Position Control Applications Research Articles

Position control performance analysis of linear actuator in swashplate-controlled electro hydrostatic actuation system

The position control of an energy efficient electrohydraulic actuation system is a decisive characteristic of its performance. In position control applications, a servo valve and/or variable displacement pump are vital to control the position of the linear actuator. In this open-loop control experimental work, the position of a linear actuator having a stroke length of 0.2 m is controlled by a swashplate-controlled electro hydrostatic actuation system. LabVIEW is used to create the control algorithm, and the National Instrument compact-RIO controller is used to control the voltage supply. The National Instruments controller processes sinusoidal and square demand signals at frequencies of 1/16, 1/12, 1/8, and 1/4 Hz. Open-loop control performance is predominantly dependent on the appropriate tuning of the voltage supply. Control performance is evaluated using the parameters integrated absolute error, integrated square error, integrated time absolute error, and integrated time square error. In comparison to square demand, it has been found that sinusoidal demand offers better position control accuracy, and square demand also offers appropriate control accuracy only at lower frequencies (1/16 Hz).

Robust output regulation of a class of smart actuators described by a minimum phase LPV dynamics

This paper presents a new control strategy for a class of minimum phase linear parameter-varying (LPV) systems representative of smart material actuators. In position control applications of such devices, one is typically interested in achieving output regulation with an arbitrary exponential decay rate. In principle, this problem can be tackled by assigning an exponential decay rate to the full system state, by means of well-established linear matrix inequalities (LMI) methods. For the class of systems under investigation, however, this approach leads to excessively large controller gains in case the desired decay rate is faster than the open-loop zero dynamics. In addition, the existence of unmeasurable state variables related to the material microstructure makes it not possible to directly implement full state feedback laws which are commonly adopted in LPV theory. To overcome these issues, a new design strategy is proposed. The key idea relies on arbitrarily shaping the output exponential decay rate without requiring fast convergence of the full state vector. This goal is achieved by means of a partial state feedback control law which solely depends on the measurable system states. A LMI algorithm is also developed to systematically address the design of the partial state feedback controller. The method is validated by means of simulations on generic examples, as well as via experiments on a mechatronic positioning system based on a dielectric elastomer membrane. In case the desired output convergence speed is faster than the open-loop zero dynamics, it is shown that the new approach leads to better transient behaviors and significantly smaller controller gains than standard LPV design techniques.

A Nonlinear Controller for Point-to-Point Position Control

Position control algorithms can be classified into two groups: point-to-point control and continuous path control. For point-to-point control implemented in programmable logic controllers, the speed setpoint is mostly the only setpoint transmitted to the industrial converter. Incorrect settings of the position controller in PLC may lead to position overshoot or oscillations, which are unacceptable in position control applications. The speed control structure in the industrial converter usually has a fixed structure which does not allow the implementation of advanced speed controller. Moreover, standard library blocks for position control encounter difficulties in diagnostics and tuning. To address these limitations, this paper proposes a novel solution for position control that achieves time-optimal speed trajectory during acceleration and enhanced capabilities during deceleration. The proposed controller was verified by simulations of positioning of zinc ingot feeder unit drive and compared with a standard P-controller. Experimental results confirmed the performance of the proposed controller with the industrial application of a feeder unit.

Maximum sensitivity (Ms)-based I-PD controller design for the control of integrating processes with time delay

Integrating processes, whose one or more poles are located at the origin, are common in the process industry. This paper focuses on maximum sensitivity (Ms)-based control of these types of processes. Integral–proportional derivative (I-PD) controllers are designed by exploiting the direct synthesis method for different forms of integrating processes. The suggested design approach is based on comparing the characteristic equation of the closed-loop system, which comprises the integrating system and I-PD controller with a lead/lag filter, with the desired characteristic equation. Simple and analytical adjusting rules are followed to determine the parameters of the I-PD controller and the lead/lag filter according to desired robustness specified by maximum sensitivity (Ms). The formulas provided contain process transfer function parameters and a tuning parameter that is used for setting the desired Ms. The benefits of the proposed technique are demonstrated by simulation examples and a real-time application of cart position control on an experimental set-up. Comparisons with some reported proportional–integral–derivative (PID) and I-PD design techniques are presented to demonstrate the advantages of the proposed design method more evidently.

Experimental investigation into the basic application of force and position control for human-machine team lifting operations in manufacturing

In manual material handling operations associated with manufacturing, often a two-person team lifts a container. The labor intensive task of lifting a container could be improved by replacing the two-person team with a human-machine team. It is hypothesized that a human-machine team could behave similarly to a two-person team when lifting a container. To test this hypothesis, the presented research experimentally investigated the application of force and position control to a machine that was working collaboratively with a human to lift a constructed container. A basic experimental approach to lifting and control was undertaken at a benchtop scale to evaluate the results for proof-of-concept and further development. For the experimental setup presented, the results show that a combined force and position control architecture delivered better lifting performance as compared to standalone force or position control. It was concluded that the combined force and position control strategy created better team behavior for the machine as it worked collaboratively with the human to lift a constructed container. The advantage of the control approach presented is its simplicity and its ability to be retrofitted to existing equipment. The novelty of the control approach lies within the way the force and position errors from independent controllers are combined into a single command signal with no priority given to either force or position.

Visual and Gyroscope Sensor for Head Movement Controller System on Meal-Assistance Application

Head movement utilizes gestures to aid people with disabilities so that they can have hands-free human-computer interaction. Currently, motion-based sensor is the most widely used approach to recognize head gestures. Identification of head movement is important to control a robotic manipulator in an assisting device. However, the most effective methodologies to assess head angular movements are yet to be discovered. This paper combines two algorithms, the visual sensor and the gyro sensor, to identify head orientation movement with high precision. Head orientations were measured using data distribution and this was done with a meal-assistance robot manipulator used in a sitting position. Evaluation of the accuracy of the system shows a visual sensor and gyro sensor. Experimental results show that a correct head movement with the average accuracy is 82%. Therefore, we propose the application of position control of meal assistive robot based on user's head movement in a sitting position.

A hybrid brain-computer interface for closed-loop position control of a robot arm

Brain-Computer interfacing (BCI) has currently added a new dimension in assistive robotics. Existing brain-computer interfaces designed for position control applications suffer from two fundamental limitations. First, most of the existing schemes employ open-loop control, and thus are unable to track positional errors, resulting in failures in taking necessary online corrective actions. There are examples of a few works dealing with closed-loop electroencephalography (EEG)-based position control. These existing closed-loop brain-induced position control schemes employ a fixed order link selection rule, which often creates a bottleneck preventing time-efficient control. Second, the existing brain-induced position controllers are designed to generate a position response like a traditional first-order system, resulting in a large steady-state error. This paper overcomes the above two limitations by keeping provisions for steady-state visual evoked potential (SSVEP) induced link-selection in an arbitrary order as required for efficient control and generating a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors. Other than the above, the third innovation is to utilize motor imagery and P300 signals to design the hybrid brain-computer interfacing system for the said application with gradually diminishing error-margin using speed reversal at the zero-crossings of positional errors. Experiments undertaken reveal that the steady-state error is reduced to 0.2%. The paper also provides a thorough analysis of the stability of the closed-loop system performance using the Root Locus technique.

Modeling and Analysis of Permanent Magnet Spherical Motors by a Multitask Gaussian Process Method and Finite Element Method for Output Torque

Permanent magnet spherical motors (PMSMs) operate on the principle of the dc excitation of stator coils and three freedom of motion in the rotor. Each coil generates the torque in a specific direction, collectively they move the rotor to a direction of motion. Modeling and analysis of the output torque are of critical importance for precise position control applications. The control of these motors requires precise output torques by all coils at a specific rotor position, which is difficult to achieve in the three-dimension space. This article is the first to apply the Gaussian process to establish the relationship of the rotor position and the output torque for PMSMs. Traditional methods are difficult to resolve such a complex three-dimensional problem with a reasonable computational accuracy and time. This article utilizes a data-driven method using only input and output data validated by experiments. The multitask Gaussian process is developed to calculate the total torque produced by multiple coils at the full operational range. The training data and test data are obtained by the finite-element method. The effectiveness of the proposed method is validated and compared with existing data-driven approaches. The results exhibit superior performance of accuracy.

A fast integral sliding mode controller with an extended state observer for position control of permanent magnet synchronous motor servo systems

Permanent magnet synchronous motor (PMSM) has been widely used in position control applications. Its performance is not satisfactory due to internal uncertainties and external load disturbances. To enhance the control performance of PMSM systems, a new method that has fast response and good robustness is proposed in this study. First, a modified integral terminal sliding mode controller is developed, which has a fast-sliding surface and a continuous reaching law. Then, an extended state observer is applied to measure the internal and external disturbances. Therefore, the disturbances can be compensated for in a feedforward manner. Compared with other sliding mode methods, the proposed method has faster response and better robustness against system disturbances. In addition, the position tracking error can converge to zero in a finite time. Simulation and experimental results reveal that the proposed control method has fast response and good robustness, and enables high-precision control.

Identification of hysteresis models using real-coded genetic algorithms

Finding an accurate model to present the hysteresis nonlinearities behavior of the smart actuator has attracted the attention of the researchers in recent years, since an accurate model has an essential role in the position control application of these actuators. Different models have been developed to describe the hysteresis nonlinearities, the generalized Prandtl-Ishlinskii (GPI) model is one of the most popular used models. This model uses the play operators represented by the threshold values and weights integrated with the odd envelope functions to characterize the hysteresis nonlinearities of smart actuators. The contribution of this paper proposes three different approaches using the Real-Coded Genetic Algorithm (RCGA) for the parameters identification of the Generalized Prandtl-Ishlinskii (GPI) model. In Approach 1, the thresholds and the values of the weights are calculated based on the proposed formulas with the unknown parameters to be identified using RCGA. In Approach 2, the thresholds values are calculated based on the proposed formula with the unknown parameters to be identified using RCGA and the values of the weights are identified directly using RCGA. In Approach 3, the thresholds and the values of the weights are identified directly using RCGA. Also, RCGA was used to identify the values of the coefficients of the envelope functions for all approaches. All approaches are tested through four different examples. Two examples are simulated examples that have linear and tangent hyperbolic envelope functions. Moreover, the other two examples represent experimental data obtained for a piezoelectric actuator and a shape alloy memory (SMA) actuator. The simulation results are carried through by the statistical and convergence analysis of the proposed approaches. The comparison and analysis show that three different approaches can be employed for modeling hysteresis nonlinearities with minimum differences between them.

ISTTOK poloidal field coils positioning assessment

The construction of any machine have inherent structural assembling errors. With aging and stresses these tend to increase and can particularly deform the original structures leading to significant deviations from original designs. To assess ISTTOK poloidal coils fixtures after almost 30 years of operation at IST, Lisbon a series of tests were conducted. Due to its inherent robustness and reliability, the magnetic diagnostic is the prime candidate for real-time plasma position control applications. ISTTOK is equipped with a set of digital integrators for magnetic reconstruction in line with W7-X and in the future with ITER. Incoherence in the data analysis of the poloidal Mirnov coils array suggested a misalignment of the poloidal field (PF) coils. This contribution explores this possibility, relying on the analysis of the magnetic diagnostic data in order to determine the magnetic position of the PF coil circuits. A significant deviation on the positions of said coils was found and a back-propagated correction based on vacuum measurements is proposed for future magnetic data analysis both for real-time control applications and equilibrium reconstruction codes.

Motion Control of Three Links Robot Manipulator (Open Chain) with Spherical Wrist

Robot manipulator is a multi-input multi-output system with high complex nonlinear dynamics, requiring an advanced controller in order to track a specific trajectory. In this work, forward and inverse kinematics are presented based on Denavit Hartenberg notation to convert the end effector planned path from cartesian space to joint space and vice versa where a cubic spline interpolation is used for trajectory segments to ensure the continuity in velocity and acceleration. Also, the derived mathematical dynamic model is based on Eular Lagrange energy method to contain the effect of friction and disturbance torques beside the inertia and Coriolis effect. Two types of controller are applied ; the nonlinear computed torque control (CTC) and the simpler form of its Proportional Derivative plus Gravity (PD+G) where they are designed to reduce the tracking trajectory errors which tend to zero where the used Kp and Kv gains are 900,60. Also, the RMS errors for tracking a step input of CTC were equal to [2.5E-14, 4.4E-14, 5.0E-14, -4.7E-14, -3.9E-14, -4.6E-14] (deg) and of PD+G were equal to [-1.77E-5, -1.22E-6, -4.28E-6, -8.97E-6, -1.32E-5, 1.05E-5] (deg) for joints one to six, respectively. The results show that CTC is more accurate but requires additional acceleration input and is more computationally extensive and PD+G controller is performed with acceptable tracking errors in manipulator position control applications.

Neural network–based sliding-mode control of a tendon sheath–actuated compliant rescue manipulator

The novel contribution of this article is to propose a neural network–based sliding-mode control strategy for improving the position-control performance of a tendon sheath–actuated compliant rescue manipulator. Structural design of a rescue robot with slender and compliant mechanical structure is introduced. The developed robot is capable of drilling into the narrow space under debris and accommodating complicated configuration in ruins. Dynamics modeling and parameters identification of a compliant gripper with flexible tendon sheath transmission are researched and discussed. Moreover, the neural network–based sliding-mode control scheme developed based on radial basis function network is proposed to improve the position-control accuracy of the gripper with modeling uncertainties and external disturbances. The stability of the proposed control system is demonstrated using Lyapunov stability theory. Further experimental investigation including trajectory-tracking experiments and step-response experiments are conducted to confirm the effectiveness of the proposed neural network–based sliding-mode control scheme. Experimental results show that the proposed neural network–based sliding-mode control scheme is superior to cascaded proportional–integral–derivative controller and conventional sliding-mode controller in position-control application.

Implementation of Two-Axis Position-Based Impedance Control with Inverse Kinematics Solution for A 2-DOF Robotic Finger

Position-based impedance control is a force control approach which consists of a single control law that accommodates the external force to achieve the desired dynamics of the body. A previously developed three-fingered robot hand was very rigid in its motion due to the application of position control alone. The position control scheme was inadequate for the tasks that involves the interaction of a robot end-effector with its environment which could damage fragile objects or be prone to slippage when provided with incorrect object's position. This paper introduces the application of two-axis position-based impedance control to one of the 2 degree-of-freedom (DOF) robotic finger of the robot hand. The goal of the control is to produce a mass-spring-dashpot system for the robot hand which considers the external force exerted by the object or environment onto the finger to modify the targeted position of the robot's tip-end. The position-based impedance control which was successfully performed however could not directly drive the DC-micromotors at the finger joints since it was expressed in the Cartesian position (X,Y,Z) form. Therefore, inverse kinematics was derived using geometrical approach to convert the Cartesian position (X,Y,Z) to angle position of motor which is controlled by PID. The proposed control and the developed kinematics were programmed using Matlab Simulink and tested in real-time experiments. The validation result has proven that the proposed position-based impedance control could modify the initial fingertip position according to the amount and direction of the applied external force, thus produced softness to the robotic finger.

Model‐free online tuning of controller parameters using a globalized local search algorithm

SummaryIn an earlier work, the authors proposed a globalized bounded Nelder‐Mead algorithm with deterministic restarts and a linearly growing memory vector. It was shown that the algorithm was a favorable option for solving multimodal optimization problems like controller tuning because of the greater probability of finding the global minimum and lesser numerical cost. Therefore, the algorithm was successfully used for model‐based offline tuning of sliding mode controller parameters for a servo‐pneumatic position control application. However, such offline tuning requires a sufficiently adequate system model, which, in some applications, is difficult to attain. Moreover, it is not generally appreciated as an essential requirement for controller tuning by the end user like the industry. An improvement in performance of optimization algorithm for tuning is expected if it relies on measurements coming directly from an actual physical system and not just its mathematical model. Therefore, in this paper, we apply the aforementioned algorithm for model‐free online optimization of controller parameters. The application involves the programmatic control of a real‐time interface of a physical system by the algorithm for data flow and logical decisions for optimization. For comparison with the results of the model‐based offline tuning suggested in earlier work, the sliding mode controller parameters are tuned online for the same position control application. The experimental results reveal that the system performance with controller parameters tuned online using the algorithm compares favorably to the one with model‐based offline tuning especially at higher priority level for accuracy. The improvement in system performance amounts to 21%.

サーボ系の機械振動抑制FIRフィルタの自動調整

Servo systems are widely used in various position control applications from general industry machine to semiconductor machine. In these systems, it is usually difficult to adjust the controller to high response, because there are mechanical vibrations caused by mechanical resonances and phase delay in high frequency domain. This paper proposes an auto-tuning method of vibration suppression FIR filter using adaptive FIR filter. The auto-tuning method is performed by setting coefficients of adaptive FIR filter outside of control loop to vibration suppression FIR filter in turn. Simulation and experimental results show that the proposed method can suppress the vibration, and can improve stability and response of servo system. Thus, the proposed method can provide auto-tuning of vibration suppression filter under various operating conditions.

Distal Proprioceptive Sensor for Motion Feedback in Endoscope-Based Modular Robotic Systems

Modular robotic systems that integrate distally with commercially available endoscopic equipment have the potential to improve the standard-of-care in therapeutic endoscopy by granting clinicians with capabilities not present in commercial tools, such as precision dexterity and feedback sensing. With the desire to integrate both sensing and actuation distally for closed-loop position control in fully deployable, endoscope-based robotic modules, commercial sensor and actuator options that acquiesce to the strict form-factor requirements are sparse or nonexistent. Herein, we describe a proprioceptive angle sensor for potential closed-loop position control applications in distal robotic modules. Fabricated monolithically using printed-circuit MEMS, the sensor employs a kinematic linkage and the principle of light intensity modulation to sense the angle of articulation with a high degree of fidelity. Onboard temperature and environmental irradiance measurements, coupled with linear regression techniques, provide robust angle measurements that are insensitive to environmental disturbances. The sensor is capable of measuring $\pm$ 45 degrees of articulation with an RMS error of 0.98 degrees. An ex vivo demonstration shows that the sensor can give real-time proprioceptive feedback when coupled with an actuator module, opening up the possibility of fully distal closed-loop control.

Anti-windup PI controller, SIPIC For Motor Position Control

Control system plays a major role in the industry nowadays as it simplifies workload and reduce manpower. Among all the controlled applicable field, control system is heavily used in motor speed and motor position controls. Although there are various types of controllers available in the market, PID controller remains as one of the most used controller due to its simplicity. Unfortunately, PID controller experiences windup phenomenon which affects the controller’s performance. This paper proposes a new type of anti-windup PI controller, SIPIC for motor position control application and aims to validate the performance of this controller as compared to conventional PI controller. To test the ability of the controllers, both controllers were experimented using hardware testing. The settings conditions of with and without loadings were used under two different inputs of 0° to 90° and 270° to 90°. The results obtained show that under without loadings, both controller showed favourable performances. Though, SIPIC controller slightly outperforms PI controller by having lower overshoot and shorter settling time for a wider range of gains. The rise time of both controllers are similar as it is the lowest possible rise time due to hardware limitations. Experiment results with loading condition, for both inputs and when Kp is 1 and Ki is 15, PI controller shows unstable performance by having large amount of oscillations and overshoots. The settling time was unable to be determined as the controller did not settle within the given step time. On the other hand, at the same gain, SIPIC controller still shows acceptable performance. This shows that SIPIC controller is more favourable by having better stable performance for a wider range of gains while PI controller needs to be finely tuned to a specific gain to obtain desired results..

Globalized and bounded Nelder‐Mead algorithm with deterministic restarts for tuning controller parameters: Method and application

SummaryThis paper develops and examines an optimization algorithm for simulation‐based tuning of controller parameters. The proposed algorithm globalizes the Guin augmented variant of Nelder–Mead's nonlinear downhill simplex by deterministic restarts, linearly growing memory vector, and moving initial simplex. First, the effectiveness of the algorithm is tested using 10 complex and multimodal optimization benchmarks. The algorithm achieves global minima of all benchmarks and compares favorably against the evolutionary, swarm, and other globalized local‐search multimodal optimization algorithms in probability of finding global minimum and numerical cost. Next, the proposed algorithm is applied for tuning sliding mode controller parameters for a servo pneumatic position control application. The experimental results reveal that the system with sliding mode controller parameters tuned using the proposed algorithm targeting smooth position control with maximum possible accuracy, performs as desired and eliminates the need of manual online tuning for desired performance. The results are also compared with the performance of the same servo pneumatic system with parameters tuned using manual online tuning in an earlier published work. The system with controller parameters tuned using the proposed algorithm shows improvement in accuracy by 28.9% in sinusoidal and 42.2% in multiple step polynomials tracking.

Online Estimation and Correction of Systematic Encoder Line Errors

This paper addresses the identification and correction of amplitude and offset errors in the sinusoidal outputs from incremental position encoders. Precise angular position measurement is of high importance in many position control applications. Manufacturing tolerances and noise from thermal and electromagnetic interference sources introduce systematic and random errors in the orthogonal sine cosine output line signals. Evaluation of these signals reproduces deviations in the measured angular position. This paper proposes two methods to identify and compensate for the influence of the systematic errors online without the necessity of a reference measurement during identification. The key component of the methods is a nonlinear estimator that exploits the orthogonality property of harmonic functions. The first method explains the basic idea with a scalar error model and operates continuously but exhibits an angular shift in direction of rotation during transients of the parameters, whereas the second method assumes an error model with error parameters as a function over one full revolution of the encoder. The latter updates the error function iteratively in subsequent revolutions.