Proportional-Integral-Observer-Based Backstepping Approach for Position Control of a Hydraulic Differential Cylinder System With Model Uncertainties and Disturbances

2018 ◽  
Vol 140 (12) ◽  
Author(s):  
Fateme Bakhshande ◽  
Dirk Söffker
Keyword(s):  
Nonlinear System ◽  
Lyapunov Function ◽  
Position Control ◽  
Measurement Noise ◽  
System Model ◽  
Control Input ◽  
External Disturbances ◽  
Proportional Integral ◽  
Unknown Inputs ◽  
Modeling Errors

This paper focuses on the design of an observer-based backstepping controller (BC) for a nonlinear hydraulic differential cylinder system. The system is affected by some uncertainties including modeling errors, external disturbances, and measurement noise. An observer-based control approach is proposed to assure suitable tracking performance and to increase robustness against unknown inputs. The task to estimate system states as well as unknown inputs is performed by a linear proportional-integral-observer (PIO). Input–output linearization is used to linearize the nonlinear system model to be used for the PIO structure. On the other hand, BC is utilized based on nonlinear system model to construct the Lyapunov function and to design the control input simultaneously. Stability or negativeness of the derivative of every-step Lyapunov function is fulfilled. Structural improvement regarding the combination of BC and PIO is the main aim of this contribution. This is supported by a novel stability proof and new conditions for the whole control loop with integrated PIO. Furthermore, parameter selection of BC is elaborately considered by defining a performance/energy criterion. A complete robustness evaluation considering different levels of additional measurement noise, modeling errors, and external disturbances is presented for the first time in this contribution. Experimental results validate the advantages of proposed observer-based approach compared to PIO-based sliding mode control (PIO-SMC) and industrial standard P-controller.

Takagi–Sugeno Fuzzy Predictive Control for a Class of Nonlinear System With Constrains and Disturbances

2015 ◽  
Vol 10 (5) ◽  
Author(s):  
Bin Wang ◽  
Jianwei Zhang ◽  
Delan Zhu ◽  
Diyi Chen
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Predictive Control ◽  
Three Dimensional ◽  
Fuzzy Model ◽  
Control Input ◽  
Chen System ◽  
External Disturbances ◽  
Takagi Sugeno ◽  
Fuzzy Predictive Control

This paper investigates the fuzzy predictive control for a class of nonlinear system with constrains under the condition of noise. Based on the fuzzy linearization theory, a class of nonlinear systems can be described by the Takagi–Sugeno (T–S) fuzzy model. The T–S fuzzy model and predictive control are combined to stabilize the proposed class of nonlinear system, and the detailed mathematical derivation is given. Moreover, the designed controller has been optimized even if the system is constrained by output and control input, or perturbed by external disturbances. Finally, numerical simulations including three-dimensional Lorenz system, four-dimensional Chen system and five-dimensional nonlinear system with external disturbances are presented to demonstrate the universality and effectiveness of the proposed scheme. The approach proposed in this paper is simple and easy to implement and also provides reference for relevant nonlinear systems.

Adaptive non-singular terminal sliding mode controller: new design for full control of the quadrotor with external disturbances

2016 ◽  
Vol 39 (3) ◽  
pp. 371-383 ◽  
Author(s):  
Alireza Modirrousta ◽  
Mahdi Khodabandeh
Keyword(s):  
Position Control ◽  
Sliding Mode ◽  
Control Input ◽  
External Disturbances ◽  
Terminal Sliding Mode ◽  
Nonlinear Disturbance Observer ◽  
Tuning Method ◽  
Regular Control ◽  
Control Scheme ◽  
Sliding Mode Controllers

This paper proposes two different adaptive robust sliding mode controllers for attitude, altitude and position control of a quadrotor. Firstly, it proposes a backstepping non-singular terminal sliding mode control with an adaptive algorithm that is applied to the quadrotor for free chattering, finite time convergence and robust aims. In this control scheme instead of regular control input, the derivative of the control input is achieved from a non-singular terminal second-layer sliding surface. An adaptive tuning method is utilized to deal with the external disturbances whose upper bounds are not required to be known in advance in the inner loop. Secondly, a nonlinear disturbance observer based on the integral sliding mode with adaptive gains is proposed for position control, which is known as the outer loop. Stability and robustness of the proposed controller are proved by using the classical Lyapunov criterion. The simulation results demonstrate the validation of the proposed control scheme.

A Nonlinear Model Predictive Control Design for Autonomous Multivehicle Merging into Platoons

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Muhammad Goli ◽  
Azim Eskandarian
Keyword(s):  
Predictive Control ◽  
Vehicle Dynamics ◽  
Integrated Control ◽  
Measurement Noise ◽  
Controlled Environment ◽  
External Disturbances ◽  
Process Noise ◽  
Modeling Uncertainties ◽  
Modeling Errors ◽  
System States

Integrated control for automated vehicles in platoons with nonlinear coupled dynamics is developed in this article. A nonlinear MPC approach is used to address the multi-input multi-output (MIMO) nature of the problem, the nonlinear vehicle dynamics, and the platoon constraints. The control actions are determined by using model-based prediction in conjunction with constrained optimization. Two distinct scenarios are then simulated. The first scenario consists of the multivehicle merging into an existing platoon in a controlled environment in the absence of noise, whereas the effects of external disturbances, modeling errors, and measurement noise are simulated in the second scenario. An extended Kalman filter (EKF) is utilized to estimate the system states under the sensor and process noise effectively. The simulation results show that the proposed approach is a suitable tool to handle the nonlinearities in the vehicle dynamics, the complication of the multivehicle merging scenario, and the presence of modeling uncertainties and measurement noise.

scholarly journals Force-Free Control for Direct Teaching of a Surgical Assistant Robot End Effector with Wire-Driven Bidirectional Telescopic Mechanism

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3498
Author(s):  
Youqiang Zhang ◽  
Cheol-Su Jeong ◽  
Minhyo Kim ◽  
Sangrok Jin
Keyword(s):  
Control Algorithm ◽  
Position Control ◽  
Friction Model ◽  
Surgical Instruments ◽  
Control Input ◽  
End Effector ◽  
Motor Current ◽  
Direct Teaching ◽  
End Effectors ◽  
Teaching Operation

This paper shows the design and modeling of an end effector with a bidirectional telescopic mechanism to allow a surgical assistant robot to hold and handle surgical instruments. It also presents a force-free control algorithm for the direct teaching of end effectors. The bidirectional telescopic mechanism can actively transmit force both upwards and downwards by staggering the wires on both sides. In order to estimate and control torque via motor current without a force/torque sensor, the gravity model and friction model of the device are derived through repeated experiments. The LuGre model is applied to the friction model, and the static and dynamic parameters are obtained using a curve fitting function and a genetic algorithm. Direct teaching control is designed using a force-free control algorithm that compensates for the estimated torque from the motor current for gravity and friction, and then converts it into a position control input. Direct teaching operation sensitivity is verified through hand-guiding experiments.

Model-Independent Control of a Flexible-Joint Robot Manipulator

2009 ◽  
Vol 131 (4) ◽  
Author(s):  
Withit Chatlatanagulchai ◽  
Peter H. Meckl
Keyword(s):  
Neural Networks ◽  
Open Problem ◽  
High Performance ◽  
Robot Manipulator ◽  
Intrinsic Property ◽  
Variable Structure ◽  
System Model ◽  
Control Input ◽  
Control Laws ◽  
Flexible Joint

Flexibility at the joint of a manipulator is an intrinsic property. Even “rigid-joint” robots, in fact, possess a certain amount of flexibility. Previous experiments confirmed that joint flexibility should be explicitly included in the model when designing a high-performance controller for a manipulator because the flexibility, if not dealt with, can excite system natural frequencies and cause severe damage. However, control design for a flexible-joint robot manipulator is still an open problem. Besides being described by a complicated system model for which the passivity property does not hold, the manipulator is also underactuated, that is, the control input does not drive the link directly, but through the flexible dynamics. Our work offers another possible solution to this open problem. We use three-layer neural networks to represent the system model. Their weights are adapted in real time and from scratch, which means we do not need the mathematical model of the robot in our control algorithm. All uncertainties are handled by variable-structure control. Backstepping structure allows input efforts to be applied to each subsystem where they are needed. Control laws to adjust all adjustable parameters are devised using Lyapunov’s second method to ensure that error trajectories are globally uniformly ultimately bounded. We present two state-feedback schemes: first, when neural networks are used to represent the unknown plant, and second, when neural networks are used to represent the unknown parts of the control laws. In the former case, we also design an observer to enable us to design a control law using only output signals—the link positions. We use simulations to compare our algorithms with some other well-known techniques. We use experiments to demonstrate the practicality of our algorithms.

scholarly journals Control of Nonlinear System with State-Constraints using Barrier Lyapunov Function and Backstepping Method

2018 ◽  
Vol 11 (4) ◽  
pp. 165-174
Author(s):  
Joseph R. P. D. Hasibuan ◽  
Elfi Yulia ◽  
Muhammad Hablul Barri ◽  
Augie Widyotriatmo
Keyword(s):  
Nonlinear System ◽  
Lyapunov Function ◽  
State Constraints ◽  
Backstepping Method ◽  
Barrier Lyapunov Function

Proportional–Integral Controller Design for Combustion-Timing Feedback, From n-Heptane to Iso-Octane in Compression–Ignition Engines

2017 ◽  
Vol 140 (5) ◽  
Author(s):  
Gabriel Ingesson ◽  
Lianhao Yin ◽  
Rolf Johansson ◽  
Per Tunestål
Keyword(s):  
Ignition Delay ◽  
Controller Design ◽  
Negative Temperature ◽  
Operating Conditions ◽  
Measurement Noise ◽  
Noise Sensitivity ◽  
Proportional Integral ◽  
Primary Reference ◽  
The Difference ◽  
Primary Reference Fuels

The problem of designing robust and noise-insensitive proportional–integral (PI) controllers for pressure-sensor-based combustion-timing control was studied through simulation. Different primary reference fuels (PRF) and operating conditions were studied. The simulations were done using a physics-based, control-oriented model with an empirical ignition-delay correlation. It was found that the controllable region in between the zero-gain region for early injection timings and the misfire region for late injection timings is strongly PRF dependent. As a result, it was necessary to adjust intake temperature to compensate for the difference in fuel reactivity prior to the controller design. With adjusted intake temperature, PRF-dependent negative-temperature coefficient (NTC) behavior gave different system characteristics for the different fuels. The PI controller design was accomplished by solving the optimization problem of maximizing disturbance rejection and tracking performance subject to constraints on robustness and measurement-noise sensitivity. Optimal controller gains were found to be limited by the high system gain at late combustion timings and high-load conditions; furthermore, the measurement-noise sensitivity was found to be higher at the low-load operating points where the ignition delay is more sensitive to variations in load and intake conditions. The controller-gain restrictions were found to vary for the different PRFs; the optimal gains for higher PRFs were lower due to a higher system gain, whereas the measurement-noise sensitivity was found to be higher for lower PRFs.

scholarly journals Robust Adaptive Neural Cooperative Control for the USV-UAV Based on the LVS-LVA Guidance Principle

2022 ◽  
Vol 10 (1) ◽  
pp. 51
Author(s):  
Jiqiang Li ◽  
Guoqing Zhang ◽  
Bo Li
Keyword(s):  
Cooperative Control ◽  
Position Control ◽  
Path Following ◽  
Dynamic Surface Control ◽  
Basic Function ◽  
Compact Set ◽  
Control Input ◽  
Dynamic Surface ◽  
Robust Adaptive ◽  
Event Triggered

Around the cooperative path-following control for the underactuated surface vessel (USV) and the unmanned aerial vehicle (UAV), a logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate the reference heading signals for the USV-UAV system by using the “virtual ship” and the “virtual aircraft”, which is critical to establish an effective correlation between the USV and the UAV. Taking the steerable variables (the main engine speed and the rudder angle of the USV, and the rotor angular velocities of the UAV) as the control input, a robust adaptive neural cooperative control algorithm was designed by employing the dynamic surface control (DSC), radial basic function neural networks (RBF-NNs) and the event-triggered technique. In the proposed algorithm, the reference roll angle and pitch angle for the UAV can be calculated from the position control loop by virtue of the nonlinear decouple technique. In addition, the system uncertainties were approximated through the RBF-NNs and the transmission burden from the controller to the actuators was reduced for merits of the event-triggered technique. Thus, the derived control law is superior in terms of the concise form, low transmission burden and robustness. Furthermore, the tracking errors of the USV-UAV cooperative control system can converge to a small compact set through adjusting the designed control parameters appropriately, and it can be also guaranteed that all the signals are the semi-global uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the proposed algorithm has been verified via numerical simulations in the presence of the time-varying disturbances.

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