Direct data‐driven design of switching controllers

Switching linear models can be used to represent the behavior of hybrid, time‐varying, and nonlinear systems, while generally providing a satisfactory trade‐off between accuracy and complexity. Although several control design techniques are available for such models, the effect of modeling errors on the closed‐loop performance has not been formally evaluated yet. In this paper, a data‐driven synthesis scheme is thus introduced to design optimal switching controllers directly from data, without needing a model of the plant. In particular, the theory will be developed for piecewise affine controllers, which have proven to be effective in many real‐world engineering applications. The performance of the proposed approach is illustrated on some benchmark simulation case studies.     

An equation error method for the design of digital controllers

The purpose of the proposed equation error technique is to design a digital controller such that the response of the resulting closed-loop system matches approximately a specified response. The technique is based on the minimization of the equation error in closed loop. The necessary and sufficient condition for minimizing the equation error is given, and is used in the design method     

Implementation of digital controllers

The variance of error at the output of a digital control system due to input data quantization and product rounding in a digital controller is derived. Two forms of controller implementations are considered. Then an expression for the word length that yields a specified variance of error is determined. Scaling is then discussed and an example consisting of a discrete integral plus proportional controller is presented.     

Modified internal model control approach to the design and tuning of linear digital controllers

A new approach to the design and tuning of two degrees of freedom linear digital controllers is presented. The important properties of the proposed method are that the controller structure is directly obtained from the model used and that a small number of adjustable parameters can be easily tuned manually to obtain high closedloop system performance both in the set-point response and in the load disturbance rejection. The method is applicable on both type-0 and-1 plants and is effective in the presence of a poorly damped complex-conjugate pole pair, a non-minimum phase zero or a dead-time. The proposed design and tuning procedures are illustrated by simulation examples, including the analysis of the IFAC '93 benchmark control problem.     

GA-based intelligent digital redesign of fuzzy-model-based controllers

Intelligent digital redesign involves converting a continuous-time fuzzy-model-based controller into an equivalent discrete-time counterpart for the digital control of continuous-time nonlinear systems by using the Takagi-Sugeno (TS) fuzzy models. In this paper, the authors present a new global state-matching intelligent digital redesign method for nonlinear systems by using genetic algorithms (GAs). More precisely, the intelligent digital redesign problem is converted to an equivalent optimization problem, and then GAs are adopted to find a solution. The search space, in which each problem variable is defined for GAs, are systematically obtained by the interval arithmetic operations. The proposed method results in global matching of the states of the analogously controlled system with those of the digitally controlled system while the conventional intelligent digital redesign method does not. The Chen's chaotic system is used as an illustrative example to show the effectiveness and the feasibility of the developed method. The proposed method provides a new approach for the digital redesign of a class of fuzzy-model-based controllers.     

On analytical design of controllers

A method to design controllers of linear plants under bounded sectionally continuous external disturbances was proposed.     

不确定性直接转矩控制系统

在异步电动机直接转矩控制系统中,由于定子电阻变化及负载扰动的不确定性,导致定子磁链、转子转速和电磁转矩估计不准确,从而影响系统的调速性能.本文基于扩展Kalman 滤波器,引进虚拟噪声补偿技术,然后采用sage 和Husa 噪声统计估值器,构成鲁棒扩展Kalman 滤波器.并将定子电流,定子磁链,转子转速,定子电阻及负载作为状态变量,基于鲁棒扩展Kalman 滤波器进行了大量实验研究.实验结果证实：状态变量能够准确估计,且转矩脉动优于常规的直接转矩控制方案,实现了高性能无速度传感器的直接转矩控制系统.     

Analysis of digital controllers using frequency-dependent describing functions

Once a digital control system has been coded and implemented on a computer, simulation must usually be relied on for testing the controller. Proving that a controller is stable requires exhaustive testing. This note discusses the computation and application of frequency-dependent describing functions to nonlinear digital controllers once the controller has been implemented on a computer.     

Suboptimal design of intentionally nonlinear controllers

A method of designing nonlinear controls for stationary plants is presented in the paper. The objective of the design is to produce soft-saturation-type constraints on certain state variables, such as velocity or acceleration. This is accomplished by formulating the problem as an optimization of a nonquadratic performance index. A sequence of suboptimal controls is then obtained. Although this sequence converges to the exact optimum solution, the procedure is stopped when the complexity of the resulting non-linear controller exceeds the design considerations of cost, size, and/or reliability. Experimental results of an actual design clearly indicate the desired velocity saturation effects.     

Hardware design of asynchronous fuzzy controllers

This paper presents a hardware approach to the design of fuzzy controllers which, by exploiting some peculiar characteristics of fuzzy logic computation, allows one to save power consumption and increase computing speed. We show that the computation involved in a fuzzy controller has some statistic features that can be exploited by asynchronous computation. This paper presents a quantitative study of the statistical properties of fuzzy computation. A design methodology is introduced, and two experimental applications are shown     

A frequency response matching method for the design of digital controllers with constraints on the pole-zero locations

The purpose of the frequency response matching technique is to design a digital controller such that the frequency response of the resulting closed-loop system matches a specified frequency response model. The simplex method is employed to determine the controller's parameter values which minimize a function of the error between the two responses. This method permits constraints on the controller's gain and the pole-zero locations to be applied, for example, in order to reduce the highly oscillatory response of the output of the controller, a phenomenon which can be observed when applying other frequency response matching techniques. An example illustrating the use of the method, particularly at low sampling frequencies, is given.     

Feedforward digital tracking controllers for motion control applications

This paper reviews digital tracking control algorithms for motion control applications. In tracking control, the control objective is to steer the control object along the time-varying desired output. Two design approaches are presented for the case where the desired signal is known in advance, i.e. previewable. One approach is based on the mathematical inverse of a closed-loop system consisting of a controlled plant and a feedback controller. If the mathematical inverse is asymptotically stable, i.e. the closed-loop system does not possess zeros outside the unit circle (unstable zeros), it is an ideal feedforward controller for achieving perfect tracking under the preview assumption. For closed-loop systems with unstable zeros, a cancellation technique for the phase shift induced by unstable zeros is introduced. Another approach is based on linear quadratic optimal control and is known as finite optimal preview control. In this approach, the feedback controller and feedforward controller are determined simultaneously by minimizing a quadratic performance index which involves a tracking error term and a term related to the control effort. Applications of these tracking control algorithms to mechanical systems control are described.     

Adaptive computed torque control for rigid link manipulations

In this paper we shall examine the adaptive control of rigid link manipulator systems. Linear estimation techniques together with a computed torque control law are shown to give a globally convergent adaptive system which does not require measurements of accelerations.     

旋挖钻机数字控制系统

介绍了一种专门为旋挖钻机的垂直起竖和井深测量而设计的控制系统的原理、实现方法和软硬件构成等。该系统基于高性能八位微处理器Mega128而设计,集成了垂直度检测、井深测量、垂直度控制和操作指示等功能。     

多变量数字鲁棒最优控制器的设计及应用

针对线性多变量离散控制系统,给出一种新的鲁棒最优控制器的设计方法．该方法提出了多变量系统的行特征函数的设计新思想,实现等价系统的动态解耦,使闭环控制系统的传递函数矩阵为正规矩阵,达到鲁棒H∞最优稳定;进一步,通过对等价解耦控制系统应用l∞最优控制方法,又能使原闭环控制系统获得最优时域指标．通过在某纸机3种定量和水分控制系统中的在线应用,验证了数字控制器的最优性与鲁棒性．     

机器人计算力矩不确定性的神经网络补偿控制

提出一种由计算力矩控制器和神经网络补偿控制器相结合的控制方案,探讨了用神经网络补偿机器人计算力矩不确定性的方法,推导了网络权值的自适应调整律,并证明了系统的稳定性和误差的收敛性.该方案结构简单、鲁棒性强,且神经网络补偿器有较好的适应性,无须事先知道机器人动力学参数和结构的精确值.对机器人轨迹跟踪的仿真结果表明,所提方案具有很好的鲁棒性和抗干扰能力.     

Independent design of robust partially decentralized controllers

An independent design method for robust partially decentralized controllers is developed. In the proposed design method, the partially decentralized control system is first expanded to the nonsquare decentralized structure. Using the Internal Model Control parametrization, the independent design procedure for robust nonsquare decentralized controllers can then be applied directly to the expanded system. Two examples, including a nonlinear stirred mixing tank, are used to illustrate the developed design method and a comparison to a decentralized controller is made.     

Genetic design of real-time neural network controllers

The use of genetic algorithms to design neural networks for real-time control of flows in sewerage networks is discussed. In many control applications, standard supervised learning techniques (such as back-propagation) cannot be used through lack of training data. Reinforcement learning techniques, such as genetic algorithms, are a computationally-expensive but viable alternative if a simulator is available for the system in question. The paper briefly describes why genetic algorithms and neural networks were selected, then reports the results of a feasibility study. This demonstrates that the approach does indeed have merits. The implications of high computational cost are discussed, in terms of scaling up to significantly complex problems.     

Wiener-Hopf design of optimal decoupling one-degree-of-freedom controllers

This reasonably self-contained paper is directed to the design of a multivariable optimal one-degree-of-freedom feedback loop which incorporates a decoupling controller in the forward path. The criterion for optimality is a quadratic-cost functional that penalizes both tracking error and saturation. The controllers on which optimization is based are general enough to allow for non-unity feedback and rectangular plant transfer matrices possessing normal row rank. Nevertheless, for the sake of brevity and clarity, attention is focused mainly on the square case. Earlier treatments of the problem have employed multi-degree-of-freedom controllers. The solution we present for the one-degree-of-freedom case is considerably more difficult to obtain, especially when saturation is taken into account. Explicit formulas are derived for the set of all decoupling controllers yielding finite cost, as well as those that are optimal. It is shown that these controllers are strictly-proper under conditions usually prevailing in practice. Four fully worked examples serve to illustrate many important numerical aspects of the theory and all major proofs are transferred to the Appendix.     

Principles and design of model-based robot controllers

Model-based control algorithms for industrial manipulators require the on-line evaluation of robot dynamics and are particularly sensitive to modelling errors. The development of a unifying framework for the analysis and design of model-based robot control strategies is the theme of this paper. In this framework, the practical problems associated with real-time implementation are highlighted and methods to improve the robustness of the closed-loop system are suggested.