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The belt-drive control enables the mechanical system to gain the advantages of lightweight, vibration absorption and high torque, while it brings strong nonlinear disturbances due to friction, backlash and flexibility. Therefore an improved disturbance observer control method based on the dual-rate loop structure is proposed in this paper to suppress these disturbances. Only a linear low-frequency device model is required which indicates this method avoids the dependence on accurate identification of the nonlinear uncertain systems. The rate information on motor-side is replaced with the input signal of inner loop due to the high bandwidth of inner motor loop, which greatly simplifies the design of control system. In case of insufficient system bandwidth, the proposed method integrates the favorable information of the load-side and the motor-side under the DOB framework. And the speed-commutation spikes and chatters resulting from disturbances on the flexible transmission chain can be more effectively suppressed by the proposed control structure compared with the conventional methods.

Multiple disturbances are the main constraints that hinder the high-performance velocity tracking of the gimbal servo system in CMG. This paper presents a non-cascade structured velocity-tracking controller (NCVTC) based on a refined disturbance observer (RDO) for handling multiple disturbances and improve the tracking performance. Specifically, a disturbance observer (DO) is designed to estimate the imbalance disturbance which can be represented by an exogenous system. The disturbances that cannot be modeled a priori are treated as a lumped term and estimated via extended state observer (ESO). By resorting to disturbance estimation, a novel sliding mode controller (SMC) based on the disturbance estimation values is developed to handle the mismatched problem and chattering issue. Finally, experimental tests are conducted to verify the effectiveness of the proposed anti-disturbance control scheme.

In this paper, we consider the time-varying trajectory tracking boundary control problem for the flexible rotation beam subject to distributed disturbance. A partial differential equation model for the flexible rotation beam system with the coupling of angle and vibration displacement is established by Hamilton principle. By introducing a servo system generated by the reference signal, a boundary controller is proposed to track the desired time-varying trajectory, which is different from the fixed angular position in most existing work. A Lyapunov-based stability analysis is presented to demonstrate the tracking error system between the servo system and the original system is uniformly ultimately bounded. Based on the infinite dimensional operator theory, it is proved that the closed-loop system is well-posed and all signals remain bounded. Numerical simulations verify the correctness of the theory and the effectiveness of the control strategy. And the experiments based on the Quanser platform demonstrate the same result as well.

Nowadays, the dual closed-loop Proportional-Integral-Lead (PI-Lead) controller is widely used, especially for the servo systems where high performance is required for motion control, like lithography machines and vehicle-used Lidars. Considering complex industrial applications and working conditions, more comprehensive and systematic research about the structure and potential problem of the PI-Lead controller is necessary for enhancing its performance and robustness. In this paper, the failure mechanism of the classic Anti-Windup methods in the PI-Lead controller is analyzed. By adjusting the location of control blocks, a novel reversed-structure-based PI-Lead controller is proposed as a complement to the traditional anti-windup methods for effective operation, and to make the system stable under the severe impact disturbance. Then, a self-commissioning strategy is designed, based on a Fast Root Mean Square Error (FRMSE) index and without additional manual tuning factors. Compared with classic indicators, the proposed FRMSE index can achieve faster instability detection and accelerate the tuning process to protect the equipment.

Most recent studies on adaptive hydraulic tracking control focus on trajectory tracking performance while the parameter convergence property is often unsatisfying. This paper proposes a composite learning adaptive position tracking controller with improved parameter convergence for electro-hydraulic servo systems. In the composite learning, a prediction error is formulated to exploit input-output memory data, and parameter estimates are driven simultaneously by tracking and prediction errors. Practical exponential stability of the closed-loop system, which implies the convergence of both the tracking and parameter estimation error, is established by a more realizable interval-excitation condition than the stringent persistent-excitation condition. Therefore, superior trajectory tracking is obtained compared with the classical adaptive hydraulic control. Besides, the initial fluid control volumes of hydraulic systems are assumed to be unknown a priori, which enhances the generality of the proposed control approach. The above two properties are generally not achievable in prevalent approaches to adaptive hydraulic control. Moreover, noisy acceleration signals and the time derivatives of pressure signals are not needed in the proposed approach, which improves its robustness against measurement noise. Extensive experimental results verify its superiority over currently available ones.

This article proposes a real-time method to control the contour error for industrial five-axis machine tools by combining the generalized predictive control (GPC) and the feedback correction (FBC) with dynamic con- tour error estimation (CEE). The CEE is developed by well considering the curves curvature and torsion based on Taylor series expansion and Frenet frame theory. By utilizing the spherical linear interpolation, the tool orientation and the tool tip position are synchronized with respect to the curve length. A novel dynamic foot point searching procedure is established to weaken the influences of the tracking errors magnitude on the CEE precision. To tackle the transmission effect, the GPC is adopted to predict the servo systems outputs, and then, the induced tool pose deviations, which are subsequently utilized to counteract the contour errors, are predicted by constructing Jacobian matrixes. Especially, the FBC loops are constructed to suppress the influences of disturbances and further to reduce the magnitudes of contour errors. Simulations and experiments are conducted to verify the effectiveness of the proposed methods.

This paper proposes a non-smooth funnel control (NSFC) strategy based on the extended state observer (ESO) for motor-drive servo systems with unknown dynamics. These unknown dynamics, including the modeling error, the external disturbances, and the nonlinear friction, are considered as a lumped disturbance. For estimating the unknown states and the lumped disturbance, a non-linear bandwidth extended state observer (NLB-ESO) is developed. The non-linear bandwidth designed using the Gaussian function and the position observation error can deal with the ``peaking value problem" caused by the high observer gains. Furthermore, a funnel error surface is proposed based on the non-smooth error transformation and incorporated into the dynamic surface control design procedure, where the NSFC can prescribe the position tracking error in a funnel region with small steady-state error and overshoot, and short adjustment time. The non-smooth funnel error surface also avoids the singular problem in controller design by selecting the non-smooth parameter. Moreover, the stability of the closed-loop control system with the NLB-ESO is guaranteed by the Lyapunov theory. Comparative simulations and experiments show that the proposed NSFC can prescribe the tracking error in a funnel and ensure better tracking performance.

A dual-flexible manipulator with a telescopic arm is affected by joint flexibility, load flexibility, and bearing friction, which will cause angular velocity fluctuation. Besides, the motion of the telescopic arm leads to dynamic parameters of the flexible load in the servo system time-varying. The variation of dynamic parameters increases fluctuations of angular velocity. Fluctuations in angular velocity will aggravate the vibration of the manipulator and affect the control accuracy of end-effectors. In this paper, the adaptive PI control strategy with the disturbance observer (DOB) suppresses the vibration of the manipulator by weakening the angular velocity fluctuations. Firstly, dynamics equations of the dual-flexible manipulator servo system considering the bearing friction are established by using the assumed mode method. Next, the low-pass filter in DOB is designed according to the robust stability theorem, so that the servo system can satisfy the stability under dynamic parameters time-varying and friction torque simultaneously. Then, the adaptive law and the over-load compensation control law are designed by Lyapunov’s stability theorem. Finally, numerical simulation analysis and control experiments of the manipulator are carried out. The simulation and experimental results show that: 1) The bearing friction torque can cause angular velocity fluctuations, but the DOB can effectively reduce the influence of the disturbance torque. 2) The adaptive control strategy can effectively reduce angular velocity errors under conditions that the telescopic arm is in different lengths. Therefore, the adaptive PI control strategy with the DOB can effectively suppress angular velocity fluctuations of the manipulator.

The high precision control of angular speed in low-speed gimbal servo systems is an essential topic in the operation of the single gimbal control moment gyro (SGCMG). This paper proposes a discrete control algorithm to suppress the influence of various disturbances on the low-speed gimbal servo system and the constraint between controller parameters and sampling time is established to ensure the stability of the system. To begin with, the disturbance analysis of the low-speed gimbal servo system is presented, including the torque ripple in the permanent magnet synchronous motor (PMSM), nonlinear friction, coupling torque caused by the spacecraft motion, and the parameter uncertainties. Then, a composite control method combining the sliding mode controller (SMC) with sliding mode observer (SMO) is applied to the speed loop and q-axis current loop. The interferences are estimated by two sliding mode observers while sliding mode controllers are designed to eliminate the influence brought by the residual disturbances. The stability of the overall system is proved based on the Lyapunov criterion. Finally, simulation and experimental results verify the effectiveness of the proposed composite control method.

Intelligent driving system requires more precise and reliable steering control, and steering-by-wire (SBW) technology can better adapt to the development of autonomous driving. The permanent magnet synchronous motor (PMSM) servo system is the actuator of the SBW. Aiming at the uncertainties of the PMSM servo system, a new adaptive control method for PMSM servo system is proposed. Parameter adaptive laws are designed for each slowly varying parameter and unknown parameter, and robust terms are introduced to the adaptive laws for the parameter uncertainties. The convergence speed of the parameter adaptive law proposed can be improved by adjusting the parameters related to convergence rate. To reduce the scope of disturbance uncertainties, the steering load disturbances are divided into a bounded unknown time-varying part and a predictable time-varying disturbance. Based on Luenberger observer, the prediction term of load torque is estimated by the current of PMSM in real time. By introducing boundary estimation and robust term of unknown disturbance into the control law and parameter adaptive law respectively, the uncertainties of parameters and unknown external disturbance can be compensated. Simulation and hardware-in-the-loop test are carried out on SBW platform. Experiments show that the control strategy of PMSM servo system designed in this paper has good tracking accuracy and stability.

It is well known that proportional-integral-derivative (PID) controllers are dominant in industrial scenarios. PID with high order derivative or integral terms named generalized PID is superior to the PID. However, there is little literature investigating how to tune the parameters of the generalized PID to enhance the disturbance rejection ability. Toward that end, this paper illustrates that the cascade controllers based on the first-order LADRCs (cascade LADRCs) and high-order LADRCs can be interpreted as the generalized PID with low-pass filters for speed servo systems and position servo systems, which in turn is an alternative method to realize the generalized PID. Moreover, the differences between the high-order LADRC and cascade LADRCs are the generalized integral terms, which can be quantified by integral time multiplied absolute error (ITAE). The proposed LADRC controllers are verified and compared with the current controllers by simulations in MATLAB/Simulink. Lastly, one experimental example of the LADRC controllers is implemented on the position servo DC motor system platform.

In the paper, an improved hybrid particle swarm optimization (IHPSO) algorithm is proposed to solve the optimization problem of controller parameters in the design of permanent magnet synchronous motor (PMSM) servo system. The proposed algorithm presents the directional mutation operation to the particles which fixes the position of some particular particles so that enhance the searching ability to some remote regions. In order to cooperate with directional mutation operation, the updating formula of particles velocity is ulteriorly improved. Then, the proposed IHPSO algorithm is adopted to optimize parameters of the designed controller. A simulation and an experimental platform of PMSM servo system are designed using biological intelligence controller based on hormone regulation for the speed control and feedforward compensation for the position controller, where IHPSO is applied to the parameter optimization for speed and position controller, which validate the effectiveness of the IHPSO algorithm and the designed control system.

To achieve the precision contouring performance, this paper presents a contouring compensation approach for the biaxial motion system even under extreme contour tasks. Two permanent magnet linear synchronous motors (PMLSMs) are installed in the biaxial motion platform. First, the dynamics of the biaxial motion servo system with the uncertainties, such as model parameter variations, additive disturbance, and nonlinear friction are introduced. Since Newton algorithm is provided to realize dynamic contouring error estimation, accurate estimation of the contouring error can be achieved, even for the high-velocity and complex contour with sharp corners and large curves. Then, iterative learning control (ILC) is used to control the contouring error for contouring performance improvement. An adaptive PD-type learning law based on an asymmetric Gaussian-like function is applied to improve the performance of system. Moreover, adaptive jerk control (AJC) integrated with adaptive feedback gain is designed to address the negative effect of the uncertainties and enhance the robustness. The adaptive feedback gain is dominated and tuned by a novel adaption law without the need for prior bound knowledge of the uncertainties. Meanwhile, parameter estimation is employed to handle the model parameter variations. Finally, the experimental results are presented to validate the efficiency and the achievable contouring performance of the proposed Newton-ILC and AJC approach.

In this paper, we investigate robust stabilization of linear time-invariant (LTI) systems with external disturbances under event-triggered impulsive control (ETIC). Especially, in order to suppress disturbances effectively, the impulsive instant sequence is generated by means of the sliding-variable-based event-triggering mechanism (ETM). Based on the ETM, some sufficient conditions are derived to exclude Zeno phenomenon and ensure the robust stabilization of the LTI systems. It is shown that the system states are ultimately bounded under the ETIC, and the ultimate bound can be arbitrarily small by selecting the parameter of ETM. More interestingly, it is proved that our obtained results can well address the case of unknown bounded external disturbances, which is often needed to adopt adaptive control to handle in previous results. Then, the theoretical results are applied to the motor servo systems in the presence of external disturbances. Finally, two illustrative example are presented to show the validity of the results.

In this study, we propose and analyze three designs of a novel aerial system that aims for autonomous firefighting missions in the body or border of water areas. In such areas, it is difficult and even dangerous for human firefighters, and firefighting robots, to approach and put out the fire. Thus, the systems proposed in this paper make use of the available water source not only for suppressing the fire, but also for propelling and maneuvering themselves. The three designs are different in their ways of actuating, namely flow rate control, nozzle rotation control, and weight distribution control. The designs are first introduced. Then, mathematical models are formulated and reveal the motion characteristics of each system. A linear control framework is developed and implemented for all of them. Simulation studies were conducted to verify their motion performance and subsequently, to select the best solution. The results indicate that the weight distribution control system struggled to follow the required reference while the two other designs both provided adequate maneuverability. The nozzle rotation control system is the better one, with greater tracking results of the head part and smaller fluctuations of the water hose.

This paper presents a new Reinforcement Learning (RL)-based control approach that uses the Policy Iteration (PI) and a metaheuristic Grey Wolf Optimizer (GWO) algorithm to train the Neural Networks (NNs). Due to an efficient tradeoff to exploration and exploitation, the GWO algorithm shows good results in NN training and solving complex optimization problems. The proposed approach is compared to the classical PI RL-based control approach using the Gradient Descent (GD) algorithm, and with the RL-based control approach which uses the metaheuristic Particle Swarm Optimization (PSO) algorithm. The experiments are conducted using a nonlinear servo system laboratory equipment. Each approach evaluated on how well it solves the optimal reference tracking control for an experimental servo system position control system. The policy NNs specific to all three approaches are implemented as state feedback with integrator controllers to remove the steady-state control errors and thus ensure the convergence of the objective function. Because of the random nature of metaheuristic algorithms, the experiments for GWO and PSO algorithms are run multiple times and the results are averaged before the conclusions are presented. The experimental results shows that for the control objective considered in this paper, the GWO algorithm represents a better solution compared to GD and PSO algorithms.

In dual-motor servo systems, several factors seriously affect the tracking performance especially in high-speed and high-accuracy situations, which include machinery flexibilities, torque disturbance, unmodeled dynamics, and motor parameter differences. Given these factors, this article investigates the command filtered backstepping synchronization control (CFBSC) method for a servo system driven by two motors synchronously. Command filters are used to deal with the virtual control signals in backstepping design process to avoid the computational burden causing by repeated derivatives, and a compensation system is applied to reduce the tracking error. Adaptive control is used to compensate the torque disturbance and unmodeled dynamics. In addition, the speed and torque synchronization control signals are designed to guarantee high synchronization performance. The stability of the dual-motor servo system is proved. And the effectiveness of the proposed controller is validated through experiments.

Eliminating substantial energy dissipation and achieve precise tracking accuracy are both vital for the hydraulic actuated servo system, especially in the face of the global energy crisis and energy exhaustion. When an asymmetric hydraulic cylinder moves symmetrically back and forth, the pressure and flow in the two chambers differ a lot, resulting in huge energy loss. To reduce the throttle loss and overflow loss of the system simultaneously, a hydraulic servo system structure based on dual hydraulic accumulators is proposed in this paper. On the one hand, two hydraulic accumulators with different pressure levels can switch the supply pressure based on the motion direction of the hydraulic cylinder to reduce the throttle loss. On the other hand, the hydraulic accumulators can absorb the excess flow to reduce the overflow loss. In addition, an output feedback controller based on the desired compensation approach is proposed to guarantee the control performance. First, the pressure and velocity signals are replaced by their desired values to reformulate the state equation. Subsequently, the state variables and lumped disturbance are estimated by the low-pass filter-based observer. Compared with the conventional method, this method has the advantages of low noise interference, fewer control parameters and intuitive form. To validate the feasibility of the proposed strategy, the stability of the controller and the energy efficiency of the system are analyzed. The results indicate that the proposed method can significantly improve the system efficiency and ensure tracking accuracy simultaneously.

The sinusoidal encoder is used as an absolute position (velocity) transducer to implement the position (velocity) of actuators in many industrial applications. However, the performance of the position (velocity) can be degraded due to nonideal factors such as differential amplitudes of the encoder signals, offset, and phase shift. To analyze this problem, we formulate the relationship between the coefficients of ideal signals and the nonideal signals characteristic, which is an ellipse formed by plotting the encoder signals versus each other. In this article, we propose a nonideal signal calibration for the imperfect components of existing sinusoidal signals to improve position (velocity) regulation performance. The fictitious cosine function is used to detect the phase shift between the sine and cosine signals, and it can be designed by using the frequency of sinusoidal signals. The proposed method is validated by simulation and experimental implementation, showing noticeable improvement in estimating nonideal signal components, Lissajous error curve, phase distribution, and the position (velocity) error signal. Experimental results show that the proposed method is able to obtain the components of the nonideal signals and the accurate position (velocity) with a small error in real time, while other calibration methods are difficult to apply to fast motion.

This paper studies a high‐performance control design for the servo system of a vehicle‐mounted mobile satellite communication antenna. Considering the different requirements for tracking and disturbance attenuation in the servo system, a novel controller structure consisting of a central controller and a disturbance filter is proposed. Based on this controller structure, a bi‐objective control design scheme is proposed: One is an optimal tracking design for the central controller, and the other is a disturbance attenuation design for the disturbance filter. It turns out that the resulting control system achieves an optimal tracking performance when the external disturbance is at a low level; meanwhile, the system achieves a robust disturbance attenuation performance when the disturbance is significant. Moreover, considering the trade‐offs between performance and the robust stability of the closed‐loop system, the weighting parameter selection in control design criteria is studied for a practical application. Furthermore, validation experiments and field tests are carried out to evaluate the effectiveness of this design, and their results show that the well‐designed bi‐objective controller significantly improves the dynamic pointing accuracy of the antenna in tracking a geostationary satellite when its carrier is driving off‐road.

High energy efficiency and tracking accuracy are both vital for hydraulic lifting servo systems. However, the appropriate hardware configuration and its corresponding nonlinear controller is always a problem to be solved. To address this multi-objective task, an integrated energy-saving and position tracking controller is developed. Specifically, to reduce the substantial energy dissipation, a system configuration referring to the structure of the three-position-six-way valve is proposed. To ensure accurate tracking performance, a hybrid observer-based output feedback controller is developed. By doing so, the function of flow regeneration and the property of flow matching are achieved, and the tracking accuracy is guaranteed by using only position signal. To validate the effectiveness of the proposed method, a common Lyapunov function is used to prove the stability of the multi-model system, and case studies are conducted to demonstrate the system performance.

Inertia load change, torque disturbance, and sophisticated mechanical nonlinearity impose great challenge on the high-precision control design of motor servo systems. To achieve better tracking and disturbance rejection performance, a practical control scheme, which combines a fixed-time-convergent generalized extended state observer (FGESO) with a fixed-time-convergent state feedback control law, is proposed in this article. First, an FGESO is designed to estimate the lumped disturbance and the fixed-time convergence of the estimation errors can be achieved. In the FGESO, there are three parameters and the correction term is selected as a continuous switching function of the output estimation error, which can facilitate the tuning process and greatly alleviate the chattering problem. Second, a control law based on the bilimit homogeneity technique is provided to regulate the tracking errors within a finite time independent of the initial condition. The fixed-time stability of the closed-loop system can be rigorously proved based on the Lyapunov theory. To facilitate the application of the proposed method, a practical two-step tuning procedure is established. Finally, extensive simulations and experiments are performed on a brushless direct current motor to validate the effectiveness and robustness of the proposed method.

This article investigates a class of linear–nonlinear switching active disturbance rejection control (ADRC) to design speed controllers and current controllers for permanent magnet synchronous machine (PMSM) in servo systems, which aims at enhancing the ability of disturbance rejection of speed and current controllers for PMSM. First, the mathematical model of PMSM is introduced. Next, the design of a class of linear–nonlinear switching ADRCs is introduced in details. Then, the stability of linear–nonlinear switching extended state observers (ESOs) is proved by multiple Lyapunov functions. Lastly, the effectiveness of the speed and current controllers based on the linear–nonlinear active disturbance rejection technique is validated by experiments results of a 5.5-kW PMSM platform. Specially, the experiment results of the speed controllers illustrate that the amplitude of speed change of the proposed ADRCs is smaller than that of the linear ADRC (LADRC) when the step load torque disturbance occurs. The proposed ADRCs can overcome the overshoot of speed response caused by improper parameter setting of LADRC. The experiment results of the current controllers show that the proposed LNSADRC type 2 has greater robustness than the other ADRC controllers when $b_{02}$ is not estimated accurately.

In this article, a predictive active disturbance rejection control (ADRC) scheme is proposed for high-precision position tracking control of servo systems with communication delays via sliding mode approach. In the proposed framework, a filtered state predictor is employed to handle time delays in the networked control system. Based on the predictive states, a linear extended state observer is used to compensate unknown perturbations for ADRC, and a boundary layer solution of the sliding mode control is applied via the internal model control rules for robust control. Since the filtered predictive scheme can compensate the time delays and alleviate the effect of the ignored high-frequency dynamics, higher control gains and observer bandwidth of the ADRC can be achieved, leading to a better position tracking accuracy of the control system in the presence of uncertainties and disturbances. The stability of the overall control system is also analyzed via the Lyapunov method. Comparative experiments were carried out to validate the superior performance of the proposed controller.

In the last years, many researches have proposed concerning the motion control and position regulation for manipulators. Motion control has important applications in many areas, for example industrial robotics. In this paper control system based on digital controller for the position control of robotic arm manipulator are build. The proposed control system was simulated on a robot manipulator driven by permanent magnet dc motors. Simulation results show the effectiveness of the control approach.