Spatial-based iterative learning control for motion control applications

For many motion control applications spatial constraints are often more important than temporal constraints. In recent work, we have developed a spatial control strategy called the ε-controller for mobile robot applications. The control strategy is based solely on static path geometry with position (in space) feedback. Motivated by this idea, in this paper, we consider the notion of spatial-based iterative learning control (ILC). Specifically, we consider repetitive operation problems where corrections are made to the control signal from trial to trial. Unlike traditional ILC, however, which updates control signals based on the time elapsed along a trajectory, we instead make updates based on path errors and progress along the path. The idea is demonstrated via simulation for a system with bang–bang velocity control. Experimental results using a high-precision, two-axis gimbal mechanism are presented to show the effectiveness of the strategy.     

Impedance control of robots using voltage control strategy

Impedance control provides a unified solution for the position and force control of robot manipulators. The dynamic behavior of a robotic system in response to environment is prescribed by an impedance model formed as Thevenin model. This model is certain and linear while the robot manipulator is highly nonlinear, coupled, and uncertain. Therefore, impedance control must overcome nonlinearity, coupling, and uncertainty to convert the robotic system to the impedance model. To overcome these problems, this paper presents a novel impedance control for electrically driven robots, which is free from the manipulator dynamics. The novelty of this paper is the use of voltage control strategy to develop the impedance control. Compared with the commonly used impedance control, which is based on the torque control strategy, it is computationally simpler, more efficient, and robust. The mathematical verification and simulation results show the effectiveness of the control method.     

Robust control of flexible-joint robots using voltage control strategy

So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.     

Sufficiency for optimal control with state and control constraints

Sufficient conditions are derived for optimal control of a dynamical system described by ordinary differential equations and subject to constraints on both state and control.     

结构主动控制的LQG/LTR改进方法

提出一种改进的LQG／LTR(Linear Quadratic Gaussian synthesis with a Loop Transfer Recovery)结构主动控制方法，一种新的补偿器结构被用于回路传输恢复(LTR)。这个补偿器有以下优点：(1)它是开环稳定的；(2)它能保证整个闭环系统的稳定性；(3)更重要的是．对于相同的回路传输恢复度，它所需要的增益要小于传统LQG／LTR方法的基于观测器的控制器增益。还有，就是这个新的补偿器比传统的基于观测器要有较好的恢复性能。最后，数值算例验证了本文方法的有效性。     

Decentralized direct adaptive fuzzy control of robots using voltage control strategy

Decentralized control is the most favorite control of robot manipulators due to computational simplicity and ease of implementation. Beside that, adaptive fuzzy control efficiently controls uncertain nonlinear systems. These motivate us to design a decentralized fuzzy controller. However, there are some challenging problems to guarantee stability. The state-space model of the robotic system including the robot manipulator and motors is in a noncompanion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. For this purpose, adaptive fuzzy control may use all variable states. As a result, it suffers from computational burden. To overcome the problems, we present a novel decentralized Direct Adaptive Fuzzy Control (DAFC) of electrically driven robot manipulators using the voltage control strategy. The proposed DAFC is simple, in a decentralized structure with high-accuracy response, robust tracking performance, and guaranteed stability. Instead of all state variables, only the tracking error of every joint and its derivative are given as the inputs of the controller. The proposed DAFC is simulated on a SCARA robot driven by permanent magnet dc motors. Simulation results verify superiority of the decentralized DAFC to a decentralized PD-fuzzy controller.     

A robust attitude control strategy with guaranteed transient performance via modified Lyapunov-based control and integral sliding mode control

In this paper, a robust control strategy with guaranteed transient performance is presented for spacecraft attitude maneuvers. Firstly, a Lyapunov-based controller is designed to achieve high-performance attitude control in the absence of disturbance and parameter variation. Unlike most existing designs, the feedback gains in the proposed controller increase with the attitude error convergence. Consequently, the system response can be accelerated without increasing the control torque at large attitude error. The overshooting phenomenon is also avoided by imposing a restriction on the parameter selection. Then, the integral sliding mode control technique is employed to preserve the desired transient characteristics and improve the robustness. Furthermore, by combining an adaptive scheme with the boundary layer method, the conservativeness in the switching gain selection is reduced and the chattering is also suppressed. Theoretical analysis and simulation results verify the effectiveness of the proposed strategy.     

Bulldozer blade control

A simple control system for controlling a bulldozing blade was developed and tested. Both controls of the bulldozing load acting on the bulldozer blade and the blade position control were validated through an operational test. It was observed that the application of this control system could not only reduce the frequent up and down actions of adjusting the bulldozer blade considering the conditions of the load applied and the irregularity of terrain surface, but also could allow the operator to concentrate on the steering during the operation of earth moving.     

静电陀螺支承控制的自适应逆控制分析

静电陀螺的支承控制系统中由于不可避免地存在建模不准确及对象扰动,传统的控制器设计只能在系统动态控制与对象扰动消除之间折衷。根据自适应逆控制的结构,利用模糊径向基函数神经网络进行对象建模、逆对象建模和扰动消除建模,设计了带扰动消除的自适应逆控制的八电极静电陀螺支承控制器。仿真表明,该控制器可以同时提高控制的精度和鲁棒性,在保证支承系统动态性能的同时,大大抵消对象扰动的影响,克服传统控制方法的折衷缺陷,对静电陀螺的自适应逆控制器的工程实现具有重要意义。     

Parametric variational solution of linear-quadratic optimal control problems with control inequality constraints

A parametric variational principle and the corresponding numerical algo- rithm are proposed to solve a linear-quadratic （LQ） optimal control problem with control inequality constraints. Based on the parametric variational principle, this control prob- lem is transformed into a set of Hamiltonian canonical equations coupled with the linear complementarity equations, which are solved by a linear complementarity solver in the discrete-time domain. The costate variable information is also evaluated by the proposed method. The parametric variational algorithm proposed in this paper is suitable for both time-invariant and time-varying systems. Two numerical examples are used to test the validity of the proposed method. The proposed algorithm is used to astrodynamics to solve a practical optimal control problem for rendezvousing spacecrafts with a finite low thrust. The numerical simulations show that the parametric variational algorithm is ef- fective for LQ optimal control problems with control inequality constraints.