Type-III closed loop control systems-Digital PID controller design

The problem of tuning digital PID controllers for type-III control loops is investigated in this work. Type-III control loops are capable of achieving perfect tracking of step, ramp and parabolic reference signals with zero steady state position, velocity and acceleration error. The proposed PID control law involves any dominant time constants of the process itself, and any parasitic dynamics introduced by both the process and the controller, i.e. time delays within the closed control system. The development of the proposed control law takes place in the frequency domain and basis of the theory is the principle of the Magnitude Optimum criterion. The final control law consists of closed form expressions which involve also the controller's sampling time T_s. The potential of the proposed theory is justified for the control of several benchmark process models throughout simulation examples. The affect of the choice of the controller's sampling time is investigated further to the step and frequency response of the control loop both for the output of the control loop and the controller's command signal.     

An approach to adaptive control of robotic manipulators

The control synthesis for the robotic systems in which parameters are partially unknown is considered. We propose synthesis of robust, non-adaptive, decentralized control which has to stabilize robots for all allowable variations of the parameters. If the robust non-adaptive control cannot withstand all expected variations of parameters, we propose synthesis of indirect adaptive control, i.e. the estimation of the robot parameters is performed first and then used for adjusting the decentralized control gains. The non-adaptive and adaptive control syntheses are illustrated by simulation of an industrial robot with unknown payload mass.     

The optimum design of robotic manipulators using dexterity indices

This paper presents new dexterity indices that can be applied to planar and spatial manipulators. These indices are based on the condition number of the Jacobian matrix of the manipulators which is known to be a measure of their kinematic accuracy. Dexterity indices based on that same criterion have been presented elsewhere. However, due to the formulation of the kinematic equations, the existing indices are affected by a scaling of the manipulator when both the position and the orientation of the end effector are included in the kinematic equations. A new formulation of these equations is proposed here to avoid this problem of dimensional dependence. Two dexterity indices are presented for planar manipulators: the first one is based on a redundant formulation of the velocity equations whereas the second one is based on the mininum number of parameters. The corresponding indices are also derived for spatial manipulators. Finally, an example is included to illustrate the use of these indices in the context of design and optimization of manipulators.     

A design approach to adaptive model-following control of robotic manipulators

In this paper, the robot dynamics are represented by a nonlinear state-space model containing a disturbance term due to gravitational loading. Using a suitable linear time-invariant reference model, an adaptive model-following control problem is formulated which satisfies the matching conditions. The control input is designed to have two components: a nonadaptive linear component to do the task of model-following and a nonlinear unit-vector component based on hyperstability theory to do the adaptive task. An additional integral feedback term is further superimposed and then the overall asymptotic hyperstability is established. The simulation results on the first three joints of PUMA 560 robot manipulator indicate the potential of our design approach.Based on research supported by Kuwait University Research Administration under Grant No. EE 049.     

Model based approach to closed loop control of 1-D engine simulation models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts to assess performance and therefore determine suitable hardware. The transient response is a key driver in the selection process which in most cases requires closed loop control of the model to ensure operation within prescribed physical limits and tracking of reference signals. Since the controller effects the system performance a systematic procedure which achieves close-to-optimal performance is desired, if the full potential of a given hardware configuration is to be properly assessed. For this purpose a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). The system is also tested for operation at high altitude conditions to demonstrate the ability of the controller to respect specified physical constraints. As an example this study is focused on the transient response of a light-duty automotive Diesel engine. For the cases examined the proposed controller design gives a more systematic procedure than other ad hoc approaches that require considerable tuning effort.     

Nonlinear adaptive control of robotic manipulators - hyperstability approach

A nonlinear model reference adaptive controller based on hyperstability approach, is presented for the control of robot manipulators. Use of hyperstability approach simplifies the stability proof of the adaptive system. The unknown parameters of the system, as well as its variable payload, are estimated on line and are adaptive to their actual values; tending to reduce the system error. In addition, any sudden change in the system parameters or payload is detected by the proposed intelligent controller. Robot path tracking, with unknown parameter values and variable payload, is simulated to show the effectiveness of the proposed adaptive control algorithm. Both system output error and parameter estimation error vanish under the proposed parameter adaptation algorithm.     

Computational intelligence approach to PID controller design using the universal model

Despite the popularity of PID (Proportional-Integral-Derivative) controllers, their tuning aspect continues to present challenges for researches and plant operators. Various control design methodologies have been proposed in the literature, such as auto-tuning, self-tuning, and pattern recognition. The main drawback of these methodologies in the industrial environment is the number of tuning parameters to be selected. In this paper, the design of a PID controller, based on the universal model of the plant, is derived, in which there is only one parameter to be tuned. This is an attractive feature from the viewpoint of plant operators. Fuzzy and neural approaches - bio-inspired methods in the field of computational intelligence - are used to design and assess the efficiency of the PID controller design based on differential evolution optimization in nonlinear plants. The numerical results presented herein indicate that the proposed bio-inspired design is effective for the nonlinear control of nonlinear plants.     

Redundancy modelling and resolution for robotic mobile manipulators: a general approach

In this work the topic of kinematic redundancy modelling and resolution for robotic mobile manipulators is considered. A set of redundancy parameters is introduced to define a general inverse kinematic procedure for mobile manipulators. Then, redundancy is treated as a non-linear optimization problem with the purpose of finding robot configurations that maximize the designed metric measures. Some strategies to design the optimization objective function are introduced in order to achieve desirable redundant behaviours, such as obstacles avoidance, mobile base motions reductions and dexterity optimization. Moreover, the robot controller has been developed following an object-oriented software architecture principle that allows to keep it general and robot independent. As a prove of reliability and generality of our approach, the same controller has been used to control several different mobile manipulators in a simulation environment, as well as a real KUKA youBot robot.     

Simultaneous linear-quadratic optimal control design via static output feedback

In this paper, the problem of designing a fixed static output feedback control law which minimizes an upper bound on linear quadratic (LQ) performance measures for r distinct MIMO plants is addressed using linear matrix inequality (LMI) technique. An iterative LMI algorithm is proposed to obtain the solution. Examples are used to demonstrate its effectiveness. Copyright ©1999 John Wiley & Sons, Ltd.     

Algorithms and implementation of a set partitioning approach for modular machining line design

A transfer line design problem is considered. Transfer lines are sequences of workstations equipped with processing modules called blocks each of which performs specific operations. These lines are used for mass production of one type of product and thus execute repetitively a given set of operations. The machine parts move along the stations in the same direction. An identical cost is associated with each station and differing costs are associated with the blocks. The problem is to determine the number of stations, select a set of blocks and assign selected blocks to the stations so that operations of the selected blocks constitute the original set of operations and the total cost is minimized. A distinct feature of the problem is that operations at the same station are performed in parallel. Plus, there are inclusion, exclusion and precedence relations that restrict the assignment of the blocks and operations to the same station as well as the processing order of the operations on the transfer line. We implement a novel set partitioning formulation of this design problem with pre-processing procedures and heuristics. The presented approach has the best performance among the existing methods in terms of solution time and quality.     

Input-to-state practical stability analysis and controller design of switched affine systems: An observer-based approach

This paper addresses the problems of the input-to-state practical stability (ISPS) analysis and output feedback controller design for switched affine systems (SASs) subject to external disturbances. First, a switched affine observer is developed to estimate unmeasurable states. Then by combining the sampled-data control approach, a less conservative mode-dependent dynamic event-triggered mechanism (ETM) is established. The proposed dynamic ETM cannot only avoid Zeno behavior but also reduce the network transmission burden effectively. Further, based on time-dependent Lyapunov-Krasovskii functional and state-dependent switching laws, a set of feasible ISPS conditions are presented in the LMI forms by means of singular value decomposition. The designed switching law depends upon the sampled-data information of the estimated state and gets rid of the chattering phenomenon. Finally, an application example of the DC-DC flyback converter is given to verify the efficacy of the proposed algorithm.     

Discrete-time modeling and control of robotic manipulators

A general approach is presented to derive discrete-time models of robotic manipulators. Such models are obtained by applying numerical discretization techniques directly to the problem of the minimization of the Lagrange action functional. Although these models are in implicit form, they own a dynamic structure that allows us to design discrete-time feedback linearizing control laws. The proposed models and control algorithms are validated by simulation with reference to a three link robot.     

Simultaneous design and control of processes under uncertainty: A robust modelling approach

This paper presents a new methodology to integrate process design and control. The key idea in this method is to represent the system’s closed-loop nonlinear behaviour as a linear state space model complemented with uncertain model parameters. Then, robust control tools are applied to calculate bounds on the process stability, the process feasibility and the worst-case scenario. The new methodology was applied to the simultaneous design and control of a mixing tank process. The resulting design avoids the solution of computationally intensive dynamic optimizations since the integration of design and control problem is reduced to a nonlinear constrained optimization problem.     

Decentralized adaptive controller design of large-scale uncertain robotic systems

In this paper, we develop a decentralized neural network control design for robotic systems. Using this design, it is not necessary to derive the robotic dynamical system (robotic model) for the control of each of the robotic components, as in traditional robot control. The advantage of the proposed neural network controller is that, under a mild assumption, unknown nonlinear dynamics such as inertia matrix and Coriolis/centripetal matrix and friction, as well as interconnections with arbitrary nonlinear bounds can be accommodated with on-line learning.     

LMI optimization approach to robust decentralized controller design

A new approach for design of robust decentralized controllers for continuous linear time‐invariant systems is proposed using linear matrix inequalities (LMIs). The proposed method is based on closed‐loop diagonal dominance. Sufficient conditions for closed‐loop stability and closed‐loop block‐diagonal dominance are obtained. Satisfying the obtained conditions is formulated as an optimization problem with a system of LMI constraints. By adding an extra LMI constraint to the system of LMI constraints in the optimization problem, the robust control is addressed as well. Accordingly, the decentralized robust control problem for a multivariable system is reduced to an optimization problem for a system of LMI constraints to be feasible. An example is given to show the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

Heuristic approach to network database external parameters design

One of the most important issues in any database design is the optimization of its performance. The external database parameters play one of the main roles in a network database performance considerations. The analytic and the simulative approaches to establish these parameters are discussed. An heuristic approach using system simulation method to find the optimal database external parameters is developed and compared with the analytic one. The software system to implement the simulation methodology is presented. This system has been successfully implemented with the VAX-11 DBMS.     

基于非配置点部分误差控制联立方法的编队卫星队形重构

针对编队卫星队形重构问题,提出一种基于非配置点部分误差控制的联立方法。首先采用基于Radau配置点的拉格朗日插值多项式对微分代数方程组进行离散化处理;然后引入非配置点,要求避撞条件在非配置点处严格满足,但不对状态变量在非配置点处的误差估计进行控制,从而降低离散化后得到的非线性规划命题的求解难度;最后对3颗编队卫星的队形重构问题进行测试和仿真并与相应文献中的结果进行了比较,数值实验结果表明该方法具有更高的求解精度和求解效率。     

A passivity approach to controller design for quasi-resonant converters

In this paper, the passivity-based approach to controller design for the boost and buck quasi-resonant converters is addressed. Quasi-resonant converters use a soft switching method where the power devices switch at zero voltage or zero current, resulting in low switching loss and high power density. The controller design is carried out using the generalized state space average equations of these converter circuits and the celebrated “energy shaping plus damping injection” ideas of the passivity-based approach. Both direct and indirect output voltage regulation schemes are studied. Simulation results are presented to illustrate the features of the proposed controllers.     

Simultaneous tracking and regulation visual servoing of wheeled mobile robots with uncalibrated extrinsic parameters

This paper presentsa global adaptive controller that simultaneously solves tracking and regulation for wheeled mobile robots with unknown depth and uncalibrated camera-to-robot extrinsic parameters. The rotational angle and the scaled translation between the current camera frame and the reference camera frame, as well as the ones between the desired camera frame and the reference camera frame can be calculated in real time by using the pose estimation techniques. A transformed system is first obtained, for which an adaptive controller is then designed to accomplish both tracking and regulation tasks, and the controller synthesis is based on Lyapunov's direct method. Finally, the effectiveness of the proposed method is illustrated by a simulation study.     

嵌入式家庭控制器系统的设计与实现

一种用户可定制的嵌入式家庭控制器系统的总体设计方案,详细论述了系统采用的网络结构和各模块的软硬件设计。本系统的特点是可以对现有家用电器和安防装置进行集中或异地监视、控制以及三表的查收。