An Adaptive Controller Design for Flexible-joint Electrically-driven Robots With Consideration of Time-Varying Uncertainties

Almost all present control strategies for electrically-driven robots are under the rigid robot assumption. Few results can be found for the control of electrically driven robots with joint flexibility. This is because the presence of the joint flexibility greatly increases the complexity of the system dynamics. What is worse is when some system dynamics are not available and a good performance controller is required. In this paper, an adaptive design is proposed to this challenging problem. A backstepping-like procedure incorporating the model reference adaptive control is employed to circumvent the difficulty introduced by its cascade structure and various uncertainties. A Lyapunov-like analysis is used to justify the closed-loop stability and boundedness of internal signals. Moreover, the upper bounds of tracking errors in the transient state are also derived. Computer simulation results are presented to demonstrate the usefulness of the proposed scheme. Keywords: Adaptive control; Flexible-joint electrically-driven robot; FAT 2. Introduction Control of rigid robots has been well understood in recent years, but most of the schemes ignore the dynamics coming from electric motors and harmonic drivers that are widely implemented in the industrial robots. However, actuator dynamics constitute an important part of the complete robot dynamics, especially in the cases of high-velocity movement and highly varying loads[1],[2]. The main reason for using a reduced model is to simplify complexity of controller design. For each joint, consideration of the flexibility from the M. C. Chien was with the Department of Mechanical Engineering, National Taiwan University of Science and Technology. He is now with the Mechanical and Systems Research Laboratories, Industrial Technology Research Institute, No. 195, Sec. 4, Chung-Hsing Rd., Chutung, Hsinchu, 310, Taiwan, R.O.C. (e-mail: [email protected]). 2 A. C. Huang is with the Department of Mechanical Engineering, National Taiwan University of Science and Technology. No. 43, Keelung Rd., Sec. 4, Taipei, Taiwan, ROC. (Tel:+886-2-27376490, Fax: +886-2-37376460, E-mail: [email protected]). (A. C. Huang provides phone number because he is the corresponding author.

Position Control of IT-Robot manipulator using Multi–Loop FOPID

Position control of the manipulator has been noted for its difficulty as the result of the so-called dynamic stability problem, parameter uncertainty and dynamic coupling. This work focused on position control of the first four degree of freedom (DOF) of IT-Robot manipulator using Fractional Order PID (FOPID) controller that can conquer this difficulty. All procedure description to model of the manipulator and control has been detailed and simulated using MATLAB R2015a/Simulink; from the mechanical model generation in SimMechanic where, the manipulator joint is moved using DC motor. Parameters of FOPID controller are optimized using GA. The controller effectiveness is analyzed for set point tracking. By simulation results, it was observed that FOPID controller give better response with minimum error than PID controller for the position control of the IT-robot manipulator

Experimental study of a two-DOF five bar closed-loop mechanism

This research is to carry out an experimental study to examine and verify the effectiveness of the control algorithms and strategies developed at the Advanced Engineering Design Laboratory (AEDL). For this purpose, two objectives are set to be achieved in this research. The first objective is to develop a generic experiment environment (test bed) such that different control approaches and algorithms can be implemented on it. The second objective is to conduct an experimental study on the examined control algorithms, as applied to the above test bed. To achieve the first objective, two main test beds, namely, the real-time controllable (RTC) mechanism and the hybrid machine, have been developed based on a two degree of freedom (DOF) closed-loop five-bar linkage. The 2-DOF closed-loop mechanism is employed in this study as it is the simplest of multi-DOF closed-loop mechanisms, and control approaches and conclusions based on a 2-DOF mechanism are generic and can be applied to a closed-loop mechanism with a higher number of degrees of freedom. The RTC mechanism test bed is driven by two servomotors and the hybrid machine is driven by one servomotor and a traditional CV motor. To achieve the second objective, an experimental study on different control algorithms has been conducted. The Proportional Derivative (PD) based control laws, i.e., traditional iii PD control, Nonlinear-PD (NPD) control, Evolutionary PD (EPD) control, non-linear PD learning control (NPD-LC) and Adaptive Evolutionary Switching-PD (AES-PD) are applied to the RTC mechanism; and as applied to the Hybrid Actuation System (HAS), the traditional PD control and the SMC control techniques are examined and compared. In the case of the RTC mechanism, the experiments on the five PD-based control algorithms, i.e., PD control, NPD control, EPD, NPD-LC, and AES-PD, show that the NPD controller has better performance than the PD controller in terms of the reduction in position tracking errors. It is also illustrated by the experiments that iteration learning control (ILC) techniques can be used to improve the trajectory tracking performance. However, AES-PD showed to have a faster convergence rate than the other ILC control laws. Experimental results also show that feedback ILC is more effective than the feedforward ILC and has a faster convergence rate. In addition, the results of the comparative study of the traditional PD and the Computed Torque Control (CTC) technique at both low and high speeds show that at lower speeds, both of these controllers provide similar results. However, with an increase in speed, the position tracking errors using the CTC control approach become larger than that of the traditional PD control. In the case of the hybrid machine, PD control and SMC control are applied to the mechanism. The results show that for the control of the hybrid machine and the range of speed used in this experimental study, PD control can result in satisfactory performance. However, SMC proved to be more effective than PD control

Direct adaptive fuzzy control of flexible-joint robots including actuator dynamics using particle swarm optimization

In this paper a novel direct adaptive fuzzy system is proposed to control flexible-joints robot including actuator dynamics. The design includes two interior loops: the inner loop controls the motor position using proposed approach while the outer loop controls the joint angle of the robot using a PID control law. One novelty of this paper is the use of a PSO algorithm for optimizing the control design parameters to achieve a desired performance. It is worthy of note that to form control law by considering practical considerations just the available feedbacks are used. It is beneficial for industrial applications wherethe real-time computation is costly. The proposed control approach has a fast response with a good tracking performance under the well-behaved control efforts. The stability is guaranteed in the presence of both structured and unstructured uncertainties. As a result, all system states are remained bounded. Simulation results on a two-link flexible-joint robot show the efficiency of the proposed scheme

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

Energy-oriented Modeling And Control of Robotic Systems

This research focuses on the energy-oriented control of robotic systems using an ultracapacitor as the energy source. The primary objective is to simultaneously achieve the motion task objective and to increase energy efficiency through energy regeneration. To achieve this objective, three aims have been introduced and studied: brushless DC motors (BLDC) control by achieving optimum current in the motor, such that the motion task is achieved, and the energy consumption is minimized. A proof-ofconcept study to design a BLDC motor driver which has superiority compare to an off-the-shelf driver in terms of energy regeneration, and finally, the third aim is to develop a framework to study energy-oriented control in cooperative robots. The first aim is achieved by introducing an analytical solution which finds the optimal currents based on the desired torque generated by a virtual. Furthermore, it is shown that the well-known choice of a zero direct current component in the direct-quadrature frame is sub-optimal relative to our energy optimization objective. The second aim is achieved by introducing a novel BLDC motor driver, composed of three independent regenerative drives. To run the motor, the control law is obtained by specifying an outer-loop torque controller followed by minimization of power consumption via online constrained quadratic optimization. An experiment is conducted to assess the performance of the proposed concept against an off-the-shelf driver. It is shown that, in terms of energy regeneration and consumption, the developed driver has better performance, and a reduction of 15% energy consumption is achieved. v For the third aim, an impedance-based control scheme is introduced for cooperative manipulators grasping a rigid object. The position and orientation of the payload are to be maintained close to a desired trajectory, trading off tracking accuracy by low energy consumption and maintaining stability. To this end, an optimization problem is formulated using energy balance equations. The optimization finds the damping and stiffness gains of the impedance relation such that the energy consumption is minimized. Furthermore, L2 stability techniques are used to allow for time-varying damping and stiffness in the desired impedance. A numerical example is provided to demonstrate the results

Hybrid intelligent machine systems : design, modeling and control

To further improve performances of machine systems, mechatronics offers some opportunities. Traditionally, mechatronics deals with how to integrate mechanics and electronics without a systematic approach. This thesis generalizes the concept of mechatronics into a new concept called hybrid intelligent machine system. A hybrid intelligent machine system is a system where two or more elements combine to play at least one of the roles such as sensor, actuator, or control mechanism, and contribute to the system behaviour. The common feature with the hybrid intelligent machine system is thus the presence of two or more entities responsible for the system behaviour with each having its different strength complementary to the others. The hybrid intelligent machine system is further viewed from the system’s structure, behaviour, function, and principle, which has led to the distinction of (1) the hybrid actuation system, (2) the hybrid motion system (mechanism), and (3) the hybrid control system. This thesis describes a comprehensive study on three hybrid intelligent machine systems. In the case of the hybrid actuation system, the study has developed a control method for the “true” hybrid actuation configuration in which the constant velocity motor is not “mimicked” by the servomotor which is treated in literature. In the case of the hybrid motion system, the study has resulted in a novel mechanism structure based on the compliant mechanism which allows the micro- and macro-motions to be integrated within a common framework. It should be noted that the existing designs in literature all take a serial structure for micro- and macro-motions. In the case of hybrid control system, a novel family of control laws is developed, which is primarily based on the iterative learning of the previous driving torque (as a feedforward part) and various feedback control laws. This new family of control laws is rooted in the computer-torque-control (CTC) law with an off-line learned torque in replacement of an analytically formulated torque in the forward part of the CTC law. This thesis also presents the verification of these novel developments by both simulation and experiments. Simulation studies are presented for the hybrid actuation system and the hybrid motion system while experimental studies are carried out for the hybrid control system