Multi-loop Control Research Articles

Neural Network-Based Parameter Estimation and Compensation Control for Time-Delay Servo System of Aeroengine

Servo systems are important actuators of aeroengines. The repetitive, reciprocating motion of the servo system leads to significant changes in its time delay and gain characteristics, and degradation increases the uncertainty of these changes. These characteristic variations may have an adverse effect on the dynamic performance of the aeroengine. Therefore, a neural network-based parameter estimation and a multi-loop neural network-based predictive control (ML-NNPC) method for aeroengine inlet guide vane (IGV) servo systems (SVS) were proposed. In this study, the time delay estimation of the servo system was treated as a classification problem, and an SE (squeeze-and-excitation)-GRU (gated recurrent unit) network was proposed to estimate the time delay by using the selected dynamic data of the servo system. The estimated delay was embedded into an online sequential extreme learning machine, and a nonlinear model predictive controller was designed to obtain an optimal control sequence. The compensation control loop was designed to reduce the impact of the model and delay mismatch problems of the control system. The proposed method was applied to the IGV SVS control of a turboshaft engine. The simulation results demonstrate that the time delay is estimated accurately and compensated effectively. Compared to the existing PI and PI with Smith predictor methods, the ML-NNPC method achieves better control performance in the control of both the SVS and the engine rotor speed system. The stability and robustness of the ML-NNPC also show superiority. The results verify the effectiveness of the proposed time delay estimation method and the ML-NNPC method.

Cascade flow rate-temperature control system design based on PID controller using direct synthesis tuning method

Cascade control is one of the multi-loop control schemes that aim to increase the performance of closed-loop control systems. Temperature control on the outlet of a plate heat exchanger often from suffers errors in the control variable and designated set point, so it is necessary to use cascade control in order to stabilize output temperature and reduce the disturbance. The Proportional Integral Derivative (PID) controller in conjunction with the direct synthesis tuning method is used due to ease of implementation and to modify the second-order process model and become the first-order process model, simplifying the model. In cascade control, the flow rate control is designated as the secondary loop, while the temperature control functions as the primary loop. The PID controller model is designed with direct synthesis tuning on the cascade flow rate temperature control, resulting a proportional gain of 2.15%, of 1.976 s, and τd of 0 seconds on the flow rate control loop. Whereas on the temperature control loop, the proportional gain is 13.23%, is 66.3 s and the τd is 7 seconds. The transient responses from cascade flow rate temperature control from Simulink are rise time (tr) = 106.7 seconds, settling time (ts) = 183 seconds, and maximum overshoot = 0%. Based on this parameter, the controller generates Process Variable (PV) responses from master control that can reach the Set Point (SP) without overshoot, maintain a steady state, and reduce the disturbance from slave control within 20 seconds of the response increasing from the steady state condition

Басқарудың цифрлық жүйелерін модельдеу

In this work, a mathematical model of digital control of multi-circuit objects is constructed, taking into account the features of the digital controller as an element of the control system. The article shows the theoretical foundations and methods of designing modern digital control systems based on traditional algorithms and new developments in the field of synthesis of continuous and discrete control systems. An example of mathematical modeling of a twocircuit system with digital control is given. To solve the problem, a standard block diagram of complex multi-loop control systems with von Neumann-type digital controllers was developed, taking into account the random nature of the processed data and real-time delays between transactions. The scientific novelty is the flexibility of the software, which significantly expands the capabilities of implementing complex algorithms, which creates the prerequisites for the practical application of the latest methods of modern control theory.

Comprehensive Optimal Network Scheduling Strategies for Wireless Control Systems

Although wireless control is one of the key technologies for future industries, most wireless networks are only used for monitoring. When wireless networks are applied to transmit control commands, the uncertain link qualities and limited network resources may destroy the performance of multi-loop control systems. Hence, it is critical to allocate these resources to optimize the control performance as the network condition changes and plants evolve. This article presents comprehensive optimal scheduling strategies for wireless control systems based on adaptive dynamic programming. First, we propose an effective adaptive dynamic programming scheduling (ADPS) strategy to solve the optimal scheduling problem based on the single-step control performance at runtime while significantly reducing computational complexity. Moreover, to overcome the “short-sightedness” of single-step performance prediction, we extend ADPS to ADPS-m ( m ulti-step prediction), which optimizes multi-step performance by incorporating a longer-horizon evolution of the plants. Furthermore, we propose ADPS-H ( H eterogeneous flow scheduling) to support heterogeneous flows with different data rates and sizes and ADPS-H-m ( m ulti-step prediction for H eterogeneous flow scheduling), which schedules heterogeneous flows in a longer prediction horizon. We prove that all these scheduling strategies can achieve optimality and stability under mild assumptions. Extensive experiments integrating TOSSIM and MATLAB/Simulink are performed to evaluate all of the proposed methods in case studies of four- and ten-loop control systems. The simulation results demonstrate that these strategies can effectively improve the control performance at lower computing costs under both cyber and physical disturbances. Under the noise level of \(-\) 76 dBm, for the four-loop case, ADPS achieves the same control performance as the linear programming while saving 99.5% of the execution time. ADPS-m further improves the control performance by up to 27.0% compared with ADPS at the prediction horizon of 3, and ADPS-H-m improves the performance by up to 32.3% and 8.4% compared with round-robin and ADPS-H, respectively. The ten-loop case indicates the effectiveness and scalability of the proposed approaches.

Strategy for obtaining robust solutions in multi-objective design with uncertainties

This paper proposes a novel definition of robustness for multi-objective optimization problems. This definition underpins an innovative strategy for obtaining robust solutions in the presence of uncertainty; it involves formulating the cost function under uncertainties as conflicting objectives during optimization. This approach aims to define the decision vectors that are not dominated in all scenarios simultaneously by any other. These solutions exhibit both optimality and robustness properties, aligning with conventional and unconventional multi-objective methods. This approach enables the implicit definition of the Pareto-optimal solutions for each scenario and robust solutions that optimize performance in worst-case scenarios. Additionally, the set of robust solutions that optimize the global performance concerning the utopian points of all uncertainty scenarios is also defined.To demonstrate the effectiveness of this method, this paper addresses two control design problems. The first example, a first-order process, illustrates the advantages and aspects of the optimization strategy. The second problem, multi-loop temperature control design of a proton exchange membrane fuel cell stack, is a more complex engineering problem involving results from previous research.

A modified perturb and observe MPPT algorithm with zero steady state oscillation for single-phase grid-connected transformerless solar inverter

ABSTRACT This paper proposes a modified perturb and observe (P&O) algorithm to improve the performance of maximum power point tracking in a grid-connected solar inverter. The proposed method eliminates the steady state oscillations in photovoltaic panel voltage under stable irradiance conditions there by enhancing its performance. It also retains the simplicity of conventional P&O algorithm and introduces only one additional step of checking the quantum of power change to bypass the perturbations. A cascaded multi-loop control structure is adopted to achieve the objectives and retain the ability to respond to changing environmental conditions. The proposed and conventional P&O algorithms along with a designed 1 kW single-phase grid-connected transformerless solar inverter are simulated in PSIM to perform a comparative study. Furthermore, the proposed algorithm is validated experimentally on the developed solar inverter prototype.

Flatness-based control in successive loops for dual-arm robotic manipulators

Dual-arm robotic manipulators are used in industry and for assisting humans since they enable dexterous handling of objects and more agile and secure execution of pick-and-place, grasping and lifting, or assembling tasks. In this article, a multi-loop flatness-based controller is proposed for the dynamic model of a dual-arm robot. In the considered application, the dual-arm robotic system has to lift and transfer an object under synchronized motion of its two end-effectors while it has also to compensate for the grasping forces between the two end-effectors and the object. The dynamic model of this robotic system is formulated while it is proven that the state-space description of the robot’s dynamics is differentially flat. The control problem for this robotic system is solved with the use of a flatness-based control approach which is implemented in successive loops. To apply the multi-loop flatness-based control method, the state-space model of the dual-arm robotic manipulator is separated into subsystems, which are connected in cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system and control about it can be performed with inversion of its dynamics as in the case of input–output linearized flat systems. The state variables of the preceding i-th subsystem become virtual control inputs for the subsequent ( i + 1)-th subsystem. In turn, real control inputs are applied to the last subsystem. The whole control method is implemented in successive loops and its global stability properties are also proven through Lyapunov stability analysis. The multi-loop flatness-based control approach is an exact nonlinear control scheme which (i) does not use approximate linearization of the dynamic model of the controlled system and (ii) does not need changes of state variables and complicated state-space model transformations.

A Stability-Guarantee Beamforming Scheme in Multi-Loop Wireless Control Systems

A Stability-Guarantee Beamforming Scheme in Multi-Loop Wireless Control Systems

Multiloop Control of Floating Wind Turbines: Tradeoffs in performance and stability

Multiloop Control of Floating Wind Turbines: Tradeoffs in performance and stability

Multi-Body Dynamics Modeling and Simulation of Maglev Satellites

The Lorentz force magnetic levitation gim2bal stabilized platform (LFMP), as a new generation of high-precision turntable for maglev satellites, can meet the requirements of future spacecraft for ultra-high attitude pointing accuracy and stability. To solve the problem of three-module multi-body attitude control under maneuvering conditions, the platform subsystem is first dynamically modeled based on the second type of Lagrangian equation, and the payload subsystem is dynamically modeled based on the Newton–Euler method. Secondly, a multi-loop control system is designed, consisting of high-precision and fast attitude pointing control for the payload, position tracking control for the platform subsystem, and tracking control for the maglev module. The final simulation results verified the feasibility and effectiveness of the payload-centered control method. An evaluation of the stability with a specific model has been performed, and the attitude accuracy of the payload is within 0.00002° and the attitude stability is within 0.00005°/s.

Intelligent optimal control of furnace temperature for the municipal solid waste incineration process using multi-loop controller and particle swarm optimization

Furnace temperature (FT) is a key variable in municipal solid waste incineration (MSWI) processes, influenced by many manipulated variables and directly impacting pollutant concentrations in exhaust gas. Domain experts cannot achieve the optimal FT setpoint value under manual control, leading to abnormal pollutant emission concentrations. To address this, we propose an intelligent optimal control framework for FT aiming to minimize pollutant emission concentration. First, the FT controlled object model is established using the Tikhonov regularization-least regression decision tree (TR-LRDT) algorithm. Then, based on the experience of domain experts, a multi-loop controller is developed using an improved single neuron adaptive PID (ISNA-PID) algorithm to stabilize FT. Next, after establishing NOx and CO2 indicator models, the particle swarm optimization (PSO) algorithm is employed to determine the FT setpoint value in terms of minimum pollutant emission concentration. Finally, the FT intelligent optimal control framework is verified. Experimental results indicate that the optimal FT setpoint value can reduce NOx and CO2 emission concentrations by 19.93 % and 6.99 %, respectively.

Design of a Multi-loop PI Controller for Minimum Phase System Level Regulation in a Quadruple Tank: A Method for Constraint Optimization

Design of a Multi-loop PI Controller for Minimum Phase System Level Regulation in a Quadruple Tank: A Method for Constraint Optimization

Identification and Compensation Method of Unbalanced Error in Driving Chain for Rate-Integrating Hemispherical Resonator Gyro.

The accuracy of the signal within a driving chain for the rate-integrating hemispherical resonator gyro (RI-HRG) plays a crucial role in the overall performance of the gyro. In this paper, a notable and effective method is proposed to realize the identification and compensation of the unbalanced error in the driving chain for the RI-HRG that improved the performance of the multi-loop control applied in the RI-HRG. Firstly, the assembly inclination and eccentricity error of the hemispherical resonator, the inconsistent metal conductive film layer resistance error of the resonator, the coupling error of the driving chain, and the parameter inconsistency error of the circuit components were considered, and the impact of these errors on the multi-loop control applied in the RI-HRG were analyzed. On this basis, the impact was further summarized as the unbalanced error in the driving chain, which included the unbalanced gain error, equivalent misalignment angle, and unbalanced equivalent misalignment angle error. Then, a model between the unbalanced error in the driving chain and a non-ideal precession angular rate was established, which was applicable to both single channel asynchronous control and dual channel synchronous control of the RI-HRG. Further, an unbalanced error identification and compensation method is proposed by utilizing the RI-HRG output with the virtual precession control. Finally, the effectiveness of the proposed method was verified through simulation and experiments in kind. After error compensation, the zero-bias instability of the RI-HRG was improved from 3.0950°/h to 0.0511°/h. The results of experiments in kind demonstrated that the proposed method can effectively suppress the non-ideal angular rate output caused by the unbalanced error in the driving chain for the RI-HRG, thereby further improving the overall performance of the RI-HRG.

Model-free PZC filter-based multi-loop speed controller for servo drives

Model-free PZC filter-based multi-loop speed controller for servo drives

Applying the Integral Controllability Property in a Multi-Loop Control for Stable Voltage Regulation in an Active Distribution Network

Distributed Energies Resources (DERs) can be controlled for supporting the voltage regulation at nodes of an Active Distribution Network (ADN) where they are connected. However, since the ADN is a Multi-Input Multi-Output (MIMO) system with coupled dynamics, the controller of a DER mutually interacts with all other controllers through the distribution lines. These interactions lead to operating conflicts which may drive the ADN to work close to its voltage stability boundaries. To achieve a stable voltage regulation without new investment in the existing ADNs, the present paper proposes a straightforward decentralized design of the multi-loop controllers based on the property of integral controllability. The main feature of the method is that the design problem can be expressed by a single parameter designed both for reducing the effects of the undesired coupling and for increasing the degree of robust stability in the presence of parameter uncertainty in the matrix plant. Simulation studies are developed to illustrate the design result and the performance achieved under different operating conditions. The performance is also compared with the one obtained by another method in terms of the integral absolute error.

Robustness, performance analysis and practical improvements of modified uncertainty and disturbance estimator based control

Modified uncertainty and disturbance estimator (MUDE) based control shows great control performance and robustness against unexpected dynamics in the presence of time delay. However, there are still some problems that have not been analyzed theoretically but actually hinder its further applications, such as noise amplification and control signal fluctuations under delay mismatch. On the other hand, the trade-off between robustness and control performance is still a critical issue in MUDE based controller design. However, some doubts arise when extending the single-loop sensitivity function analysis method to MUDE (multi-loop) control systems. To this end, this paper comprehensively analyzes the performance of MUDE, including control performance and robustness, and proposes some practical improvements to address its issues (denoted as IUDE). An ambiguity in analysis of sensitivity functions for multi-loop control systems is first clarified. Then, based on the two-degree-of-freedom equivalent control structure and sensitivity functions, the control performance and robustness of the MUDE based control system are analyzed in detail, including noise sensitivity and control signal response. Finally, some practical improvements are proposed and a quantitative tuning rule is also derived to facilitate its application. Simulation results show that the proposed control method effectively mitigates the problems of noise amplification and control signal fluctuation while almost not degrading the control performance. Water-tank control experiments have also been performed to validate the efficacy of the proposed method, which depicts a promising prospect in control practice.

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

Maintaining the health and welfare of broilers, besides obtaining and optimizing good performance, are the main objectives of poultry production. In response, climate control remains the most guaranteed strategy for managing livestock successfully. Separate controlling temperature and humidity on the one hand; and contaminant gases on the other was a focus of several investigations. Thus, the particularity of this work which involves the study, analysis, and control of broiler livestock building while taking into account, at the same time, all the system's constituent variables (i.e., temperature, humidity, NH3 and CO2 concentration, air velocity, and differential pressure). In this paper, an Active Disturbance Rejection Control (ADRC) and Proportional Integral Derivative (PID) controllers were designed and combined with a multi-loop approach for a multi-inputs multi-outputs (MIMO) system. Then, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) were used to obtain the optimal controllers' parameters employing the reward function, the Integrated Time Absolute Error (ITAE), according to the poultry system requirements. Simulation experiments were carried out using the Matlab Simulink toolbox to verify the effectiveness of all the proposed control methods with the two optimization algorithms regarding stabilization and tracking setpoints. Despite the introduction of several disturbances in the plant model, the PSO-ADRC controller still exhibits notable benefits in terms of rise time, overshoot, settling time, and good disturbance rejection, proving the robustness of the suggested control method.

Enhanced Tracking in Legged Robots through Model Reduction and Hybrid Control Techniques: Addressing Disturbances, Delays, and Saturation

This study introduces a reduced-order leg dynamic model to simplify the controller design and enhance robustness. The proposed multi-loop control scheme tackles tracking control issues in legged robots, including joint angle and contact-force regulation, disturbance suppression, measurement delay, and motor saturation avoidance. Firstly, model predictive control (MPC) and sliding mode control (SMC) schemes are developed using a simplified model, and their stability is analyzed using the Lyapunov method. Numerical simulations under two disturbances validate the superior tracking performance of the SMC scheme. Secondly, an Nth-order linear active disturbance rejection control (LADRC) is designed based on a simplified model and optimization problems. The second-order LADRC-SMC scheme reduces the contact-force control error in the SMC scheme by ten times. Finally, a fourth-order LADRC-SMC with a Smith Predictor (LADRC-SMC-SP) scheme is formulated, employing each loop controller independently. This scheme simplifies the design and enhances performance. Compared to numerical simulations of the above and existing schemes, the LADRC-SMC-SP scheme eliminates delay oscillations, shortens convergence time, and demonstrates fast force-position tracking responses, minimal overshoot, and strong disturbance rejection. The peak contact-force error in the LADRC-SMC-SP scheme was ten times smaller than that in the LADRC-SMC scheme. The integral square error (ISE) values for the tracking errors of joint angles θ1 and θ2, and contact force f, are 1.6636×10−28 rad2⋅s, 1.7983×10−28 rad2⋅s, and 1.8062×10−30 N2⋅s, respectively. These significant improvements in control performance address the challenges in single-leg dynamic systems, effectively handling disturbances, delays, and motor saturation.

The Speed Control of PMLSM with Discontinuous Driving Coils Based on Multi-loop DOB Model

A permanent magnet linear synchronous motor (PMLSM) with discontinuous driving coils potentially applied in the underground pipeline freight delivery system is introduced in this article. Firstly, the detailed structure of the PMLSM with discontinuous driving coils is designed and presented, and the dynamic models of the PMLSM during three different processes are developed. In addition, based on the proportional-integral (PI) and the adaptive disturbance observer (DOB), a multi-loop control strategy is designed for the PMLSM with discontinuous driving coils. The critical performances of PMLSM, such as the speed precision and anti-disturbance ability, are testified in the experiment, and the results validate that the multi-loop control model with adaptive DOB used in the PMLSM with discontinuous driving coils has better speed precision than the PI+PI model by suppressing the detent force.

A New H∞ Weighted Sensitive Function-Based Robust Multi-Loop PID Controller for a Multi-Variable System

A New <i>H_∞ </i> Weighted Sensitive Function-Based Robust Multi-Loop PID Controller for a Multi-Variable System