C.W. de Silva

Compensation for transmission delays in an ethernet-based control network using variable-horizon predictive control

Distributed control networks encounter nondeterministic delays in data communication between sensors, actuators, and controllers, including direct-feedback control and higher level supervisor control. This paper presents a novel strategy, which extends the Generalized Predictive Control (GPC) algorithm to compensate for these data-transmission delays. Communication lines between sensors to controller and controller to actuators are considered. The present strategy incorporates a minimum-effort estimator to estimate missing or delayed sensor data and a variable-horizon adaptive GPC controller to predict the required future control efforts to drive the plant to track a desired reference trajectory. Action buffers are introduced at the actuators to sequence the future control efforts. A parallel objective of this paper is to investigate the suitability of the Ethernet network, which is cost-effective and widely deployed for implementing networked control systems. An Ethernet-based client-server control architecture is developed. The developed scheme is implemented on the dual-axis hydraulic position system of an industrial fish-processing machine.

Tracking control of an electrohydraulic manipulator in the presence of friction

Analysis and estimation of friction and compensation for its effects in the control of an electrohydraulic manipulator is addressed. The specific hydraulic manipulator is an integral part of an automated fish processing machine which has been developed in our laboratory. The analysis reveals that considerable static and dynamic friction exists in the system. An available nonlinear observer for Coulomb friction, is modified to simultaneously estimate friction, velocity, and acceleration. A novel observer-based friction compensating control strategy is developed for improved tracking performance of the manipulator. The approach is based on acceleration feedback control. Experimental investigations show that this controller significantly outperforms the conventional PD controller. The general approach presented in this paper, may be applied to compensate for friction in any servomechanism, particularly when the actuator dynamics is not negligible.

A Hybrid Visual Servo Controller for Robust Grasping by Wheeled Mobile Robots

This paper develops a robust vision-based mobile manipulation system for wheeled mobile robots (WMRs). In particular, this paper addresses the retention of visual features in the field of view of the camera, which is an important robustness issue in visual servoing. First, the classical approach of image-based visual servoing (IBVS) for fixed-base manipulators is extended to WMRs and a control law with Lyapunov stability is determined. Second, in order to guarantee visibility of visual features, an innovative controller with machine learning using Q-learning is proposed, which can learn its behavior policy and autonomously improve its performance. Third, a hybrid controller for robust mobile manipulation is developed to integrate the IBVS controller and the Q-learning controller through a rule-based arbitrator. This is thought to be the first paper that integrates reinforcement learning or Q-learning with visual servoing to achieve robust operation. Experiments are carried out to validate the approaches developed in this paper. The experimental results show that the new hybrid controller developed here possesses the capabilities of self-learning and fast response, and provides a balanced performance with respect to robustness and accuracy.

Stability Analysis of Isolated Bidirectional Dual Active Full-Bridge DC–DC Converter With Triple Phase-Shift Control

This paper proposes a new method for stability analysis of a bidirectional dual full-bridge dc-dc converter with triple phase-shift control under arbitrary parameter changes. The present analysis makes the stability determination of these power converters more systematic and precise than the existing methods in this field, which are largely based on simulation. Nonlinear and periodic operation of the bidirectional converter is presented including the control circuit. Using the working theory, the converter operation is separated into several stages. Equivalent circuits and state equations are developed for each stage. The Lyapunov function method is used to determine the stability of the converter in every stage. Justification is provided for the absence of abrupt changes of the state variables or infinite noise at the interface of different stages. The stability of the bidirectional converter is determined theoretically by integrating these concepts. Some simulation results are provided to validate the developments.

Stability validation of a constrained model predictive networked control system with future input buffering

This paper addresses the stability of a newly-developed control strategy for networked control systems (NCS). This control strategy hones the potential of constrained model predictive control (MPC) by buffering the predicted control sequence at the actuator in anticipation of typical data transmission errors associated with NCS. Closed-loop stability in the sense of Lyapunov is guaranteed for the controller in the linear case, by bounding the projected receding horizon costs by lower- and upper-bounding terms using a predetermined terminal cost. A stability theorem is developed, which provides a suboptimal measure for the controller in real time, and is sufficient to estimate the worst-case transmission delay that can be handled by the developed control buffering strategy. The stability conditions, as governed by the theorem, are validated through real-time implementation on an electro-hydraulic servo system of an industrial processing machine, through an Ethernet network.

Knowledge-based control approach for robotic manipulators

The integration of hard algorithmic control and soft knowledge-based control is addressed, in the specific context of robotic manipulator control. In particular, a hierarchical control structure having a high-speed hard controller at the lowest level and an intelligent observer and an intelligent tuner at the upper levels, is discussed. The rationale for a specific control structure is explored, and the necessary qualitative and analytical foundation for the control structure is presented. To demonstrate the development and feasibility of this control structure, an example application has been programmed on a SUN workstation. A two degree-of-freedom robot was simulated (a C program) as a separate UNIX process. The intelligent observer was developed using an available AI toolkit. The top-level intelligent tuner was developed from a valid set of linguistic tuning rules for proportional-integral-derivative (PID) servos, using fuzzy system concepts, and implemented as a set of decision tables. The control str...

Mechatronic Design Quotient as the Basis of a New Multicriteria Mechatronic Design Methodology

A concurrent, integrated, and multicriteria methodology is presented for the conceptual design of mechatronic systems. It uses an evaluation model called mechatronic design quotient (MDQ) to facilitate decision-making in the design process. A nonlinear fuzzy integral is used for the aggregation of criteria in MDQ, thereby accommodating possible correlations among them. The performance of the developed methodology is validated by applying it to an industrial fish cutting machine called Iron Butcher-an electromechanical system that falls into the class of mixed or multidomain systems

Autonomous Robotic Capture of a Satellite Using Constrained Predictive Control

This paper investigates the use of model-based predictive control for the capture of a multi-degrees-of-freedom object that moves in a somewhat predictable manner, using a deployable manipulator. The study is conducted through both computer simulations and ground-based experiments with the intended application focused on automating the robotic capture of a free-floating and spinning satellite. The present investigation uses an innovative manipulator known as the multi module deployable manipulator system (MDMS), which has been designed and built in our laboratory. The MDMS is used to capture the simulated target satellites. The objective is to evaluate the performance of the predictive controller for the capturing task and to investigate the need and feasibility of incorporating constraints into the controller. Offline solutions to multi parametric quadratic programming (mp-QP) problems are used to create a lookup table so that constrained optimal control decisions can be made in real time. Moreover, a suboptimal formulation of the mp-QP problem has been used to reduce the size of the online lookup table and to mitigate any numerical problems. The results show that when the satellite motion is predicted, the tracking performance is improved. Furthermore, when the physical constraints of the system are formulated into the optimization, the controller becomes aware of its own limitations and the approach toward the satellite is improved by eliminating the possible overshooting of the target

Friction estimation in a planar electrohydraulic manipulator

An automated machine for industrial fish head cutting has been designed and built in our laboratory. A planar electrohydraulic manipulator is used to quickly move a sharp pneumatically actuated blade to its desired position. There are two lubricated metal guideways under the blade. The objective of this experimental investigation is to understand the nature of friction present in the system and corresponding effects. At first, a simple open-loop procedure is used to obtain the steady-state friction-velocity behavior at very low velocities. Online estimation of dynamic friction (in the closed-loop system) is considered afterwards. A nonlinear reduced-order observer, introduced in the literature, for simultaneous estimation of friction and velocity, is applied to the system. Experimental results indicate that this estimator does not work well. Thus, in its original form, it is not suitable. A modification is proposed herein, to obtain good performance. Experiments with the modified observer show satisfactory estimation of velocity and friction.

System-Based and Concurrent Design of a Smart Mechatronic System Using the Concept of Mechatronic Design Quotient (MDQ)

A mechatronic system needs an integrated, concurrent, and system-based design approach due to the existence of interactions among its subsystems, and also the existence of interactions between the criteria involved in a realistic evaluation of a mechatronic product. This paper presents a systematic methodology for a detailed mechatronic design based on a mechatronic design quotient (MDQ). MDQ is a multicriteria index, reflecting a system-based evaluation of a mechatronic design, which is calculated using soft computing techniques, thereby accommodating interactions between criteria and human experience. A niching genetic algorithm is utilized to explore the huge search space raised due to concurrent and integrated design approach, with the aim to find the elite representatives of different possible configurations. To demonstrate the method, it is applied to an industrial fish cutting machine called the Iron Butcher-an electromechanical system that falls into the class of mixed or multidomain systems.