Nonlinear Compensation Term Research Articles

YOLOv7‐EAS: A Small Target Detection of Camera Module Surface Based on Improved YOLOv7

AbstractThe camera module surface may introduce defects in the focusing process, and manual detection of these defects is inefficient and costly. To address this problem, a method to automatically expand the dataset for deep learning models with fewer original images is developed. A defect detection method is also presented, YOLOv7‐EAS, that enhances YOLOv7 for camera module images with complex backgrounds and small target defects. This method introduces NewEIOU Loss, a bounding box regression loss function that extends EIOU Loss with a nonlinear compensation term. This function improves the model's convergence rate to quadratic order. Moreover, the detection head based on ASFF is redesigned to adapt the layer features and spatially filter out irrelevant information to improve the detection rate of small targets. Finally, a 3D attention mechanism is applied to increase the model's ability to extract fine‐grained features without increasing the network parameters. Experimental results show that the improved YOLOv7 algorithm achieves 90.5% mAP for the camera module image dataset, which is 10.7% higher than the original algorithm, at 136 FPS. This method can perform the camera module surface defect detection task more accurately and meet the real‐time requirements of the production line.

Decentralized adaptive neuro-fuzzy dynamic surface control for maximum power point tracking of a photovoltaic system

The current work proposes a decentralized adaptive dynamic surface control approach for extracting the maximum power from a photovoltaic (PV) system and then regulating the required voltage for charging the battery. In this regard, two cascaded direct current-direct current (DC-DC) converters are utilized. The boost converter is interposed between the PV system and the load to help extract the maximum power. The buck-boost converter is then exploited to maintain the output voltage at a specified level which must meet the battery demand. Therefore, to handle the interactions between the cascaded converters, a decentralized control approach is developed. In the suggested approach, by introducing a nonlinear filter, an effective dynamic surface control (DSC) scheme is proposed with guaranteeing asymptotic tracking convergence. Further, by incorporating a nonlinear compensation term into the proposed control approach, the robustness of the resulting controller is improved. In addition, since the model of the converters is nonlinear with unknown uncertainties, the neuro-fuzzy system is used to estimate lumped uncertainties. The proposed control method has good attributes in terms of having a low tracking error, an excellent transition response, and a quick response to changes in atmospheric conditions. The stability of the whole control system is proved by the Lyapunov stability theorem. Finally, comprehensive simulation results are performed to validate the effectiveness of the suggested control approach.

A Novel Extended Desired Compensation Adaptive Law for High-Speed Pick-and-Throw with PKMs

This paper focuses on the development of a new revised Desired Compensation Adaptive Law (DCAL). DCAL is a model-based adaptive control strategy consisting of three main parts: (i) an adaptive feedforward term, (ii) a linear PD feedback term, and (iii) a nonlinear compensation term. In order to deal with highly nonlinear dynamic systems characterized by their abundant uncertainties and parameters variations, we propose to revise the original DCAL control law by adopting adaptive feedback gains depending on the system state errors. Besides, DCAL controller is known for its robustness against measurement noise thanks to its desired compensation design, but a large amount of external disturbances are still not compensated by such a design. Therefore, the proposed DCAL with adaptive gains (DCAL-AG) is extended with a sliding-based term to further improve its robustness and the overall performance. A model-based robust adaptive feedback controller appropriate to the control of nonlinear systems in real-time applications is thereby obtained. To demonstrate the improvements brought by the proposed control strategy, numerical simulations have been conducted on a Delta-link parallel robot named T3KR in a ”Pick-and-Throw” application task at different operating conditions.

Ultra-Local Model-Based Intelligent Robust Control of PKMs: Theory and Simulations

In this paper, we propose a novel Intelligent Robust Control (IRC) suitable for controlling highly nonlinear Multiple-Input-Multiple-Output (MIMO) systems. The proposed IRC scheme takes advantage of the Robust Integral of the Sign of the Error (RISE) control law and Model-Free Control (MFC). The MFC scheme is mainly composed of: (i) a nonlinear function estimated from an ultra-local model representing the input-output behavior of the system, (ii) the νth derivative of the reference trajectory as a feedforward term, and (iii) a feedback control term. MFC is characterized by its simple concept and its ability to compensate for the modeled and unmodeled system dynamics through its nonlinear compensation term. The proposed IRC approach consists of redesigning the feedback term of MFC scheme based on RISE feedback law to further improve its robustness against external disturbances and to guarantee a semi-global asymptotic tracking despite the presence of disturbances and uncertainties. Numerical simulations under different operating conditions have been conducted on T3KR parallel manipulator, in a pick-and-throw task, to validate the relevance of the proposed IRC strategy. The comparison with a model-based feedforward RISE and a feedforward super-twisting sliding mode control, by exploiting different performance indices, confirms the superiority of the proposed IRC approach.

A fuzzy PID controller with nonlinear compensation term for mold level of continuous casting process

The mold level is the key to stable continuous casting production process, and its fluctuation determines the quality of the slab. It is of great economic and scientific value to stabilize the mold level in numerous disturbances and complicated operating modes. To achieve high-precision and fast-response control of mold level control in engineering applications, a fuzzy PID controller with nonlinear compensation term is designed in this paper. By analyze the dynamic characteristics of the mold level, a fuzzy PID controller is designed. The parameters of fuzzy controller is optimized by using PSO algorithm, which achieves a better control effect in abnormal operating conditions. More importantly, a nonlinear compensation term is introduced to compensate the output of the fuzzy PID controller, thus further improving the anti-interference ability of the system. To verify the superiority of our method, a series of simulation studies are carried out. Finally, the method is applied to industrial sites. The running results show that, compared with the traditional control method, our method effectively improves the anti-interference ability under normal operating conditions and better suppresses the fluctuation of casting opening.

Approximate Design of Optimal Controller for Continuous Disturbance Nonlinear Active Magnetic Bearing System

A successive approximation algorithm for optimal controller of nonlinear active magnetic bearing system is presented. By constructing a series of linear two-point boundary value problems, the original optimal control problem is transformed into a series of inhomogeneous linear two-point boundary value problems. The optimal control law consists of exact linear term and nonlinear compensation term. The method only needs to solve the nonlinear compensation terms of the adjoint vector differential equation iteratively.

An iterative method for suboptimal control of a class of nonlinear time-delayed systems

ABSTRACTThis work presents an approximate solution method for the infinite-horizon nonlinear time-delay optimal control problem. A variational iteration method (VIM) is applied to design feedforward and feedback optimal controllers. By using the VIM, the original optimal control is transformed into a sequence of nonhomogeneous linear two-point boundary value problems (TPBVPs). The existence and uniqueness of the optimal control law are proved. The optimal control law obtained consists of an accurate linear feedback term and a nonlinear compensation term which is the limit of an adjoint vector sequence. The feedback term is determined by solving Riccati matrix differential equation. By using the finite-step iteration of a nonlinear compensation sequence, we can obtain a suboptimal control law. Simulation results demonstrate the validity and applicability of the VIM.

Hybrid Fuzzy Decoupling Control for a Precision Maglev Motion System

This paper presents a hybrid fuzzy decoupling control strategy, and its implementation for leveling and positioning a maglev wafer carrier in an integrated circuit (IC) packaging application. The maglev platform possesses micron scale positioning and can carry the wafers with precision motion between workstations. Because the maglev system is open-loop unstable, there are strong nonlinear interactions between electromagnets and the exact nonlinear system model is unknown, it is hard to achieve a good decoupling control performance by using conventional control strategy. Therefore, in this paper, a hybrid fuzzy decoupling control with good decoupling performance is proposed. The decoupling control uses a master–slave structure, which consists of a linear master decoupling control term and a nonlinear slave intelligent compensation term. The master decoupling term decouples the main interactions of the coupled maglev system. Using the decoupled main system as reference, the slave intelligent term compensates the nonlinear interactions. Furthermore, for this control strategy, establishing the exact linear or nonlinear model is not necessary, only an approximated linear model is needed. The experimental results show that the proposed control strategy decouples most of the interactions between the electromagnetic actuators. Experimental comparisons also highlight that the master–slave decoupling control has shorter settling time and smaller steady-state error than a conventional adaptive fuzzy controller and proportional-integral-differential controller.

An Alternating Identification Algorithm for a Class of Nonlinear Dynamical Systems.

While modeling nonlinear systems by combining a linear model with a nonlinear compensation term, namely, virtual unmodeled dynamics (VUD), the parameter estimation of the linear model and the learning-based VUD estimate influences and interacts with each other simultaneously. This paper aims to develop an alternating identification scheme for resolving such a challenging problem, where a projection algorithm is employed to identify the linear model and a feedforward neural network is used to model the VUD of a class of nonlinear dynamical systems. An open-loop estimation algorithm on the VUD is first presented under the known linear model, followed by an alternating identification algorithm for completely unknown nonlinear systems. Algorithm description is given and some simulation studies on multiple input and multiple output nonlinear systems are carried out to illustrate the effectiveness of our proposed modeling techniques.

Dynamic Model and Nonlinear Control for a Two Degrees of Freedom First Generation Tidal Energy Converter

Abstract: Several manufacturers have developed devices with which to harness tidal/currents power in areas where the depth does not exceed 40 meters. These are the so-called first generation tidal energy converters (TEC). The maintenance tasks carried out on these devices therefore require them to be extracted from their bases to the sea surface and subsequently placed back on the bases. Special high performance ships are required for these tasks, signifying high maintenance costs. The automation of emersion and immersion maneuvers will undoubtedly lead to lower costs, given that ships with less demanding requirements will be required for the aforementioned maintenance tasks. This work presents a very simple dynamic modeling for a first generation TEC composed of only two lumped masses, which are handled solely by hydrostatic forces (conceived as volume-increasing devices). We propose a nonlinear control law based on friction terms compensation for closed loop depth and/or orientation control in order to ensure an adequate behavior when the TEC performs emersion and immersion maneuvers with only passive hydrostatic forces. A control scheme based on nonlinear input transformation, a proportional-derivative (PD) linear action and nonlinear compensation term are also proposed in order to ensure a global asymptotic stability of the TEC posture. Finally, the effectiveness of the dynamic model and the controller approach is demonstrated by means of numerical simulations when the TEC is carrying out an emersion maneuver for the development of blade-cleaning maintenance tasks.

Congestion Control for Nonlinear TD-SCDMA Discrete Networks Based on TCP/IP

A successive approximation approach (SAA) is developed to obtain a new congestion controller for the nonlinear TD-SCDMA network control systems based on TCP/IP. By using the successive approximation approach, the original optimal control problem is transformed into a sequence of nonhomogeneous linear two-point boundary value (TPBV) problems. The optimal control law obtained consists of an accurate linear feedback term and a nonlinear compensation term that is the limit of the solution sequence of the adjoint vector differential equations. By using the finite-time iteration of nonlinear compensation term of optimal solution sequence, we can obtain a suboptimal control law for TD-SCDMA network control systems based on TCP/IP.

An iterative method for suboptimal control of linear time-delayed systems

This article presents a new approach for solving the Optimal Control Problem (OCP) of linear time-delay systems with a quadratic cost functional. The proposed method can also be used for designing optimal control time-delay systems with disturbance. In this study, the Variational Iteration Method (VIM) is employed to convert the original Time-Delay Optimal Control Problem (TDOCP) into a sequence of nonhomogeneous linear two-point boundary value problems (TPBVPs). The optimal control law obtained consists of an accurate linear feedback term and a nonlinear compensation term which is the limit of an adjoint vector sequence. The feedback term is determined by solving Riccati matrix differential equation. By using the finite-step iteration of a nonlinear compensation sequence, we can obtain a suboptimal control law. Finally, Illustrative examples are included to demonstrate the validity and applicability of the technique.

Switching Angular Velocity Observer for Rigid-Body Attitude Stabilization and Tracking Control

This paper provides a new switching angular velocity observer formulation to the classical problem of rigid-body attitude tracking control in the absence of angular rate measurements. Exponential convergence of the angular velocity state estimation errors is proven using a novel error signal definition through the use of this switching-type observer. The observer synthesis and convergence properties are independent of controller design. The switching ensures continuity for all the estimated states. Further, the maximum number of switches required by the observer is shown to be finite and that zeno-type behavior cannot occur. A “separation-property” type result for the attitude tracking problem is established, wherein a proportional-derivative controller uses angular velocity estimates from the proposed switching observer in the absence of actual angular rate measurements, while ensuring almost global asymptotic stability for the overall closed-loop tracking error dynamics. The separation property is also proven to hold when a gyroscopic nonlinear compensation term is added to the proportional-derivative controller.

On integral sliding mode control for a unicycle

In this paper we present an integral sliding mode controller (ISMC) that can stabilise an underactuated unicycle system. The unicycle consists of a wheel and a saddle that is modelled as an inverse pendulum. The control objective for a unicycle is to achieve position control of the wheel while keeping the pendulum at the balanced position that is an unstable equilibrium. The only driving force is the torque applied to the shaft of the wheel. The proposed ISMC consists of an integral sliding surface, a switching term, a nonlinear compensation term and a LQR stabilising controller for the sliding manifold. The ISMC can effectively reject the matched disturbance and reduce the influence from unmatched disturbances, which is verified through rigorous analysis and intensive numerical validation.

Sub-Optimal Control for Nonlinear Heat Equations

This paper presents a successive approximation approach (SAA) designing optimal controllers for a class of nonlinear heat equations with a quadratic performance index. By using the SAA, the optimal control problem for nonlinear heat equations is transformed into a sequence of nonhomogeneous linear differential Riccati operator equations. The optimal control law obtained consists of an accurate linear feedback term and a nonlinear compensation term which is the limit of an adjoin vector sequence. By using the finite-step iteration of the nonlinear compensation sequence, we can obtain a suboptimal control law.

A Successive Approximation Approach of Nonlinear Optimal Control with R-Rank Persistent Disturbances

A new feedforward and feedback optimal control law for a class of nonlinear systems with persistent disturbances is presented in this paper. By using a successive approximation approach (SAA), the original nonlinear optimal control problem is transformed into a sequence of nonhomogeneous linear two-point boundary value (TPBV) problems. The optimal control law obtained consists of analytical linear feedforward and feedback terms and a nonlinear compensation term which is the limit of the solution sequence for the adjoint vector differential equations. By using the finite-step iteration of nonlinear compensation sequence, we can obtain a feedforward and feedback suboptimal control law. A disturbance observer is designed to get a physically realizable controller. Simulation examples show the effectiveness of the approach.

An Approximate Optimal Damping Control Method for Nonlinear Time-delay Systems with Disturbances

The optimal damping control for nonlinear time-delay systems with persistent disturbances is considered. Based on successive approximation approach (SAA), the optimal damping control (ODC) law is achieved by solving a decoupled sequence of inhomogeneous linear two-point boundary value (TPBV) problems without time-delay and time-advance terms. The ODC law of the original problem consists of accurate state feedback term, disturbance rejection term and a nonlinear time-delay compensation term, which is the limit of the adjoint vector sequence. By using the finite-time iteration of the compensation sequence, we can obtain an approximate optimal disturbance rejection control law. The proposed algorithms not only solve optimal control problems in the nonlinear time-delay system but also reduce the computation time and improve the precision. Numerical examples are included to illustrate the procedures.

Series-based approximate approach of optimal tracking control for nonlinear systems with time-delay

The optimal output tracking control (OTC) problem for nonlinear systems with time-delay is considered. Using a series-based approximate approach, the original OTC problem is transformed into iteration solving linear two-point boundary value problems without time-delay. The OTC law obtained consists of analytical linear feedback and feedforward terms and a nonlinear compensation term with an infinite series of the adjoint vectors. By truncating a finite sum of the adjoint vector series, an approximate optimal tracking control law is obtained. A reduced-order reference input observer is constructed to make the feedforward term physically realizable. Simulation examples are used to test the validity of the series-based approximate approach.

Successive approximation procedure of optimal tracking control for nonlinear similar composite systems

The optimal tracking control (OTC) problem for a class of affine nonlinear composite systems with similar structure is considered. By using a modeling technique, the nonlinear similar composite system is first transformed into some quasi-decoupled subsystems. Then the high-order, strongly coupled, nonlinear two-point boundary value (TPBV) problem is transformed into a sequence of linear decoupled TPBV problems through a successive approximation procedure. The obtained OTC law consists of an accurate linear term and a nonlinear compensation term which is the limit of the adjoint vector sequence. A suboptimal tracking control law is obtained by truncating a finite iterative result of the adjoint vector sequence as its nonlinear compensation term.

Optimal output tracking control for bilinear systems

We consider the optimal output tracking control (OOTC) problem for a class of bilinear systems with a quadratic performance index. Using a successive approximation approach (SAA), the original non-linear optimal problem is transformed into a sequence of linear non-homogeneous two-point boundary value (TPBV) problems. An adjoint vector sequence can be obtained from the iterative solution of the sequence of TPBV problems. The OOTC law obtained consists of accurate linear feedback and feedforward terms and a non-linear compensation term which is the limit of the adjoint vector sequence. A reference input observer is constructed to make the approximate OOTC law physically realizable. A numerical simulation is provided to illustrate the effectiveness of the proposed method.