Design of discrete time adaptive PID control systems with parallel feedforward compensator

This paper deals with the design of an adaptive PID control system with a parallel feedforward compensator (PFC) for discrete-time SISO systems and its application to water level control of a 3-tank system. The proposed method utilizes the characteristics of almost strict positive realness (ASPR) of the controlled plant. A conventional design scheme of a PFC which realizes an ASPR augmented controlled plant is also proposed. Further it is shown that the introduction of an internal model improves the control performance of the control system with the PFC. The effectiveness of the proposed method is confirmed through water level control experiments on a three-tank SISO system.     

Adaptive Output Feedback based Output Tracking Control for a Time‐Delay System with a PFC

This output tracking control system for time‐delay systems with a parallel feedforward compensator (PFC). It has been clarified that one can design an adaptive output tracking control system for systems with almost strictly positive real (ASPR) properties. However, the robust stability for non‐ASPR time‐delay systems with a PFC introduced for making the resulting augmented system ASPR has not been analyzed. In this paper, it will be clarified that one can design a stable adaptive output tracking control system for time‐delay systems with a PFC, even if the resulting augmented system is not exactly ASPR.     

A combined QFT/H ∞ design technique for TDOF uncertain feedback systems

A new way of incorporating QFT principles into H X -control design techniques for solving the two-degrees of freedom feedback problem with highly uncertain plants is developed. The proposed practical design approach consists of two stages. In the first stage, the robustness problem, due to plant uncertainties, is solved by H X -norm optimization. In this stage, the controller inside the loop (the first degree of freedom) is designed, with the ultimate goal of minimizing the cost of feedback. Minimization of the sensor white noise amplification at the input to the plant is also performed using QFT principles. In the second stage of the design, the prefilter outside the loop (the second degree of freedom), is used to achieve the tracking specifications by conventional classical control theory, as practiced by the QFT design procedure. The combined QFT/H X design procedure for single input-single output (SISO) feedback systems is directly applicable to multi input-multi output (MIMO) feedback uncertain systems. The efficiency of the proposed technique is demonstrated with SISO and MIMO design examples for higly uncertain plants.     

Linear unstable plants with saturating actuators: Robust stabilization by a time varying sliding surface

This paper proposes the use of a time-varying sliding surface for the robust stabilization of linear uncertain SISO plants with saturating actuators. A constructive procedure for its design is also proposed, and stability of the closed loop system is proved in the null controllable region. The proposed technique does not require plant stability, and can manage any bounded disturbance term satisfying the matching condition. Theoretical results have been validated by simulation using the missile roll angle control problem.     

Design of low‐order controllers satisfying sensitivity constraints for unstructured uncertain plants

This paper presents a simple analytically based algorithm for the design of reduced‐order controllers satisfying frequency‐dependent sensitivity specifications for SISO plants having unstructured uncertainty. The uncertainties can be additive as well as multiplicative, and can take the form of circles, polygons or sectors located around a nominal plant. Moreover, the circle radius and polygon and sector sizes may depend on the frequency. The proposed method is applicable to both continuous and discrete designs. Copyright © 2004 John Wiley & Sons, Ltd.     

Direct passivity of a class of MIMO non-linear systems using adaptive feedback

In this paper, an adaptive controller with adaptive laws specially designed is proposed to solve the problem of making a multi-input multi-output (MIMO) non-linear system, with explicit linear parametric uncertainty, equivalent to a passive system. These results are an extension of those obtained by the authors for the SISO case. Some stability issues associated to the resultant closed-loop passive system are also discussed. The results obtained are applied to models of dynamical MIMO systems, to illustrate the controller design methodology.     

Controller parameterization for SISO and MIMO plants with time delay

Controller parameterization is a very fundamental problem in control theory. It provides an elegant and efficient way towards solving the stabilizing and design problem, with which all stabilizing controllers are characterized and thus a constrained design procedure can be replaced by an unconstrained optimization. In this paper we deal with the problem of characterizing all stabilizing controllers for single-input/single-output (SISO) plants with time delay and multi-input/multi-output (MIMO) plants with multiple time delays. A new parameterization is derived on the basis of the definition of the internal stability. The new parameterization does not depend on the coprime factorization of the plant and has similar form to that of the Youla parameterization for stable plants. An important merit of the proposed parameterization is that it reflects the internal model control (IMC) structure and thus has a very simple relationship to the sensitivity function and complementary sensitivity function. Numerical examples are given to illustrate the proposed parameterization.     

具有不确定性时滞及仿射结构不确定性过程的简易自适应控制

讨论了具有不确定性时滞及仿射结构不确定系统的简易自适应控制问题.给出了对系统再建模方法,所提出的方法可更精确评价不确定性时滞.通过对受控对象附加鲁棒并行补偿器补偿,设计了简易自适应控制器.     

Design and Experimental Evaluation of a Discrete‐time ASPR‐based Adaptive Output Feedback Control System Using FRIT

This paper describes the design of an adaptive output feedback control system in discrete‐time, based on almost strictly positive real (ASPR)‐ness with a feedforward input. It is well‐known that an adaptive output feedback control system based on ASPR conditions can achieve asymptotic stability via a constant feedback gain. Unfortunately, most realistic systems are not ASPR because of the severe conditions. The introduction of a parallel feedforward compensator (PFC) is an efficient way to alleviate such restrictions. However, the problem remains that there exists a steady state error between the output of the augmented system and the output of the original system. The proposed scheme provides a strategy wherein the feedforward input is utilized such that the steady state error is removed. Furthermore, the fictitious reference iterative tuning (FRIT) approach is employed to determine the control parameters using one‐shot input/output experimental data directly, without prior information about the control system. This paper explains how the FRIT approach is applied in designing an adaptive output feedback control system. The effectiveness of the proposed scheme is confirmed experimentally, by using a motor application.     

Hybrid-based adaptive NN backstepping control of strict-feedback systems

Hybrid-based adaptive NN backstepping tracking control designs for both the single-input/single-output (SISO) and the square multi-input/multi-output (MIMO) strict-feedback systems with unknown system nonlinearities are presented. Each virtual/actual controller in these designs contains four main parts: a single-layer radial basis function neural network (RBFNN) for re-parameterizing the unknown nonlinearity to render the adaptive control applicable; an adaptive linearizing controller for compensating the resembled nonlinearities; a supervisory agent which hands over temporarily the control authority to the fourth part of a robust controller during the singularity. The proposed design ensures the semiglobal uniform ultimate boundedness (SGUUB) of all the closed-loop signals and compared with existing schemes has a wider applicability with a simpler structure. Simulation results demonstrating the validity of the proposed design are given in the final section.     

MIMO design models and internal regulators for cyclicly switchedparameter-adaptive control systems

In Pait and Morse (1994) the concept of “cyclic switching” was proposed as a means of dealing with the well-known stabilizability problem, which arises in adaptive controller synthesis because of the existence of points in parameter space where the design model upon which certainty equivalence control is based loses stabilizability. While the procedure outlined in the above paper is specific enough to enable one to construct cyclicly switched adaptive controllers for SISO process models, for the MIMO case two key issues are left unresolved. The objective of this paper is to address both of these issues, thereby extending excitation free, identifier-based adaptive control methods to minimum and nonminimum phase MIMO linear systems     

Simple adaptive control of processes with time-delay

This paper is concerned with the development of tuning guidelines and robustness evaluation tools for a simple adaptive control (SAC) scheme. The adaptive technique requires knowledge of only the relative degree of the plant and an upperbound of the process gain. This is an explicit or direct adaptive scheme. The SAC method is evaluated by simulated applications to two processes. The application of SAC to a process with time-delay is also considered in this paper. This issue has both theoretical, because of the strictly positive real (SPR) requirements, as well as practical appeal. Simulation results show the practicality and usefulness of the proposed algorithm.     

一种H∞混合灵敏度控制器设计方法

传统的输出反馈H∞优化控制设计比较复杂,由于控制器的阶数要远远高于实际系统的阶数,在实际工业控制过程中不容易实现。从次优控制的角度出发,利用量子粒子群算法解决特定结构的H∞混合灵敏度优化控制设计。对带有超前/滞后环节控制器的SISO锁相闭环摩托速度系统和PI 型控制器的MIMO超级机动F18/harv 战斗机系统使用量子粒子群算法进行了分析,并和GA算法进行了比较。实验仿真显示了量子粒子群算法的有效性。     

基于CARMA模型多变量系统的j步输出预估

用于广义预测控制（GPC）的单变量j步预估器传统上是在多项式域采用丢番图方程导出的,针对与其等价的状态空间形式预估器,对该预估器的多变量扩展进行了z域分析,得到一个多项式域的基于CARMA模型的多变量j步预估器．该预估器可以简化多变量系统的GPC算法设计,在单变量情形,该预估器即为传统的GPC预估器,最后提供了传统GPC预估器与状态空间形式预估器等价性的严格证明．     

基于精确线性化的MIMO双线性系统预测函数控制

针对典型多输入多输出双线性系统, 提出了基于非线性过程精确反馈解耦线性化的预测函数控制方法这是一种分层的控制策略, 首先设计一个静态的非线性状态反馈, 使得闭环系统是输入输出解耦和线性的;然后设计一组单输入单输出预测函数控制器, 下层为上层预测函数控制提供一组单输入单输出模型, 而上层预测函数控制以其固有的鲁棒性来补偿参数变化和解耦线性化的近似性, 并以纸机加压网前箱为例进行了仿真实验, 结果是令人满意的.     

Adaptive sampling with automatic stopping for feasible region identification in engineering design

Engineering design is a complex process to find a suitable trade-off among different, and sometimes conflicting, design specifications. In reality, these requirements can be often considered as constraints of the design problem, that can be defined in terms of performance measures or geometrical characteristics of the device under study. In this paper, a new design space exploration methodology is presented for discovering feasible regions in the design space, where the term feasible region indicates the set of all design configurations satisfying all constraints of the design problem. The proposed method is based on Gaussian process metamodels to estimate the feasible region and leverages a information-based adaptive sampling technique to sequentially refine the prediction accuracy, which is applicable for multiple constraints problems. To efficiently stop the adaptive sampling process, a novel framework to estimate the metamodel’s prediction accuracy is proposed. The efficiency, accuracy and robustness of the proposed approach are compared with state-of-art techniques on suitable benchmark problems and practical engineering examples.

     

The singular-G method for unstable non-minimum-phase plants†

In linear time-invariant feedback systems with plants which have both poles and zeros in the right half-plane, it is always possible to stabilize the system for a fixed plant. But in the previous optimum techniques, the stability margins might be so small as to render the design wholly impractical. This problem was overcome in the X-29 aircraft in a multiple-input-multiple-output (MIMO) setting, by use of a singular-G (compensation) matrix inside the loop. Excellent stability margins were then achievable over a wide plant parameter range, by means of a fixed-G compensation matrix.

This paper extends the singular-G technique to the single-input-single-output (SISO) plant. The latter is converted into an equivalent N × N MIMO plant by means of N parallel independent time-varying modulators acting on the plant output, a technique previously used for non-linear network synthesis. The singular-G method is then applicable to the equivalent N × N MIMO plant. The detailed design procedure is presented by means of an example with N = 2.     

二维直线电机的多入多出无模型自适应轮廓控制

针对传统的单入单出控制器无法解决二维直线电机存在的非线性,不确定性以及强耦合作用等问题,依据无模型自适应控制不依赖于被控系统精确数学模型,仅需受控系统输入输出数据便能实现自适应控制这一特点,采用多入多出的紧格式动态线性化无模型自适应控制算法对二维直线电机XY轴进行整体控制器设计.同时,针对二维直线电机这种含有纯二阶积分环节的非自平衡系统,提出了多入多出无模型自适应控制改良方法,并进行严格的稳定性和收敛性证明.为了提高二维直线电机的轮廓精度,在多入多出无模型自适应控制改良方法的基础上,加入交叉耦合控制器,与传统的交叉耦合控制方法相比较,提高了跟踪精度和轮廓精度.最后通过仿真和实物实验证明了所提方案的有效性.     

Operator-Based Robust Nonlinear Control for SISO and MIMO Nonlinear Systems With PI Hysteresis

In this paper, operator based robust nonlinear control for single-input single-output (SISO) and multi-input multi-output (MIMO) nonlinear uncertain systems preceded by generalized Prandtl-Ishlinskii (PI) hysteresis is considered respectively. In detail, by using operator based robust right coprime factorization approach, the control system design structures including feedforward and feedback controllers for both SISO and MIMO nonlinear uncertain systems are given, respectively. In which, the controller design includes the information of PI hysteresis and its inverse, and some sufficient conditions for the controllers in both SISO and MIMO systems should be satisfied are also derived respectively. Based on the proposed conditions, influence from hysteresis is rejected, the systems are robustly stable and output tracking performance can be realized. Finally, the effectiveness of the proposed method is confirmed by numerical simulations.      

Output feedback control for MIMO non-linear systems with unknown sign of the high frequency gain matrix

The paper presents a new output feedback adaptive control scheme for multi-input and multi-output (MIMO) non-linear systems whose non-linear terms depend only on the output variable based on the backstepping approach with vector form. The assumption on the prior knowledge of the high frequency gain matrix in existing results is reduced and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. This control scheme guarantees the global stability of the closed-loop systems and makes the tracking error be arbitrary small. A simulation example is included to demonstrate the proposed algorithm.