Adaptive robust precision motion control of linear motors withnegligible electrical dynamics: theory and experiments

This paper studies the high performance robust motion control of an epoxy core linear motor, which has negligible electrical dynamics due to the fast response of the electrical subsystem. A discontinuous projection based adaptive robust controller (ARC) is first constructed. The controller theoretically guarantees a prescribed transient performance and final tracking accuracy in general, while achieving asymptotic tracking in the presence of parametric uncertainties. A desired compensation ARC scheme is then presented, in which the regressor is calculated using the reference trajectory information only. The resulting controller has several implementation advantages such as less online computation time, reduced effect of measurement noise, a separation of robust control design from parameter adaptation, and a faster adaptation rate. Both schemes are implemented and compared on an epoxy core linear motor. Extensive comparative experimental results are presented to illustrate the effectiveness and the achievable control performance of the two ARC designs     

High-performance robust motion control of machine tools: an adaptive robust control approach and comparative experiments

This paper studies the high-performance robust motion control of machine tools. The newly proposed adaptive robust control (ARC) is applied to make the resulting closed-loop system robust to model uncertainties, instead of the disturbance observer (DOB) design previously tested by many researchers. Compared to DOB, the proposed ARC has a better tracking performance and transient in the presence of discontinuous disturbances, such as Coulomb friction, and it is of a lower order. As a result, time-consuming and costly rigorous friction identification and compensation is alleviated, and overall tracking performance is improved. The ARC design can also handle large parameter variations and is flexible in introducing extra nonlinear robust control terms and parameter adaptations to further improve the transient response and tracking performance. An anti-integration windup mechanism is inherently built in the ARC and, thus, the problem of control saturation is alleviated. Extensive comparative experimental tests are performed, and the results show the improved performance of the proposed ARC.     

Application of shape memory alloy actuators for flexure control: theory and experiments

This paper presents a nonlinear control scheme for deflection control of a flexible beam using shape memory alloy (SMAs) actuators. These actuators possess interesting properties in terms of force generation capacity, possibility of miniaturization, and power consumption. However, their use in precision applications is hampered by undesirable characteristics, such as nonlinearities, hysteresis, extreme temperature dependencies, and slow response. By taking into account the nonlinear and thermal characteristics, a control scheme based on partial feedback linearization is developed to regulate the forces exerted by a differential SMA actuator pair attached to a flexible beam. The regulated force corresponds to a specific position of the flexible beam; hence, regulating the force results in position regulation. Using a Lyapunov stability analysis, qualitative guidelines are provided for selecting controller gain parameters. Furthermore, performance of the developed control scheme is tested experimentally on a laboratory testbed.     

Adaptive integral robust control of hydraulic systems with asymptotic tracking

In this paper, an adaptive integral robust controller is developed for high accuracy motion tracking control of a double-rod hydraulic actuator. We take unknown constant parameters including the load and hydraulic parameters, and lumped unmodeled disturbances in inertia load dynamics and pressure dynamics into consideration. A discontinuous projection-based adaptive control law is constructed to handle parametric uncertainties, and an integral of the sign of the extended error based robust feedback term to attenuate unmodeled disturbances. Moreover, the present controller does not require a priori knowledge on the bounds of the lumped disturbances and the gain of the designed robust control law can be tuned itself. The major feature of the proposed full state controller is that it can theoretically guarantee global asymptotic tracking performance with a continuous control input, in the presence of various parametric uncertainties and unmodeled disturbances such as unmodeled dynamics as well as external disturbances via Lyapunov analysis. Comparative experimental results are obtained for motion control of a double-rod hydraulic actuator and verify the high-performance nature of the proposed control strategy.     

Adaptive robust motion control of linear motors for precision manufacturing

Linear motors offer several advantages over their rotary counterparts in many precision manufacturing applications requiring linear motion; linear motors can achieve a much higher speed and have the potential of gaining a higher load positioning accuracy due to the elimination of mechanical transmission mechanisms. However, these advantages are obtained at the expense of added difficulties in controlling such a system. Specifically, linear motors are more sensitive to disturbances and parameter variations. Furthermore, certain types of linear motors such as the iron core are subject to significant nonlinear effects due to periodic cogging force and force ripple. To address all these issues, the recently proposed adaptive robust control (ARC) strategy is applied and a discontinuous projection-based ARC controller is constructed. In particular, based on the special structures of various periodic nonlinear forces, design models consisting of known basis functions with unknown weights are used to approximate those unknown nonlinear forces. On-line parameter adaptation is then utilized to reduce the effect of various parametric uncertainties such as unknown weights, inertia, and motor parameters while certain robust control laws are used to handle the uncompensated uncertain nonlinearities effectively for high performance. The resulting ARC controller achieves a guaranteed transient performance and a guaranteed final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. In addition, in the presence of parametric uncertainties, the controller achieves asymptotic output tracking. Extensive simulation results are shown to illustrate the effectiveness of the proposed algorithm.     

Transputer control of hydraulic actuators and robots

The paper reports and discusses results from a Danish mechatronic research program focusing on intelligent actuators for intelligent motion control. A mechatronic test facility with a transputer controlled hydraulic robot suitable for real-time experimentation and evaluation of control laws and algorithms is described. Concepts of intelligent motion control and intelligent hydraulic actuators are proposed. Promising experimental path-tracking results obtained from model-based adaptive control algorithms are presented and discussed. The experiments confirm that transputers have significant advantages in intelligent control of actuators and robots for high-speed and high-precision tasks. Further, research on learning controllers and hybrid controller architecture, including real-time switching between control algorithms, benefits from applying transputer technology     

Adaptive robust motion control of SISO nonlinear systems with implementation on linear motors

For the purpose of controlling an X–Y table driven by linear motors with a high precision, an adaptive robust motion tracking control method is first introduced. The controller is developed based upon a class of SISO nonlinear systems whose nonlinear part can be linearly parameterized. The advantage of such a controller is that parametric uncertainties and unknown disturbances can be dealt with, which is essential for a high precision of the control of linear-motor-driven X–Y table. With the prior knowledge of the bounds of the system parameters, a discontinuous projection is utilized in the adaptive law to ensure the boundedness of the parameters estimates. The algorithm is then implemented on a real X–Y table driven by the linear motors. In the modeling of such a system, fiction effects are also considered, which is useful for the derivation of the adaptive law. Experiments on the X–Y table are carried out and the results show excellent tracking performance of the system.     

Adaptive dynamic surface control with sliding mode control and RWNN for robust positioning of a linear motion stage

Ball-screw-driven system provides high precision and long stroke range for positioning and tracking control of a linear stage. Friction and backlash nonlinearities in this system act often the main obstacles for high precision control. It is difficult to achieve effective compensation of these types of nonlinearities by traditional linear control methodology without the aid of a proper compensation schemes. Here, we present an adaptive dynamic surface control scheme combined with sliding mode control to compensate for friction and backlash nonlinearities in a linear stage motion system. The adaptive laws of the recurrent wavelet neural networks and friction estimation are derived to approximate and compensate for the backlash and friction nonlinearities. The boundedness and convergence of the closed-loop system are guaranteed from a Lyapunov stability analysis. The performance of the proposed control scheme was verified through simulations and experiments on the ball-screw-driven linear stage.     

Adaptive robust fast control for induction motors

A new induction motor position controller that exhibits fast response and robustness is proposed. The control strategy is based on the well-known linear quadratic regulator design principle. By adaptively adjusting a penalty parameter, it is shown that the control strategy enables the induction motor system to exhibit fast convergence. Meanwhile, since the sliding mode will occur in the transient process, the fast control inherits the robustness in matched uncertainties of the sliding-mode control. In addition, to alleviate the chattering effect of the switching control signal, a low-pass filter is used to smooth the control and its design is integrated with the switching control design. The performance of the proposed control strategy is verified by experimental results     

Adaptive robust control of fully-constrained cable driven parallel robots

In this paper, adaptive robust control (ARC) of fully-constrained cable driven parallel robots is studied in detail. Since kinematic and dynamic models of the robot are partly structurally unknown in practice, in this paper an adaptive robust sliding mode controller is proposed based on the adaptation of the upper bound of the uncertainties. This approach does not require pre-knowledge of the uncertainties upper bounds and linear regression form of kinematic and dynamic models. Moreover, to ensure that all cables remain in tension, proposed control algorithm benefit the internal force concept in its structure. The proposed controller not only keeps all cables under tension for the whole workspace of the robot, it is chattering-free, computationally simple and it does not require measurement of the end-effector acceleration. The stability of the closed-loop system with proposed control algorithm is analyzed through Lyapunov second method and it is shown that the tracking error will remain uniformly ultimately bounded (UUB). Finally, the effectiveness of the proposed control algorithm is examined through some experiments on a planar cable driven parallel robot and it is shown that the proposed controller is able to provide suitable tracking performance in practice.     

A straight-line motion tracking control of hydraulic excavator system

The Cartesian control of automated excavators has been noted for its difficulty, especially due to severe nonlinearities in hydraulic actuators, which are hardly observed in electric motors. The nonlinearities tend to become even more severe as the size of an excavator increases and the speed of end-effector becomes faster, and conventional controls have been unable to adequately handle nonlinearities to this degree. In a conviction that modern robust controls can resolve this problem, we approached this problem by adopting Time-delay control (TDC) as the baseline control, and by enhancing it with compensators on the basis of insights obtained from the plant dynamics. The resulting control law has been applied to straight-line motions of a 13 ton hydraulic excavator with a bucket (end-effector) speed of 0.5 m/s, a speed level at which skilful operators work. The accuracy achieved was mostly within 3 cm for surfaces with various inclinations and over broad ranges of joint motions, which is far better than that of an expert operator. These promising results not only justify our approach to this problem, but also convince us that we now have an effective means for the control of automated excavator systems.     

Application of robust iterative learning algorithm in motion control system

Robustness issue is considered to be one of the major concerns in application of the iterative learning control in motion control systems. The robustness in servo systems is related to parameter uncertainties and noise accumulation. In this paper, both parameter uncertainties and noise are considered in derivation of the error dynamic equation of the ILC algorithm. Based on the error dynamics, the H_∞ framework is utilized to design the robust learning controller. An optimization design process in selecting the proper learning gain and determining the learning function is proposed to ensure that both tracking performance and convergence condition are achieved. Simulations and experiments are conducted to validate the robust learning algorithm which can be applied efficiently to machine tools with the payload varying from 0 to 20 kg. The experimental results demonstrate that the proposed method improves the tracking and contouring performances significantly when performing a complex NURBS curve on a three-axis milling machine.     

Parameter identification and position control for helical hydraulic rotary actuators based on particle swarm optimization

It is difficult to obtain an accurate mathematical model in electro-hydraulic servo control system, due to the nonlinear factors such as dead zone, saturation, flow coefficient, and friction. Hence, a parameter identification algorithm, combining recursive least squares (RLS) with modified nonlinear particle swarm optimization (NPSO) algorithm, is proposed. On this basis, another improved NPSO algorithm is also put forward, aiming at searching for the optimal proportional–integral (PI) controller gain of the nonlinear hydraulic system while giving comprehensive consideration to the system performance indexes. The system identification experiments and position tracking control are conducted, respectively. As indicated by the comparison with the least squares (LS), RLS, PSO, and RLS–LPSO results, the proposed method shows higher identification and control accuracy.     

The reduction of stick-slip friction in hydraulic actuators

The stick-slip friction phenomenon is observed near zero relative velocity, during the transition from static to dynamic friction, when static friction is greater than dynamic friction. This nonlinear change in friction force over a small change in velocity results in difficulties in achieving accurate and repeatable position control. In some cases, the actuator position controller reaches a limit cycle (hunting effect). Friction compensation at low speeds has traditionally been approached through various control techniques. This paper proposes an alternative solution, namely, friction avoidance. By rotating the piston and rod, the Stribeck region of the friction-velocity curve is avoided and the axial friction opposing the piston movement is approximately linearized. Simulation and experimental results are presented to validate this approach.     

Impedance control of series elastic actuators: Passivity and acceleration-based control

Series elastic joints allow force and impedance controllers to be implemented on high torque and high power density motors. Several impedance controllers have been proposed whose stability is usually analyzed by means of passivity-based tools such as the Z-width characterization. This paper proposes an overview of existing impedance control solutions for series elastic joints and derives the passivity characterizations that are still missing in the literature, thus providing a complete and coherent overview of the existing solutions. Within this overview, we highlight the advantages of impedance control based on positive acceleration feedback showing improved stability robustness and impedance accuracy with respect to existing solutions. These advantages are theoretically motivated (considering ideal conditions) and experimentally validated.     

Modeling,control and experimental investigation of horizontal hydraulic flight motion simulator

The horizontal hydraulic flight motion simulator (HHFMS) is widely applied in the hardware-in-the-loop (HWIL) simulation of the aircraft attitude attributing to high dynamic response and large power density when a heavy load is tested. In order to achieve a high-precision control performance of the HHFMS, some serious mismatched uncertainties consisting of nonlinear friction torque, unbalanced gravity torque, inertia variation and unmodeled dynamics have to be taken into account. In particular, gravity torque, as an asymmetrical load, will degrade the control performance at the starting moment. In this paper, via transforming mismatched uncertainties into matched uncertainties as a unified disturbance, a cascaded model was firstly established, which can not only avoid designing the complex virtual control laws but also help indirectly reduce the asymmetrical effect of gravity torque. Then, a linear extended state observer (LESO) based continuous sliding mode control (SMC) was proposed. LESO is expected to realize a good suppression of disturbance, as well as convenient acquisition of states signals such as velocity and acceleration. In addition to ensuring the control accuracy and the robustness, continuous SMC without sign function also frees from worrying about possible chattering. Moreover, a setting criterion of two parameters that satisfy Hurwitz's Condition in the third-order SMC was also provided. Finally, experimental investigation shows the effectiveness of dynamic modeling and the practicability of the proposed control method.     

Adaptive robust control of media advance systems for thermal inkjet printers

The inkjet printer offers an attractive feature set that fits well to the consumer’s needs at the low-end color hardcopy market. Better performance at a lower cost is and will always be the driving force for future product development. In this paper, an adaptive robust control is implemented to the media advance system in thermal inkjet printers to achieve designate objectives. Robust control guarantees the transient performance and final tracking error. The parameter adaptation also maintains asymptotic tracking. The experimental results indicate the excellent transient performance and final tracking accuracy.     

Adaptive control of the car motion of a monorail road

Construction of the mathematical model of the car motion, identification of the model parameters, and filtering of the coordinates of the car motion in a monorail road are considered. The law of control of the car motion that ensures an acceptable quality of operation of the control system is selected. Simulation confirming the serviceability of the obtained algorithms and the whole control system is performed.