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.     

Energy-based balance control approach to the ball and beam system

This article investigates the set-point balance control problem of the ball and beam system acting on the ball which is an underactuated system. The control law is designed, based on the total mechanical energy and the passivity properties of the system. According to the desired set-point, the zero equilibrium point and non-zero equilibrium points are studied respectively. For the zero case, it is proved that a single PD feedback controller is sufficient to bring the state to zero from any initial condition, on condition that the control parameters satisfy an inequality. For the non-zero case, the control problem is much more complicated. Unlike the previous energy-based control laws, a new form of Lyapunov function candidate is constructed. A complete analysis of the convergence of the energy and the dynamics is given, and the characteristics of the closed-loop system with the proposed feedback control law are illustrated. Moreover, it is proved that with the parameter choice rules proposed in this article, the ball and beam system will eventually converge exactly to the desired non-zero equilibrium point. Furthermore, since the length of the beam is not unlimited, the trajectory of the ball should be restricted within a limited range. The balance control laws are modified to avoid the ball running beyond the joint range limitation for the zero case and the non-zero case respectively. Simulation results show that the control laws proposed in this article are effective for the set-point balance control problem of the ball and beam system.     

Model reference adaptive control of discrete‐time piecewise linear systems

This article presents a switched model reference adaptive controller for discrete‐time piecewise linear systems. In the spirit of the work by Landau in the late seventies, proof of asymptotic stability of the closed‐loop error system is obtained, recasting its dynamics as a feedback system and showing the feedforward and the feedback paths are both passive. The challenge is that both paths can be piecewise linear. Numerical results show excellent performance of the proposed controller even in the face of sudden variations of the plant parameters. Copyright © 2012 John Wiley & Sons, Ltd.     

Robust stabilization of singularly perturbed nonlinear systems

Consider a singularly perturbed nonlinear system endowed with a control input and suppose a static nonlinear feedback law is designed. We show that the operations ‘compute the reduced order system’ (i.e., let the singular perturbation parameter μ = 0) and ‘close the feedback loop’ commute, i.e. the closed loop reduced-order system is unambiguously determined. We then show that, if the reduced order system associated with the original system is stabilizable or has uncertainties matched with the input (a condition frequently used in the design of robust controllers), then the closed loop reduced-order system enjoys the same property. As shown by an example, this result can be used to simplify the structure of a composite controller.     

A family of virtual contraction based controllers for tracking of flexible‐joints port‐Hamiltonian robots: Theory and experiments

In this work, we present a constructive method to design a family of virtual contraction based controllers that solve the standard trajectory tracking problem of flexible‐joint robots in the port‐Hamiltonian framework. The proposed design method, called virtual contraction based control, combines the concepts of virtual control systems and contraction analysis. It is shown that under potential energy matching conditions, the closed‐loop virtual system is contractive and exponential convergence to a predefined trajectory is guaranteed. Moreover, the closed‐loop virtual system exhibits properties such as structure preservation, differential passivity, and the existence of (incrementally) passive maps. The method is later applied to a planar RR robot, and two nonlinear tracking control schemes in the developed controllers family are designed using different contraction analysis approaches. Experiments confirm the theoretical results for each controller.     

Robust controller design for infinite‐dimensional exosystems

In this paper, we consider robust output regulation of distributed parameter systems with infinite‐dimensional exosystems capable of generating polynomially growing signals. We design an observer‐based error feedback controller solving the control problem. The controller is chosen in such a way that it incorporates an internal model of the infinite‐dimensional exosystem. The remaining parameters of the controller are chosen to stabilize the closed‐loop system strongly. We also analyze the classes of signals generated by the exosystem. In particular, we explore the connection between the smoothness properties of the reference and disturbance signals and the strictness of the conditions required for the existence of a controller solving the robust output regulation problem. Copyright © 2012 John Wiley & Sons, Ltd.     

Some investigations on hybrid fuzzy IPD controllers for proportional and derivative kick suppression

Proportional and derivative kick i.e., a large change in control action of a proportional plus integral plus derivative (PID) controller due to a sudden change in reference set-point is generally undesired in process industry. Therefore, the structure of conventional parallel PID controller is modified to integral minus proportional derivative (I-PD) controller. In this paper, three hybrid fuzzy IPD controllers such as a fuzzy I-fuzzy PD (FI-FPD) controller and its hybrid combinations with its conventional counterpart such as fuzzy I-PD (FI-PD) and I-fuzzy PD (I-FPD) are presented in view of above industrial problem. These controllers are based upon the counterpart conventional I-PD controller and contains analytical formulae. Computer simulations are carried out to evaluate the performance of hybrid fuzzy controllers along with conventional I-PD and PID controllers for set-point tracking and disturbance rejection for an induction motor in closed loop using LabVIEW? environment. The gains of conventional and hybrid fuzzy controllers are tuned using genetic algorithm (GA) for minimum overshoot and settling time. It has been observed that hybrid fuzzy controllers along with the conventional I-PD controller significantly remove the kick from the control action in reference set-point tracking. However, in disturbance rejection, I-PD and FI-PD controllers fail to eliminate the kick from the control signal. In contrast, FI-FPD and I-FPD controllers considerably reduced spikes from the control action in disturbance rejection. Among the conventional and hybrid fuzzy IPD controllers, FI-FPD demonstrates much better set-point tracking and disturbance rejection response with spike free control action.     

无线网络环境下数据驱动混合选别浓密过程双率控制方法

无线网络环境下赤铁矿混合选别浓密过程控制问题是以底流矿浆泵频率为内环输入,以底流矿浆流量为内环输出外环输入,以底流矿浆浓度为外环输出的非线性串级工业过程控制问题.其外环反馈回路存在丢包,且模型参数难以辨识,故本文利用工业运行过程的在线数据,设计不依赖模型参数的跟踪控制器.首先,利用浓密过程运行在工作点附近的特点进行线性化,对流量过程设计Q-学习控制器,保证流量过程能够跟踪给定的流量设定值;然后采用提升技术,得到统一时间尺度的以底流矿浆流量设定值为输入,以底流矿浆浓度为输出的被控对象;最后,考虑到在无线网络环境下浓度过程存在反馈丢包,当前的状态可能无法获得,故采用史密斯预估器的思想,利用历史的数据估计系统当前的状态,设计丢包Q-学习设定值控制器为流量过程提供最优设定值.通过仿真实验验证所提算法的有效性.     

Learning from Workaround Practices: the Challenge of Enterprise System Implementations in Multinational Corporations

Based on a four‐year longitudinal case study of a French multinational corporation (MNC) this research explains how a global enterprise system, initially designed to provide greater control by headquarters across its MNC sites, led to the emergence of unexpected practices – known as workarounds – in its Chinese subsidiaries. Drawing on concepts from activity theory our findings provide greater theoretical understanding of workarounds in three ways. First, users are involved in collectively constructing and implementing workaround practices rather than simply being passive users or reduced to the dichotomous framing of ‘accepting’ or ‘rejecting’ an information system. Workarounds are not simple individual user improvizations but are collectively developed and become unofficial local rules. Second, workarounds are part of learning which goes beyond the view of workarounds as deviant and non‐compliant behavior. Third, learning activities are not restricted to users and their practices. Rather, as we demonstrate learning and evolution take place between the users, managers, processes and the system; that is, workarounds are not only a critical part of ‘getting work done’ but also an integral part of the institutionalization of an enterprise system.     

Energy shaping control of an inverted flexible pendulum fixed to a cart

Control of compliant mechanical systems is increasingly being researched for several applications including flexible link robots and ultra-precision positioning systems. The control problem in these systems is challenging, especially with gravity coupling and large deformations, because of inherent underactuation and the combination of lumped and distributed parameters of a nonlinear system. In this paper we consider an ultra-flexible inverted pendulum on a cart and propose a new nonlinear energy shaping controller to keep the pendulum at the upward position with the cart stopped at a desired location. The design is based on a model, obtained via the constrained Lagrange formulation, which previously has been validated experimentally. The controller design consists of a partial feedback linearization step followed by a standard PID controller acting on two passive outputs. Boundedness of all signals and (local) asymptotic stability of the desired equilibrium is theoretically established. Simulations and experimental evidence assess the performance of the proposed controller.     

Guaranteed cost control of distributed parameter networked control systems with time‐varying delay

Distributed parameter networked control systems mean distributed parameter systems are controlled through a network, where the control loops are closed. In this paper, the problem of guaranteed cost and state feedback controller design is investigated for a class of distributed parameter networked control systems. With the network factors, such as transmission delays, data packet dropouts considered, the distributed parameter networked control system is modeled as a linear closed‐loop system with time‐varying delay and uncertain parameters. By selecting an appropriate Lyapunov‐Krasovskii function and using linear matrix inequality (LMI) approach, the controller is designed to render the system stable and it can keep the cost function less than a certain upper value. In addition, numerical simulation is included to demonstrate the theoretical results.     

Energy-based control of a distributed solar collector field

Model-based control of the outlet temperature of a distributed solar collector field is studied. An energy-based controller is derived using internal energy as a controlled variable. The controller relies on a distributed parameter nonlinear plant model and includes feedforward from the solar irradiation and inlet temperature. Convergence of the closed loop is proved, and the method is experimentally verified to perform well on a pilot-scale solar power plant.     

Extremum seeking loops with quadratic functions: Estimation and control

Extremum-seeking (also peak-seeking ) controllers are designed to operate at an a priori unknown set-point that extremizes the value of a performance function. Traditional approaches to the problem assume a time-scale separation between the gradient computation and function minimization and the system dynamics. The work here, in contrast, assumes that the performance function can be approximated by a quadratic function with a finite number of parameters. These parameters are estimated on-line and the extremum seeking controller operates based on these estimated values. A significant advantage of a quadratic function is that it allows the peak-seeking control loop to be reduced to a linear system. For such a loop, the wealth of linear system analysis and synthesis tools can be employed. First, the control loop is analysed assuming that the parameters in the function are known (full information case) and then when the parameters are estimated on line (the partial information case).     

A direct synthesis tuning method of unstable first-order-plus-time-delay processes

A direct synthesis tuning method is proposed for the PI controller settings of unstable first-order-plus-time-delay processes. Unlike hitherto-known PI setting rules which often result in overshoots in time response or require the modification of the feedback control structure, this method ensures the overdamped response as desired while retaining the conventional PI control structure. This enhanced performance is possible by introducing a first-order set-point filter and applying simple rules for setting the values of the controller parameters without having any tuning parameters. The comparison with both conventional PI controllers and two-stage IMC method reveals that the proposed method produces not only smooth overdamped closed-loop response for set-point changes, but also fast regulatory control response for load changes. These responses are also shown to be quite robust against the uncertainties of the parameters as well as against the noise in the signal. The stability conditions for the processes having a large time delay or different ratios of time delay/time constant have been investigated as well. ©     

步进梁加热炉神经网络模型预测控制

针对步进梁式连续加热炉燃烧过程控制的温度分布非线性和滞后性,提出了一种基于非线性优化技术的神经网络模型预测控制算法。神经网络具有强大的自学习和非线性映射能力,把神经网络预测模型和非线性优化器整合为一个温度控制器,通过神经网络预测模型描述温度控制对象的动态行为,根据加热炉当前温度和出钢温度预测未来时刻的温度输出值,实现加热炉温度控制。实验结果表明,通过对网络模型进行大样本训练和对模型预测控制参数的优化,加热炉温度控制系统能快速达到控制要求,具有良好的抗干扰能力和温度跟随性能。     

Adaptive output feedback control of uncertain nonlinear systems based on dynamic surface control technique

An adaptive output feedback control approach is studied for a class of uncertain nonlinear systems in the parametric output feedback form. Unlike the previous works on the adaptive output feedback control, the problem of ‘explosion of complexity’ of the controller in the conventional backstepping design is overcome in this paper by introducing the dynamic surface control (DSC) technique. In the previous schemes for the DSC technique, the time derivative for the virtual controllers is assumed to be bounded. In this paper, this assumption is removed. It can be proven that the resulting closed‐loop system is stable in the sense that all the signals are semi‐global uniformly ultimately bounded and the system output tracks the reference signal to a bounded compact set. A simulation example is given to verify the effectiveness of the proposed approach. Copyright © 2011 John Wiley & Sons, Ltd.     

Some investigations on fuzzy P + fuzzy I + fuzzy D controller for non-stationary process

The paper addresses the adaptive behaviour of parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller. The parallel FP+FI+FD controller is actually a non-linear adaptive controller whose gain changes continuously with output of the process under control. Two non-stationary processes, whose characteristics change with time, are considered for simulation study. Simulation is performed using software LabVIEW TM . The set-point tracking response of parallel FP+FI+FD is compared with conventional parallel proportional plus integral plus derivative (PID) controller, tuned with the Ziegler-Nichols (Z-N) tuning technique. Simulation results show that conventional PID controller fails to track the set-point and becomes unstable as the process changes its characteristic with time. But the parallel FP+FI+FD controller shows considerably much better set-point tracking response and does not deviate from steady state. Also, a huge spike is observed in the output of PID controller as the reference set-point and process parameters are changed, while the FP+FI+FD controller gives spike free control signal.     

网络环境下不敏感系统的分布式区域预测控制方法

针对二分图网络结构下的不敏感系统的可控性比较差的问题,本文提出了带有区域控制的分布式模型预测控制方法.该方法首先利用分支定界法对分布式控制系统结构进行最优设计;然后,结合区域控制提高控制系统的动态性能指标;最后,依据回路之间的关联性的强弱选择每个回路的控制方式(精确控制或区域控制).仿真结果显示带有区域控制的分布式预测控制系统的调节时间比没有带区域控制的分布式控制系统明显缩短;同时,通过对回路控制方式的选择增加了精确控制的智能体数量.仿真结果证明了利用分布式区域预测控制方法可以提高系统的容错性,通过对系统的可控性和关联性进行分析,可以在精确控制和区域控制之间寻找到最优组合,从而达到快速精确的控制效果.     

Cylinder pressure based combustion phase optimization and control in spark-ignited engines

Efficiency and emissions of spark-ignited engines are significantly affected by combustion phase which can usually be indicated by crank angle of 50\% mass burnt (CA50). Managing combustion phase at the optimal value at which the maximal efficiency can be achieved is a challenging issue due to the cyclic variations of combustion process. This paper addresses this issue in two loops: CA50 set-point optimization (outer loop) and set-point tracking (inner loop) by controlling spark advance (SA). Extremum seeking approach maximizing thermal efficiency is employed in the CA50 set-point optimization. A proportional-integral (PI) controller is adopted to make the moving average value of CA50 tracking the optimal CA50 set-point determined in the outer loop. Moreover, in order to obtain fast responses at steady and transient operations, feed-forward maps are designed for extremum seeking controller and PI controller, respectively. Finally, experimental validations are conducted on a six-cylinder gasoline at steady and transient operations to show the effectiveness of proposed control scheme.     

Closed loop parameter identifiability and adaptive control of a linear stochastic system

We show that if the parameters of a linear stochastic control system are identifiable using a persistently existing input then the same systems remains parameter identifiable if the system operates under closed loop in a certain way. We assume that the controller itself depends on the test value of the system parameters, and as usual the control signal is dithered. The estimation problem is formulated as the problem of minimizing an appropriate asymptotic cost function. It is shown that a suitable modification of the gradient of the cost function converts our problem into another problem for which Ljung's scheme can be applied. Thus the theorem provides a general method for the solution of the local adaptive control problem.