The suggested multiloop output-feedback system for dc/dc power converters deals with changes in parameters and loads, as well as performance issues, by using advanced methods like constrained feedback-loop intelligentification and pole-zero cancelation (PZC)-based order reduction (OR). This study offers several key contributions: 1) a cascade-type model-free observer minimizes steady-state ripple in the output filtering error, thereby broadening the feasible operating region; 2) the resulting observer facilitates an OR adaptive inner loop system capable of exponentially stabilizing the output voltage derivative error; and 3) a nonlinear update rule introduces intelligence into the outer loop by ensuring a critically damped transfer function, which automatically adjusts feedback gain according to the operating conditions. A prototype 3-kW bi-directional power converter demonstrates the practical advantages of the proposed technique by the experimental comparison study.

This article exhibits an innovative intelligent output-feedback solution for the speed tracking problem in servo drives, aimed at reducing peak current as well as the reliance on sensor measurements, system modeling, and load information. The proposed output-feedback system adopts a conventional multiloop structure that operates without current measurements and offers the following three contributions: first, a model-free speed observer based on a low-pass filter using position measurements, achieved through an order reduction technique; first, outer loop intelligence that maintains critically damped tracking performance while lowering peak current levels; and third, a simple adaptive proportional-derivative control for stabilizing inner loop errors designed by an order reduction technique. Experimental validation of the system is conducted using a 500 W brushless dc motor prototype, demonstrating its effectiveness subject to the various load conditions.

This article presents an advanced speed filtering technique for servo drives independent from the system model information with the reduction of the performance tuning difficulty. The contributions are two-fold: (a) the main filtering system outputs the filtered rotor position from the encoder measurement to recover the rotational speed of the rotor through the order reduction by the pole-zero cancellation property, resulting in the filtering error diagonalization, and (b) the subsystem, which forms the second-order disturbance observer, attenuates the disturbance to improve the acceleration filtering accuracy. The prototype 500-W servo drive validates the improvement in filtering performance under several load conditions.

The proposed technique systematically incorporates the low-pass filter (LPF) and disturbance observer (DOB) into the model-free order reduction filter as auxiliary systems to improve the accuracy of speed and acceleration estimations for the servo drive applications. The resultant filter also makes the tuning procedure more convenient through error dynamics diagonalization property. This article results in several practical contributions: 1) the Luenberger observer, serving as the main filtering mechanism from position measurement, enables the filtering estimation error dynamics to be diagonalizable according to the order reduction characteristics; 2) the LPF acting as the first assistant extracts the fundamental component of the speed from the pure differentiation of the position measurement; 3) the DOB-like system as the second assistant improves the disturbance attenuation capability of the entire filtering system against the high-frequency noises. A prototype dynamometer incorporating a 500-W brushless dc motor as the test servo drive, showcases the filtering performance of the proposed solution by demonstrating an improvement in the feedback system's performance.

This study systematically considers the model and load uncertainties of the two-wheeled vehicles and its motor to devise an improved trajectory-tracking controller. The resultant feedback system consists of an inner loop command-following controller with respect to linear velocity and yaw angle references from the outer loop position controller. First, high-order pole-zero cancellation (PZC) techniques derive the model-free observers for the inner and outer loops to estimate the velocity and acceleration without the model structure and its parameter information. Second, similar to the observer design process, the observer-based proportional- integral controllers compensated by active damping terms stabilize the inner and outer loops, ensuring performance recovery by the first-order PZC. A LabVIEW-based prototype two-wheeled vehicle built by the TETRIX kit (vehicle body), OptiTrack (localization), and a MyRIO1900 (controller) validates the effectiveness of the proposed technique.

This article addresses the filtering of position, speed, and acceleration in servo motor applications by confronting practical challenges such as model dependence, complex matrix computations, and inconsistent performance. The proposed filter is systematically derived through the integration of a disturbance observer (DOB) design and a high-order pole-zero cancellation (PZC) technique, yielding the following contributions. First, a double-integral, offset-free position filter reduces the order of the filtering error dynamics by employing nonlinearly parameterized gains. Second, the combination of the DOB-based system with these gains facilitates the design of speed and acceleration filters based on filtered position measurements. Third, the diagonalization of the filtering error dynamics via nonlinear gain parameterization simplifies the tuning process for desired performance. The experimental validation using a 500-W brushless dc motor-based dynamometer demonstrates a 27% improvement in feedback system performance compared to a well-tuned extended state observer (ESO).

The proposed observer-based controller stabilizes the output voltage of dc/dc converters, without without any high-model dependence, including a low-pass filter (LPF) for the output voltage measurement as a part of the main feedback system. Considering additional LPF dynamics makes the closed-loop design process complicated and increases number of tuning factors. To address this challenge, the combination of second-order active damping terms and nonlinearly designed feedback gains for both the controller and observer invokes the second-order pole-zero cancellation (PZC) to lower the increased feedback system order owing to the consideration of LPF dynamics. The model-free observer robustly finds the correct output voltage derivative information based on the second-order PZC technique to remove the necessity of incorporating the current feedback. On the basis of the observer, the output-feedback technique forming proportional–integral–derivative controller assigns the critically damped output voltage response to the controlled system without the singularity problem, including the second-order active damping terms and the disturbance observer as the auxiliary system. A 3-kW prototype dc/dc converter experimentally validated the practical benefits of the closed-loop design.

The proposed cascade-type feedback system stabilizes the terminal voltage of single machine infinite bus (SMIB) systems using two measurements: power angle and terminal voltage. The resultant control law only requires the nominal system parameters of the SMIB, and the observer removes any model dependence. This paper provides several contributions. First, the high-order pole-zero cancellation (PZC) technique constructs the observer to estimate the time derivatives of the terminal voltage and power angle measurements without any SMIB model information. Second, the high-order PZC technique enables the outer loop to estimate the desired power angle reference along the critically damped dynamics for the terminal voltage. Third, the observer-based proportional-double integral-derivative control law for the inner loop exponentially stabilizes the power angle error by reducing the closed-loop order to $2$ through the high-order PZC technique. A MATLAB/Simulink implementation of the proposed cascade-type feedback system validates the effectiveness of the proposed solution.

This study proposes an observer-based multiloop output-feedback system that regulates the output dc-link voltage of dc/dc converters to the desired value to lower the system model dependence level. There are a few features: 1) the outer loop injecting the nonlinear active damping to ensure the critically damped output voltage response; 2) a model-independent output voltage derivative observer facilitates the inner loop and eliminates the need for complex matrix calculations for tuning the estimation performance; and 3) the use of a pole-zero cancellation acceleration error stabilizer for the inner loop helps maintain the targeted closed-loop performance. The experimental study adopts a 420-W brushless dc motor dynamo system as the load for the prototype 600-W bidirectional converter controlled using the proposed solution.

This article designs a filter-based output-feedback system to regulate the speed of permanent magnet synchronous motors (PMSMs), which structures a simple single-loop form compensated by feed-forward terms. The proposed controller design framework considerably reduces the dependence level of the PMSM model by requiring partial nominal parameter values for control law and removing the model structure and whole parameter information for the filter. The main advantages consist of two parts. First, the proposed observer employs the second-order pole-zero cancelation (PZC) technique to continuously extract the speed and acceleration from noisy position measurements by the rotary encoder, independent from the PMSM model. Second, the PZC filter-based proportional–integral control forms a single-loop feedback system including the active damping injection and disturbance observer, which assigns the critically damped performance to the closed-loop system by specially structuring the feedback gains. The performance improvement derived by the closed-loop analysis is validated through an experimental comparison study using a prototype 700-W PMSM controlled by the 32-b microprocessor.

IEC 61131-3 is an international standard for developing standardized software for automation and control systems. Machine vision systems are a prominent technology in the field of computer vision and are widely used in various industries, such as manufacturing, robotics, healthcare, and automotive, and are often combined with AI technologies. In industrial automation systems, software developed for defect detection or product classification typically involves separate systems for automation and machine vision programs, leading to increased system complexity and unnecessary resource wastage. To address these limitations, this study proposes an IEC 61131-3-based integrated development environment for programmable machine vision. We selected 11 APIs commonly used in machine vision systems, evaluated their functions in an IEC 61131-3 compliant development environment, and measured the performance of representative machine vision applications. This approach demonstrates the feasibility of developing PLC and machine vision programs within a single-controller system. We investigated the impact of controller performance on function execution.

This work presents an advanced decentralized multiloop output-feedback solution enabling closed-loop systems to reduce the position synchronization errors via feedback-loop intelligentization and a model-free observer while handling the challenges of the practical concerns, system model and load information dependence, imperfect output measurement, complicated feedback system structure. The contributions of this article fall into three parts: 1) the model-free observer for estimating the speed and acceleration specifies its gain for two design parameters, resulting in diagonalized estimation error dynamics; 2) the observer-based proportional-integral-derivative inner loop control exponentially stabilizes speed errors according to the desired first-order convergent system through the order reduction technique; and 3) the outer loop control injects the desired critically damped position dynamics by incorporating a simple feedback-loop intelligence mechanism. The effectiveness of the proposal is validated through an experimental study using a hardware platform comprising QUBE-servo2 and a MyRIO1900 processor.

This article presents an output-feedback solution involving the observer to the speed control problem in servo systems by eliminating the true system model and reducing the number of sensors. The novel active injection technique derives the observation mechanism for speed, acceleration, and speed control law. The resulting benefits are stated as follows. First, a model-free observer outputs information that emulates the speed and acceleration from the output measurement based on the desired estimation error dynamics obtained by the order reduction property. Second, the observed speed and acceleration enable the constitution of the proposed pole-zero cancellation (PZC) control law leading to the critical damping performance. It is experimentally verified that the resultant critically damped system performs similarly to a conventional PZC controller while reducing the peak current level in the transient periods using a 420 W brushless dc motor dynamo system.

This study designs an advanced single-loop output feedback system for speed servo drive applications, in which a simple proportional–integral–integral (PII) controller equipped with nonlinear feedback and feed-forward gains is formed. The resultant feedback system shows the desired critically damped performance for wide-operating regions by actively handling the system parameter and load uncertainties. There are three contributions: first, the third-order observer estimates, independent from the system model, where the speed and acceleration are obtained using the position measurement with the order reduction property; second, the observer-based PII controller is compensated by active damping with a nonlinearly structured feedback and feed-forward gains; and, third, a guarantee is achieved on the desired critically damped performance through a closed-loop analysis. A hardware testbed that adopts a 500 W brushless DC motor is used to experimentally demonstrate performance improvements over certain constant torque regions under various scenarios.

This paper is concerned with the problem of robustly estimating the speed and acceleration of servo drives without the system model parameter information, depending on only the order of the open-loop system. The proposed filtering solution incorporates the disturbance observer (DOB) into the second-order pole-zero cancellation (PZC) observer. The main contributions fall into three parts. First, the model-free Luenberger observer as the first subsystem specifies its gain structure in the nonlinear form to invoke the second-order PZC. Second, the first-order nonlinear DOB as the second subsystem estimates the high-frequency disturbance to yield the compensation term for the second-order PZC observer. Third, the combination of these two subsystems eventually results in the diagonalized estimation error dynamics, which makes the performance adjusting process more convenient for field engineers. The experimental study confirms the effectiveness of the proposed filtering solution using a 500-W brushless DC (direct current) motor-based servo drive under various operation modes.

The output feedback system proposed in this article robustly regulates the position of the servo drives independent from the current loop and true system parameters and load information, forming a simple structure that is similar to a proportional-integral-derivative controller. The contributions of this article are threefold: 1) a high-order pole-zero cancellation (PZC) observer that estimates the speed and acceleration without the use of a system model; 2) an observer-based proportional-double-integral-derivative (PDID) controller that employs the active damping term as the feed-forward compensator while only using nominal system parameters; and 3) special structures of the PDID and active damping gains that trigger the high-order PZC to ensure a second-order transfer function with the multiple poles. The proposed solution is implemented using QUBE-servo2 to experimentally validate the practical merits of the proposals.

This paper presents a novel filtering solution for servo system applications to extract the speed and acceleration information from the imperfect angle measurement. The proposed solution forms a cascade-type structure without using plant information, including its structural and parameter information, with the following contributions: (a) an improved disturbance attenuation capability incorporating the nonlinearly structured filter gain into the extended state observer and (b) a simple performance tuning process that does not involve matrix algebra to determine the desired filtering gain due to the filtering error dynamics diagonalization by the pole-zero cancellation technique. Moreover, the closed-loop filtering dynamics are rigorously analyzed, and various experiments validate the feasibility of the proposed solution.

This article exhibits a current controller guaranteeing the performance recovery property despite the parameter uncertainties for interior-mounted permanent magnet synchronous motors (IPMSMs). The contributions of the proposed method are as follows. The first one is to build the current control law for the closed-loop system to asymptotically recover the target current tracking performance, while estimating the unknown parameters. The second one is to present a systematic way assigning the optimal control gains by solving an optimization problem. The third one is to rigorously analyze the internal dynamics problem caused by the speed dynamics of IPMSMs. The efficacy of the proposed method is verified by conducting experiments where the proposed method is applied to a 5-kW IPMSM.

This paper proposes an output-feedback solution for DC/DC converter applications that considers model-plant mismatches and load variations as constraints in industrial applications. The following two major contributions of this study are particularly advantageous: (a) nonlinear damping terms to inject the critical damping performance into the closed-loop system with the cooperation of the feedback gain structure depending on the damping coefficients, and (b) estimation of the output voltage derivative by the model-independent observer with only one simple closed-loop eigenvalue and current feedback removal. The experimental study highlights the practical merit of the proposed solution by demonstrating the critical damping performance that suppresses the peak current level using a 3-kW bidirectional DC/DC converter.

This article presents an advanced solution to the speed tracking problem of permanent magnet synchronous motors (PMSMs) subject to the following two practical concerns: uncertain motor parameter values, load variations, and current feedback dependence level. The results present a few contributions for industrial application: first, a parameter-independent angle filter (providing speed and acceleration estimates) by modifying the structure of the conventional extended state observer, second, the angle filter-based pole-zero cancellation acceleration stabilizer removing the $q$ -axis current dependence of the speed loop to secure the current sensor fault tolerance, and third, the adaptive speed loop in the analytic form to improve the tracking performance by boosting feedback gain during only the transient periods. Using a dynamo testbed adopting a 700-W PMSM as the test motor, this experimental study verifies the effectiveness of the proposed technique under various operating modes.