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Model-Following Designs Using Direct State Derivative Measurement Feedback in Novel Reciprocal State Space Form

The main purpose of this paper is to construct an autopilot system for unmanned railcars based on computer vision technology in a fixed luminous environment. Four graphic predefined signs of different colors and shapes serve as motion commands of acceleration, deceleration, reverse and stop for the motion control system of railcars based on image recognition. The predefined signs&rsquo, strong classifiers were trained based on Haar-like feature training and AdaBoosting from Open Source Computer Vision Library (OpenCV). Comprehensive system integrations such as hardware, device drives, protocols, an application program in Python and man machine interface have been properly done. The objectives of this research include: (1) Verifying the feasibility of graphic predefined signs serving as commands of a motion control system of railcars with computer vision through experiments, (2) Providing reliable solutions for motion control of unmanned railcars, based on image recognition at affordable cost. The experiment results successfully verify the proposed methodology and integrated system. In the main program, every predefined sign must be detected at least three times in consecutive images within 0.2 s before the system confirms the detection. This digital filter like feature can filter out false detections and make the correct rate of detections close to 100%. After detecting a predefined sign, it was observed that the system could generate new motion commands to drive the railcars within 0.3 s. Therefore, both real time performance and the precision of the system are good. Since the sensing and control devices of the proposed system consist of computer, camera and predefined signs only, both the implementation and maintenance costs are very low. In addition, the proposed system is immune to electromagnetic interference, so it is ideal to merge into popular radio Communication Based Train Control (CBTC) systems in railways to improve the safety of operations.

Parameter identification of an induction machine is of great importance in numerous industrial applications. This paper used time-varied signals of voltage, current, and rotor speed to compute the equivalent circuit parameters, moment of inertia, and friction coefficient of an induction machine. The theoretical impedance-slip rate characteristic curve of the induction machine can be expressed as a polynomial fraction, so that a proper polynomial fraction can obtain complete and accurate parameters. A time-varied impedance can be found by the time-varied voltage and current. From the variation of impedance to the rotor speed, the parameters of the equivalent circuit can be found. According to the equivalent circuit and rotor speed, the torque can be determined via dynamic simulation. On the basis of torque and rotor speed with time, the moment of inertia and friction coefficient of the motor can then be obtained. Advantages of this method include the ability to obtain the optimal value via only one calculation, without the requirement of any initial value, and the avoidance of any local optimal solution. In this paper, the analysis of a practical induction machine was used as an example to illustrate the practical application.

There are three problems that people usually have to face when they carry out optimal control designs in state space system form or descriptor system form. They are no state derivative considered in cost functional,no well-developedstate derivative feedback control algorithms and some systems cannot easily design optimal control in these two system forms. To overcome the problems, a novel state derivative space system (SDS) form is introduced. In this novel form, novel differential Lagrange multiplier should be used to adjoinSDS system constraint to the cost functional that is function of state derivative only to straightforwardly carry out optimal control design. Based on the optimal control design in SDS form, control in SDS form is developed. It showed that for descriptor systems with impulse modes, if they can be expressed in SDS form, one can easily carry outcontrol design by solving only an algebraic Riccati equation. The purpose of this research is to develop novel and simple control algorithms in SDS form so that wider ranges of problems can be solved without much of mathematics overhead.

H-infinity norm is the maximum system gain and is related to the system output response. Finding the minimum of H-infinity norm is essential in control design to avoid overshoot or saturation in implementation. The fundamental of finding the minimum of H-infinity norm is based on optimal control. There are three problems that people usually have to face when they carry out optimal control designs in state space system form or descriptor system form. They are no state derivative considered in cost functional, no well-developed state derivative feedback control algorithms and some systems cannot easily design optimal control in these two system forms. To overcome the problems, a novel state derivative space system (SDS) form is introduced. In this novel form, novel differential Lagrange multiplier should be used to adjoin SDS system constraint to the cost functional that is function of state derivative only to straightforwardly carry out optimal control design. Based on the optimal control design in SDS form, the process of finding the minimum H-infinity norm in SDS form is successfully developed and verified in this paper. That process in SDS form is actually as straightforward as its counterpart in state space form. Consequently, wider ranges of problems can be solved without much of mathematics overhead.

This chapter introduces a novel reciprocal state space (RSS) system form. The concepts and the need of RSS form are comprehensively reviewed and explained. It shows that in RSS form, control design using state derivative related feedback is straightforward. Sliding mode control (SMC) is a nonlinear control design method and a highly active area of research. Finite-time convergence due to discontinuous control law, low sensitivity to plant parameter uncertainty and/or external perturbation, and greatly reduced-order modeling of plant dynamics are the main advantages of SMC. In the past, the majority of available SMC algorithms and the corresponding switching conditions involved only state related variables. In this chapter, the advantages of both RSS and SMC are combined to develop sliding mode control in RSS form so that state derivate related feedback can be systematically applied in SMC to handle wider range of control problems. To provide the theoretical foundation, stability analysis in RSS form is first reviewed. Next, novel switching function and approaching condition based on the derivative of sliding surface are proposed to carry out SMC design approach in RSS form with considerations of system uncertainty and disturbance. In addition, algorithm of finding upper bound of system uncertainty is developed for robustness analysis. To verify the proposed design algorithms, numerical examples are provided. Finally, conclusions are drawn.

To reduce the manpower and response time for surveillance systems at low cost, in this paper, an ARM-based embedded system dedicated for unattended realtime moving target detection is constructed. The comprehensive procedures in building up an embedded system such as setup environment for cross-compilation, migration of Bootloader, migration of Linux-2.6 kernel, fabrication and migration of root document system and setup of peripheral driving devices have been presented. The algorithm of image background subtraction for moving target detection and tracking technology has been presented. In this embedded system, for two consecutive 640×480 image frames captured by camera, if the difference of 8-bit gray level value of a pixel at the same position is greater than 32, that pixel is marked as a “moving pixel”. When there are more than 500 moving pixels in two consecutive image frames, the camera is triggered to take pictures because the system assumes that a moving “invader” appears. Consequently, the system will transfer the taken invader's pictures to “The Cloud” through WiFi to prevent the pictures being destroyed by the invader. The constructed embedded system can be used in a security system and other applications with proper modifications.

The purpose of this paper is to design an intelligent wheel robot, which can recognize and follow a predefined forward sign while automatically bypassing any encountered obstacle. By distributing those forward signs, the path of the robot is determined. With this concept, an image based autopilot system with immunity against electromagnetic interference is constructed. Harr-like feature training algorithm in OpenCV has been applied so that the robot can quick detect the forward sign. The rotation of the robot for automatic target detecting is achieved by fuzzy control. The experimental results showed that the robot could successfully detect forward sign and response properly. Consequently, the proposed design approach is proven to be workable. Simply redistributing the recognizable signs by the robot, a new path for robot is constructed. Therefore, it has great flexibility for applications. The detail will be presented in part II.

The purpose of this paper is to design an intelligent wheel robot, which can recognize and follow a predefined forward sign while automatically bypassing any encountered obstacle. By distributing those forward signs, the path of the robot is determined. With this concept, an image based autopilot system with immunity against electromagnetic interference is constructed. Harr-like feature training algorithm in OpenCV has been applied so that the robot can quick detect the forward sign. The rotation of the robot for automatic target detecting is achieved by fuzzy control. The experimental results showed that the robot could successfully detect forward sign and response properly. Consequently, the proposed design approach is proven to be workable. Simply redistributing the recognizable signs by the robot, a new path for robot is constructed. Therefore, it has great flexibility for applications.

This paper addresses the need of the novel reciprocal state space (RSS) framework to be the supplement of standard state space system in control designs. A model following design based on variable structure control design approach utilizing direct state derivative measurement for an RSS system with nonlinear dead-zone input is proposed. Simulations for both nonlinear dead-zone input and nonlinear sector input are carried out for an unstable RSS system to successfully verify the proposed algorithm. It shows that the design procedure is straightforward for systems with direct state derivative measurement if we express the system in RSS framework.

There are two major problems that people usually have to face when they carry out optimal control designs in state space system or descriptor system. One is no state derivative considered in cost functional, the other is that some systems cannot easily design optimal control in either state space system or generalized system frameworks. To overcome the problems, a novel state derivative space system (SDS system) framework is proposed. In this novel framework, novel differential Lagrange multiplier should be used to adjoin SDS system constraint to the cost functional that is function of state derivative to straightforwardly carry out optimal control design. It showed that some singular systems with impulse mode can easily carry out optimal control in SDS system. The purpose of this research is to develop novel and simple optimal control algorithms in SDS system so that wider ranges of problems can be solved without much of mathematics overhead.

This paper proposes an anisotropic probabilistic neural network image interpolation (APNNI2). The method used anisotropic Gaussian kernel to improve probabilistic neural network image interpolation (PNNI2) which caused blurring edge. The method is better for sharpness enhancement at edge region. We interpolate slanted-edge image to observe blurring and blocking effect. Finally, we report the performance of these newly proposed methods in other image interpolation method.

This paper investigates the novel variable structure control (VSC) designs with state derivative feedback in nontraditional reciprocal state space (RSS) framework. Novel switching functions based on the derivative of sliding surface satisfying the approaching condition of sliding mode are introduced. In addition, algorithm of finding upper bound of system uncertainty is developed for robustness analysis. VSC design is carried out for unstable systems with system uncertainty and matched external disturbance. Simulation results successfully verify the validities of the proposed algorithms.

This paper introduces novel tracking control algorithms for step command utilizing state derivative output feedback and feedforward in reciprocal state space framework. Linear quadratic regulator (LQR) design of deviation system is used to find state derivative output feedback gain and two methods are developed to find feedforward gain to construct tracking controller in reciprocal state space framework. For the systems with state derivative sensors, applying the proposed algorithms, tracking control designs become straightforward while unnecessary integrations can be avoid to reduce implementation cost. Simulations of a nano-positioner with micro-accelerometer as sensor have been successfully carried out to verify the proposed algorithms. From the simulation results, we find that although the design is based on step response shaping, it also gives good time responses for time varying reference commands such as sine wave and square wave.

The paper describes the criteria of stability, controllability and observability for the systems, which can be expressed in the 'reciprocal state space framework'. Several important reasons are presented to justify the need for the 'reciprocal state space framework' and advantages of the 'reciprocal state space framework' are explained and contrasted with those of the typical standard state space framework. This concept of the direct state derivative feedback control design in the 'reciprocal state space framework' is new and attractive, especially for descriptor systems, singular systems or semi-state systems.

Introduces a design approach based on a new framework called 'reciprocal state space' framework in which the state derivative can be sensed and fed back directly. By using accelerometers and integrators, information of acceleration, velocity and displacement can be obtained and fedback. The proposed methodology using the reciprocal state space framework is useful in structural control because accelerometers are widely used in structural control systems. The proposed methodology is is illustrated by considering the vibration control problem for an aircraft wing, modeled by the finite element method.

In this paper, a design approach for controlling a composite plate structure subject to aeroelastic loading using piezoelectric actuators and sensors is presented. The nature of the sensing variables is exploited and accommodated in the control design algorithm. The controller is a feedback controller that uses various measurements related to motion variables such as accelerations, velocities and displacements. Proposed controller designs in this paper are based on equivalent first order state-space baseline design gains that use existing control system design software. The proposed method provides different norms for controller gains, thereby allowing more flexibility in gain magnitudes and selection of sensors and still meet the time response specifications.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

In this paper, a design approach for controlling a composite plate structure subject to aeroelastic loading using piezoelectric actuators and sensors is presented. The nature of the sensing variables is exploited and accommodated in the control design algorithm. The controller is a state estimate based feedback using various measurements related to motion variables such as accelerations, velocities and displacements. Controller designs are based on equivalent first-order state-space baseline design gains that use existing algorithms. The proposed method provides different norms for estimator and controller gains, thereby allowing more flexibility in gain magnitudes and selection of sensors.