Controller Design For Systems Research Articles

Improved Design of Concurrent Synchronization System Controller Based on Petri Net

At present, the advancement of science and technology has contributed to the emergence of various network parallel environments, web service concurrency environments and massively parallel processors. In order to abstract some practical systems into concurrent system models, it is necessary to conduct model analysis, and to perform deadlock detection of the concurrent system. Despite prior studies on the control problem of the synchronous concurrent system, there remains room for improvement in terms of workload, time, and efficiency. Some very practical methods are explored by introducing locking and unlocking to synchronize the concurrent system, and the algorithm that involves the specific regulation is provided. The Petri net model of the controller is developed to provide an effective method applicable to find the deadlock and to prevent and eliminate the deadlock for synchronous concurrent systems.

Enhanced disturbance observer-based hybrid cascade active disturbance rejection control design for high-precise tracking system in application to aerospace satellite

In the control issue of the detection system for aerospace satellites, a strategy that can effectively ensure line-of-sight (LOS) stabilization of the detection system under complex environments is essential. As the essential detection part of aerospace satellites, the high-precise tracking system (HTS) can be limited in practice by disturbances and system uncertainties and usually needs to solve a disturbance suppression problem. Motivated by successful applications of the active disturbance rejection control (ADRC) in HTS, this article investigates the LOS stabilization problem for the HTS with disturbances and system nonlinearity utilizing enhanced disturbance observer-based hybrid cascade active disturbance rejection control (CADRC). A novel enhanced disturbance observer (EDOB) together with CADRC is initially designed to estimate the disturbances of the HTS, where EDOB is mainly used to compensate for the impacts of external disturbances, and the disturbances that are difficult to model are estimated by CADRC. A set of simulations and experiments, performed on an HTS, compared with the traditional method, shows that the proposed method can effectively suppress the time-varying uncertainties and non-linear friction.

Adaptive predefined time neural filtered control design for an uncertain nonlinear system and application to flight control

The paper studies the control problem of an uncertain nonlinear system with tracking error constraint, unknown nonlinear functions and unknown control input gains. An asymmetric barrier Lyapunov function composed with predefined time prescribed performance function is constructed to ensure tracking error enters into the predefined asymmetric constraint in a given time. Then radial basis function neural network is adopted to approximate unknown functions. To reduce computation load, minimal-learning parameter technique is applied. Meanwhile, adaptive method is used to solve actuator faults and the unknown control input gains. Moreover, an adaptive neural control strategy is designed in the framework of backstepping method. An adaptive fixed time filter is developed for avoiding the “explosion of complexity” problem, where the convergence speed of the filter error is improved compared with fixed time filter. It is proved that all signals of the closed-loop system are bounded and tracking error is kept in its constraint boundary. At the end, compared numerical simulations and application simulation of a hypersonic vehicle are demonstrated to verify the efficiency of the designed control scheme.

Fixed-Time Observer-Based Output Feedback Control for Nonlinear Systems With Full-State Constraints

This brief investigates the problem of fixed-time state observer-based output feedback control design for nonlinear systems with full-state constraints. First, a fixed-time state observer is constructed to estimate the unknown states, which can accurately estimate the system states within a fixed settling time. Then, by combining the integral barrier Lyapunov function with the backstepping method, the full-state constraints are realized after the fixed time. Meanwhile, the proposed control strategy can directly constrain the states rather than impose constraints on errors, which reduces the conservativeness of the constraint satisfaction condition. The proposed control method ensures that all signals in the closed-loop system are bounded and symmetric state constraints are strictly maintained after the fixed settling time. Finally, simulation results prove the effectiveness of the proposed method.

Homogeneous Unit Sliding Mode Control

The methodology of the unit sliding mode control design (known since 1970s) for linear systems is revised based on the concept of the generalized homogeneity. The restriction about a consistency of the number of control inputs with the dimension of the sliding surface is eliminated. A simple procedure of control parameters tuning based on a known maximal magnitude of matched perturbations is developed. To deal with perturbations of unknown magnitude, a homogeneous sliding mode control with integral action is designed as well. The theoretical results are supported by numerical simulations.

Disturbance estimation-based resilient control design for interval type-2 fuzzy stochastic systems under multiple disturbance observer

This research endeavour's primary attention is on the problems of stabilization and multiple disturbance rejection for a class of interval type-2 fuzzy stochastic systems that are prone to parameter uncertainties and multiple disturbances. Specifically, the multiple disturbances are classified into two aspects: the first aspect is matched disturbances, which emanate from an exogenous system, while the second aspect is norm-bounded mismatched disturbances. Further, to provide a precise estimation of the matched disturbances, a fuzzy rule-based multiple disturbance observer is built. Based on the estimated information from the framed observer, a disturbance estimation-based resilient control is devised that can withstand the effects of disturbances. Besides, the footprints of mismatched kind of disturbances are handled by employing the ( Q , S , R ) − ς ~ dissipative performance. Moreover, to insure the attainment of the foremost objective of this analysis, a collection of suitable criteria has been developed by means of linear matrix inequalities with the satisfied disturbance attenuation index through Lyapunov's theory of stability. In addition, under the lighting of adequate conditions, the gain matrices of the configured controller and the framed observer can be determined. Finally, two simulation examples are supplied as a conclusion to the examination, each serving to illustrate the potency and viability of the designed control scheme and the presented theoretical findings.

A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions

At present, fossil fuel-based power generation systems are reducing drastically because of their less availability in nature. In addition, it produces hazardous gasses and high environmental pollution. So, in this work, the solar natural source is selected for generating the electricity. Due to the nonlinear behavior of PV, achieving maximum voltage from the Photovoltaic (PV) system is a more tough job. In this work, various hybrid optimization controllers are studied for tracing the working power point of the PV under different Partial Shading Conditions. The studied hybrid optimization MPPT methods are equated in terms of oscillations across MPP, output power extraction, settling time of the MPP, dependency on the PV modeling, operating duty value of the converter, error finding accuracy of MPPT, algorithm complexity, tracking speed, periodic tuning required, and the number of sensing parameters utilized. Based on the simulative comparison results, it has been observed that the modified Grey Wolf Optimization based ANFIS hybrid MPPT method provides good results when equated with the other power point tracking techniques. Here, the conventional converter helps increase the PV source voltage from one level to another level. The proposed system is investigated by using the MATLAB/Simulink tool.

Dynamic modeling and closed-loop control design for humanoid robotic systems: Gibbs–Appell formulation and SDRE approach

Dynamic modeling and closed-loop control design for humanoid robotic systems: Gibbs–Appell formulation and SDRE approach

Control Design for a Power-Assisted Mobile Trainer: Applied to Clinical Stroke Rehabilitation

This paper presents control design and implementation for a power-assisted mobile trainer that employs neuro-developmental treatment (NDT) principles. NDT is a gait rehabilitation technique for stroke patients that provides minimum intervention at critical gait events. Traditional NDT rehabilitation is an effective post-stroke treatment but is also time consuming and labor intensive for therapists. Therefore, we designed a mobile NDT trainer to automatically repeat therapists’ intervention patterns, allowing patients to receive sufficient training without increasing therapists’ workloads. Because the trainer was self-propelled, it could cause burdens to stroke patients with limited muscle strength, thereby potentially degrading the rehabilitation effects. Hence, this paper proposes a power-assisted device that can let the mobile trainer follow the user, allowing the subject to focus on the rehabilitation training. We conducted system identification and control design for the power-assisted NDT trainer. We then implemented the designed controllers and tested the trainer. Finally, we invited 10 healthy subjects and 12 stroke patients to conduct clinical experiments. After using the power-assisted NDT trainer, most participants exhibited improvements in swing-phase symmetry, pelvic rotation, and walking speed. Based on the results, the power-assisted device was deemed effective in facilitating stroke rehabilitation.

Design of simple nonovershooting controllers for linear high order systems with or without time delay

In this paper, we mainly considered the problem of nonovershooting control of high order systems with or without time delay by simple controllers. As basic principles for nonovershooting control systems, three propositions are offered and proved. Under direction of these principles, a nonovershooting dominant pole control structure having three dominant poles, i.e., one real pole and a pair of complex conjugate poles on its left, is proposed. While its zeroes and nondominant poles are on the left side of these three dominant poles with sufficient distance. The controllers adopted are composed by first order filter and PD-PID controller. Dominance of the three dominant poles can be checked and ensured through the computational method we offered. Two illustrating examples are given to show the effectiveness of our method.

Reachable Set Estimation and Controller Design for Linear Time-Delayed Control System with Disturbances

This paper investigates reachable set estimation and state-feedback controller design for linear time-delay control systems with bounded disturbances. By constructing an appropriate Lyapunov–Krasovskii functional, we obtain a delay-dependent condition, which determines the admissible bounding ellipsoid for the reachable set of the system we considered. Then, a sufficient condition in the form of liner matrix inequalities is given to solve the problem of controller design and reachable set estimation. Then, by minimizing the volume of the ellipsoid and solving the liner matrix inequality, we obtain the desired ellipsoid and controller gain. A comparative numerical example is given to show the effectiveness of our result.

PI CONTROLLER DESIGN FOR TIME DELAY SYSTEMS USING DIFFERENT MODEL ORDER REDUCTION METHODS

This study focuses on designing PI controllers for time-delay systems using various model order reduction techniques to reduce complexity. The stability boundary locus method was used to determine PI parameters that stabilizing reduced order models. After the PI parameters have been determined using the weighted geometric center method, the calculated controller parameters have been implemented in the original system. In this way, the efficiency of the controller design is effectively demonstrated through the reduction techniques. In addition, the study investigated the effectiveness of reduction methods with increasing time delay and adding an integrator to the system. The importance of these results is that they demonstrate the use of model order reduction techniques in the design of controllers for time-delay systems and reveal the advantages of these methods.

Electric power steering system controller design using induction machine

Electric power steering system controller design using induction machine

On Contractive Port-Hamiltonian Systems With State-Modulated Interconnection and Damping Matrices

In this paper, for the input-state-output class of port-Hamiltonian systems the contraction property is characterized. Recently, some results on contraction of port-Hamiltonian systems with constant interconnection and damping matrices have been published. This paper, extends these results for state-modulated interconnection and damping matrices. In this regard, the powerful method of IDA-PBC is extended for tracking designs. Controller design for under-actuated mechanical systems with non-constant mass matrices usually leads to non-constant (state-modulated) interconnection and damping matrices for the closed-loop system. Therefore, the result of this paper can be used for tracking controller design for under-actuated mechanical systems. To show the potency of proposed results, a tracking controller for cart-pole system is designed and simulated.

Degradation tolerant optimal control design for stochastic linear systems

Degradation tolerant optimal control design for stochastic linear systems

State-Feedback Control Design for Polynomial Discrete-Time Systems obtained via Second-Order Runge-Kutta Discretization

This paper addresses the state-feedback control problem for the class of state-polynomial discrete-time systems. The continuous-time polynomial nonlinear model is discretized by the second-order Runge-Kutta method. The Lyapunov theory and the exponential stability were employed to derive the conditions. The sum of squares formulation was used to check the constraints. Two approaches are presented, the first makes use of the Lyapunov function to recover the gain matrices. While the second formulation allows the design of rational state feedback control gains. We evaluated the impact of the step size used in the discretization process in the results. Numerical experiments were used to illustrate the potential of the proposed technique.

Learning safe control for multi-robot systems: Methods, verification, and open challenges

In this survey, we review the recent advances in control design methods for robotic multi-agent systems (MAS), focusing on learning-based methods with safety considerations. We start by reviewing various notions of safety and liveness properties, and modeling frameworks used for problem formulation of MAS. Then we provide a comprehensive review of learning-based methods for safe control design for multi-robot systems. We start with various shielding-based methods, such as safety certificates, predictive filters, and reachability tools. Then, we review the current state of control barrier certificate learning in both a centralized and distributed manner, followed by a comprehensive review of multi-agent reinforcement learning with a particular focus on safety. Next, we discuss the state-of-the-art verification tools for the correctness of learning-based methods. Based on the capabilities and the limitations of the state-of-the-art methods in learning and verification for MAS, we identify various broad themes for open challenges: how to design methods that can achieve good performance along with safety guarantees; how to decompose single-agent-based centralized methods for MAS; how to account for communication-related practical issues; and how to assess transfer of theoretical guarantees to practice.

Design of Electric Power Steering System Identification and Control for Autonomous Vehicles Based on Artificial Neural Network

Design of Electric Power Steering System Identification and Control for Autonomous Vehicles Based on Artificial Neural Network

Optimized Controller Design for Renewable Energy Systems by using Deep Reinforcement Learning Technique

Optimized Controller Design for Renewable Energy Systems by using Deep Reinforcement Learning Technique

Stability analysis of switching systems with all modes unstable based on a $ \Phi $-dependent max-minimum dwell time method

<abstract><p>This paper applies stable and unstable switching instants to study switching systems with unstable modes under time-dependent switching signals. A new Lyapunov function is proposed to study the properties of switching instant using different $ \Phi $-dependent max-minimum dwell time methods. After that, the global exponential stability conditions for nonlinear and linear switching systems are derived and stable switching is used to compensate for unstable switching and unstable modes. The relevant results are extended to the controller design of linear switching systems. Finally, a simulation verifies the effectiveness of the results of this paper.</p></abstract>