied to a distributed solar collector field.     

A multivariable control scheme in a two-stage anaerobic digestion system described by partial differential equations

This paper deals with the design and application of a nonlinear multivariable controller in an anaerobic digestion system (AD) carried out in two interconnected fixed bed bioreactors. The proposed control scheme is derived from a mathematical model of the AD system described by a set of partial differential equations and consists of an estimator and two nonlinear control laws. The first law is developed to regulate the volatile fatty acids in the first bioreactor while the second aims at maintaining the chemical oxygen demand at predetermined set-points in the second bioreactor. The performance of the control algorithm is evaluated via numerical simulations in the face of load disturbances, parameter kinetic uncertainties and set-point changes. Stability and convergence properties of the proposed control scheme are also addressed in this paper.     

Robust proximate time-optimal servomechanism with speed constraint for rapid motion control

A control scheme is proposed to achieve fast and accurate set-point servo motion in typical double integrator systems subject to disturbances and speed constraint. The controller consists of a Proximate Time-optimal Servomechanism (PTOS) control law and a compensation term for the unknown disturbance. An extended state observer is adopted to estimate the un-measured velocity signal and the unknown disturbance. In the presence of speed constraint, a speed regulation stage is incorporated between the PTOS acceleration and deceleration stages. The closed-loop stability is analyzed theoretically. The control scheme is then applied to the position-velocity control loop in a permanent magnet synchronous motor servo system for set-point tracking. MATLAB simulation has been conducted, followed by experimental verification based on the TMS320F2812 DSP controller board. The results confirm that the proposed control scheme can track a wide range of target references fast and accurately, and has good performance robustness with respect to the disturbance and parameter variations.     

An automatic tuning methodology for a unified dead-time compensator

In this paper, an automatic tuning methodology for a modified Smith predictor control scheme is proposed. The main feature of the procedure is that it is applied in closed-loop (by either evaluating a set-point or a load disturbance step response) and it is suitable for self-regulating, integral and unstable processes. Further, the process parameter estimation technique is based on the evaluation of the integral of signals, thus making it inherently robust to measurement noise. Simulation and experimental results demonstrate the effectiveness of the methodology.     

Neural network control of multivariable processes with a fast optimisation algorithm

A radial basis function (RBF) neural network model based predictive control scheme is developed for multivariable nonlinear systems in this paper. A fast convergence algorithm is proposed and employed in multidimensional optimisation in the control scheme to reduce the computing time and save required computer memory. The scheme is applied to a simulated two-input two-output nonlinear process for set-point tracking control. Simulation results demonstrate the effectiveness of the control strategy and the fast learning algorithm for multivariable non-linear processes. Comparison of the performance with PID control is included.     

具有时滞的积分和不稳定对象的鲁棒控制

针对含时滞的积分和不稳定对象提出了一种新颖的两自由度控制结构,首先用一个比例控制器镇定给定值响应,然后基于鲁棒H₂最优性能指标设计给定值跟踪控制器.根据实际运行抗干扰要求,在对象输入和输出端之间设计负载扰动抑制闭环,利用扰动观测器抑制负载干扰信号,通过提出期望的闭环余灵敏度函数来确定扰动观测器,同时给出了扰动抑制闭环保证鲁棒稳定性的充要条件.最后通过仿真实例验证了该方法相对于近期其它方法的优越性.