Remarks on tracking method of neural network weight change for adaptive type neural network feedforward feedback controller

A cost function is useful for a confirmation of neural network controller learning performance, but, this confirmation may not be correct for neural networks. Previous papers proposed a tracking method of neural network weight change and simulated it on the application of both learning and adaptive type neural network direct controllers. This paper applies the tracking method to an adaptive type neural network feedforward feedback controller and simulates it. The simulation results confirm that a track of the neural network weight change is separated into two trajectories. They also discuss the relationship between the feedback gain of the feedback controller and the parameter determining the neural network learning speed. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Feedback stabilization of a linear control system in Hilbert space with ana priori bounded control

This paper derives a feedback controlf(t), ‖f(t)‖_E≦r,r>0, which forces the infinite-dimensional control systemdu/dt=Au+Bf, u(0)=u _o ≠H to have the asymptotic behavioru(t)→0 ast→∞ inH. HereA is the infinitesimal generator of aC _o semigroup of contractionse ^At on a real Hilbert spaceH andB is a bounded linear operator mapping a Hilbert space of controlsE intoH. An application to the boundary feedback control of a vibrating beam is provided in detail and an application to the stabilization of the NASA Spacecraft Control Laboratory is sketched. This research was sponsored in part by the Air Force Office of Scientific Research, Air Force Systems Command, USAF Contract/Grants AFOSR 81-0172 and AFOSR 87-0315.     

基于信息融合估计的离散系统最优跟踪控制

针对期望输出和未来干扰无预见的离散线性系统最优跟踪问题,提出一种基于信息融合最优估计的控制方法.若将当前给定值和可测干扰值分别看作系统未来输出和干扰的预见值,则跟踪控制问题可转化为具有无限预见步数的预见控制问题,并将无限预见信息融合成一步等效预见信息,进而获得近似最优融合控制律.对线性直流电机系统和宏观经济系统的仿真结果均验证了该控制器在提高系统跟踪精度和抑制干扰等方面的有效性.     

Bounded output feedback tracking control of fully actuated Euler-Lagrange systems

In this short note we deal with the problem of trajectory tracking control of fully actuated Euler-Lagrange systems with unmeasurable velocities and bounded control inputs. In order to avoid the use of velocity measurements we introduce a nonlinear dynamic extension for the plant which renders the closed-loop system semi-globally asymptotically stable, hence, we prove that by increasing some of the dynamic extension parameters it is possible to enlarge the domain of attraction and to maintain the control inputs bounded.     

Approximate feedback linearization of discrete-time non-linear systems using virtual input direct design

The design of feedback-linearization and poles-placement controllers for discrete-time non-linear plants, using Input/Output/State measurements only, is typically addressed via indirect design. In this paper we propose the use of a new technique, based on a Virtual Input Direct Design (VID²) approach. The main feature of such a technique is to reduce the control design problem into a standard non-linear mapping approximation problem, without calling for the preliminary construction of an appropriate model of the plant. As compared with the existing methods, the new one requires less computational effort, while taking full advantage of the non-linear approximation software tools already available. In this paper, the new method is described, a simple theoretical analysis is given, and some numerical examples are presented.     

反馈控制理论在直流控制系统中的应用

使用直流控制系统实现转速或位置控制时,必须使用闭环反馈控制来实现。此文建立了这种系统的数学模型,分析了系统的绝对稳定性和相对稳定性,并提出了改善系统稳定性的方法和如何排除不稳定因素出现,为正确分析和设计直流控制系统提出了理论依据     

A set oriented approach to optimal feedback stabilization

We present a numerical construction of an optimal control based feedback law for the stabilization of discrete time nonlinear control systems. The feedback is based on a recently developed numerical solution method for optimal control problems using set oriented and graph theoretic algorithms. We show how this method can be used to construct approximately optimal and stabilizing feedback laws and present an a posteriori error estimation technique for the adaptive generation of the underlying set oriented space discretization.     

一种跟踪问题中的次优非线性预测控制算法

针对跟踪问题中无状态和输入约束的非线性预测控制最优解的求取问题,引入参考输入轨迹的概念,利用Ｓｔｉｒｌｉｎｇ插值公式,将非线性系统模型沿参考输入输出轨迹展开,取其一阶近似,处理成参数已知的线性模型．在此基础上,利用线性系统预测控制理论求解得到原系统的次优控制律．该方法不要求系统模型连续可导,且无需对线性化后的模型参数进行在线辨识,计算量小,易于实现．     

Digital tracking control of space robots using a transpose of the generalized Jacobian matrix

We have proposed discrete time-control methods using the transpose of the generalized Jacobian matrix (GJM) for free-floating space robots having manipulators. The control methods are robust for singular configurations of robots. Since the methods belong to a class of constant-value control, in this article we propose a digital trajectory tracking control method using the transpose of the GJM. Computer simulations show the effectiveness of the proposed method. This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006     

A modified direct adaptive robust motion trajectory tracking controller of a pneumatic system

In this study, we developed and tested a high-precision motion trajectory tracking controller of a pneumatic cylinder driven by four costless on/off solenoid valves rather than by a proportional directional control valve. The relationship between the pulse width modulation （PWM） of a signal＇s duty cycle and control law was determined experimentally, and a mathematical model of the whole system established. Owing to unknown disturbances and unmodeled dynamics, there are considerable uncertain nonlinearities and parametric uncertainties in this pneumatic system. A modified direct adaptive robust controller （DARC） was constructed to cope with these issues. The controller employs a gradient type adaptation law based on discontinuous projection mapping to guarantee that estimated unknown model parameters stay within a known bounded region, and uses a deterministic robust control strategy to weaken the effects of unmodeled dynamics, disturbances, and parameter estimation errors. By using discontinuous projection mapping, the parameter adaptation law and the robust control law can be synthesized separately. A recursive backstepping technology is applied to account for unmatched model uncertainties. Kalman filters were designed sepa- rately to estimate the motion states and the derivative of the intermediate control law in synthesizing the deterministic robust control law. Experimental results illustrate the effectiveness of the proposed controller.     

Global output feedback tracking control for a class of Lagrangian systems

The problem of global tracking control without velocity measurement of the so-called Euler–Lagrange systems has been paid a lot of attention for the past several years. In this note, a nice property of one-degree-of-freedom Euler–Lagrange systems is highlighted, which in particular allows us to obtain a new solution to the problem of tracking control for this class of systems. The solution is under the form of a linear-like observer-based controller which gives fairly good results, as illustrated in the simulation. The method can be generalized to any system having the same property.     

MPC for tracking with optimal closed-loop performance

In the recent paper [Limon, D., Alvarado, I., Alamo, T., & Camacho, E.F. (2008). MPC for tracking of piece-wise constant references for constrained linear systems. Automatica, 44, 2382-2387], a novel predictive control technique for tracking changing target operating points has been proposed. Asymptotic stability of any admissible equilibrium point is achieved by adding an artificial steady state and input as decision variables, specializing the terminal conditions and adding an offset cost function to the functional.In this paper, the closed-loop performance of this controller is studied and it is demonstrated that the offset cost function plays an important role in the performance of the model predictive control (MPC) for tracking. Firstly, the controller formulation has been enhanced by considering a convex, positive definite and subdifferential function as the offset cost function. Then it is demonstrated that this formulation ensures convergence to an equilibrium point which minimizes the offset cost function. Thus, in case of target operation points which are not reachable steady states or inputs for the constrained system, the proposed control law steers the system to an admissible steady state (different to the target) which is optimal with relation to the offset cost function. Therefore, the offset cost function plays the role of a steady-state target optimizer which is built into the controller. On the other hand, optimal performance of the MPC for tracking is studied and it is demonstrated that under some conditions on both the offset and the terminal cost functions optimal closed-loop performance is locally achieved.     

A distributed multiuser virtual space system

Today, in an era of increased Internet use, tools designed to help users communicate across the network have begun to proliferate. Interest in virtual 3D spaces is growing too. We outline a technique for directly transferring the necessary parameter information to express virtual human emotions across a network. We also discuss the methods required for constructing a system that can facilitate this kind of direct transfer using distributed object technology. We offer a method for integrating the services of our system and a constructed database of movements. Finally, we propose various quality-of-service (QoS) techniques for effective motion information transfer in our constructed system.     

A rigorous solution of the infinite time interval LQ problem with constant state tracking

A linear quadratic constant state tracking problem is considered over an infinite time horizon. It is shown that the solution cannot be obtained as a limit from a finite time horizon problem, as in general the limiting problem is ill-posed. To obtain a rigorous solution, the problem is split in two natural well-posed subproblems. One optimal control problem addresses the transient and the other optimal control problem concerns the steady state behavior. It is shown that the transient problem and the steady state problem are solved by the same control law.     

Composite nonlinear control with state and measurement feedback for general multivariable systems with input saturation

In this paper, we present a design procedure of composite nonlinear feedback control for general multivariable systems with actuator saturation. We consider both the state feedback case and the measurement feedback case without imposing any restrictive assumption on the given systems. The composite nonlinear feedback control consists of a linear feedback law and a nonlinear feedback law without any switching element. The linear feedback part is designed to yield a closed-loop system with faster rise time, while at the same time not exceeding the actuator limits for the desired command input levels. The nonlinear feedback law is used to reduce overshoot and undershoot caused by the linear part. As such, a highly desired tracking performance with faster settling time and smaller overshoot can be obtained. The result is illustrated by a numerical example, which shows that the proposed design method yields a very satisfactory performance.     

A heuristic feedback control theory based interactive expert system – RSCD

In this paper, we focus on the difficulties of resource recycling problems relating to the used Iron and/or Aluminum cans. Based on the feedback control theory and combining with micro-chip processor, sensors, phonic chip, oil-compressor and mechanism technology, we design an interactive resource recycling Expert System –“Recycling Squeezed Cans Device” (RSCD) and the proposed interactive RSCD is an automaton device and achieves the following attractive functions: (1) Automatic guiding and detecting system, (2) Security protection system, (3) Automatic classification system, (4) Automatic squeezing system, (5) Automatic distributed collection system, (6) Automatic refund system. We design a heuristic feedback control algorithm imbedded in processor chip and the proposed interactive RSCD has the following special features: the Automatic guiding and detecting system using phonic chip associated with sensors and panel light indicator can easily lead users to operate the RSCD, the Security protection system using sensors associated with electromagnetic switches and safety mechanism designs can protect users harmless and the RSCD as well, the Automatic classification system using sensors associated with mechanic device and the design relating to rotating stepping motor can precisely discriminate whether the recycling used cans material belongs to metal or nonmetal type, and moreover, classify Iron or Aluminum type, the Automatic squeezing system using oil-compressor associated with sensors, and the design as to the compressing device can rapidly squeeze the recycling used cans into under about 1/5 of its original volume, the Automatic distributed collection system using sensors associated with stepping motor, micro-switches, and the design concerning the collection device can precisely distributed collect the recycling compressed cans into two different cans collection tanks, and the Automatic refund system using micro-switches associated with counter, and the design as to the rotating withdrawing device quickly give back the desired refunds. We install the proposed interactive RSCD in several different areas in public and make numerous simulations, the test results show that the proposed interactive RSCD is efficient for handling the resource recycling problems as to the recycling used Iron and/or Aluminum cans.     

Application of type-2 fuzzy logic system for load frequency control using feedback error learning approaches

In this paper, the type-2 fuzzy logic system (T2FLS) controller using the feedback error learning (FEL) strategy has been proposed for load frequency control (LFC) in the restructure power system. The original FEL strategy consists of an intelligent feedforward controller (INFC) (i.e. artificial neural network (ANN)) and the conventional feedback controller (CFC). The CFC acting as a general feedback controller to guarantee the stability of the system plays a crucial role in the transient state. The INFC is adopted in forward path to take over the control problem in the steady state. In this work, to improve the performance of the FEL strategy, the T2FLS is adopted instead of ANN in the INFC part due to its ability to model uncertainties, which may exist in the rules and measured data of sensors more effectively. The proposed FEL controller has been compared with a type-1 fuzzy logic system (T1FLS) – based FEL controller and the proportional, integral and derivative (PID) controller to highlight the effectiveness of the proposed method.     

A new approach to nonlinear optimal feedback law

For a fixed-time free endpoint optimal control problem it is shown that the optimal feedback control satisfies a system of ordinary differential equations. They are obtained using an elimination procedure of the adjoint vector which appears linearly in a set of differential equations. These equations, involving Lie brackets of vector fields, are derived from the Maximum Principle. An application of this approach to robotics is given.