Pid based sliding mode controller design

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Pid based sliding mode controller design

In recent times the quadrotor unmanned aerial vehicles UAV systems have been getting significant interest from engineers and researchers because of its applications, including both civilian and military sectors. In this paper, the feedback linearization FBL technique is used to linearize the attitude and altitude dynamic equations of the quadrotor.

Pid based sliding mode controller design

Back To Abstract. Unmanned aerial vehicle quadrotor UAV is an aircraft vehicle driven without a human pilot onboard. Earlier, the UAVs came up with the large size, which results in an expensive cost. However, the recent technologies in the batteries, electronics kits, mechanics, etc. Then, depends on the control design requirements, the driven model can be manipulated in various mathematical expressions to describe the translational and the rotational dynamics of the quadrotor UAV.

The explanation of numerous representations of the quadrotor dynamics modeling and control design are discussed, besides computing desired pitch and roll angles by implementing the virtual control method Lee and Kim, The quadrotor classified as a nonlinear, underactuated, and unstable system; these challenges must be considered while designing the control law. Therefore, many control methods have been implemented for the Quadrotor in the literature, such as PID controller which is extensively implemented to control the quadrotor systems because of its simplicity Min et al.

The nonlinear dynamics equations of the quadrotor linearized at the equilibrium points, and then the controllability and observability is tested of the extracted linear model Al-Jarrah and Jhemi, ; Ataka et al. The direct feedback linearization and adaptive feedback linearization for quadrotor is applied Lee et al. The attitude controller is designed based on quantitative feedback theory, then, a fuzzy logic controller is applied to provide the position trajectory tracking for the quadrotor UAV Voos, ; Mardan et al.

In this manuscript, the dynamic model of quadrotor UAV has been mathematically formulated. Then, the feedback linearization technique is used to linearize the attitude dynamic equations of the quadrotor.

The PID controller is applied to stabilize the attitude and altitude of the quadrotor. The rotors are fixed in a cross structure and symmetric shape as illustrated in Figure 1. Essentially, the quadrotor motions controlled by changing the speed of the rotors.

The front and the rear of the quadrotor represented by the rotors 1, 3and the left and the right represented by the rotors 2, 4as depicted in Figure 2. By agreement, the rotors 1, 3 rotate in the clockwise direction, and rotors 2, 4 rotate in the anti-clockwise direction.

The quadrotor moves in a vertical direction by increasing or decreasing the angular velocities of all rotors with the equal speed, which generate a total lift force thrust anti the gravity force. Consequently, the quadrotor takes-off or landing as illustrated in Fig.

The right direction movement of the quadrotor is achieved by increasing the rotational speed of the rotor 2 and decreasing the rotational speed of the rotor 4 ; subsequently, the quadrotor moves to the right direction as depicted in Figure 3C.

Likewise, the left direction movement is achieved by increasing the rotational speed of rotor 4 and decreasing the rotational speed of the rotor 2 ; as a result, the quadrotor moves to the left direction as shown in Figure 3D. The forward movement of the quadrotor is achieved by increasing the rotational speed of the rotor 3 and decreasing the rotational speed of the rotor 1 ; subsequently, the quadrotor moves to the forward direction as illustrated in Figure 3E.

Similarly, the backward movement of the quadrotor is achieved by increasing the rotational speed of the rotor 1 and decreasing the rotational speed of the rotor 3 ; as a result, the quadrotor moves to the backward direction as shown in Figure 3F. The feedback linearization technique uses to transfer the nonlinear systems dynamics to an equivalent linear system that can be handled easily. Then, a proposed controller can be implemented on the linearized model, as shown in Figure 4.

The SMC control technique is used to attract the state variables of the system toward the equilibrium sliding surface and stay on it. The SMC control can be designed as follows. Chattering is an unwanted phenomenon with a finite-frequency, and finite-amplitude oscillations happened near the desired surface Behnamgol et al. The chattering caused by the switching function sign swhich existed in the SMC control law. In this work, the switching function sing s has been approximated by the error function.

pid based sliding mode controller design

On other hand, the switching function sing s in the SMC control laws has been replaced by an approximated error function as shown in Figure 6. The first step is to define the tracking errors as same as in Eq. The third step recalls the sliding mode condition as in Eq. By substitute Eq.The main aim of control design is to provide the desired dynamic behavior of passenger car under road variations.

See diagrams. These controllers may be realized in terms of any element that provides hysteresis. PID control design therefore, boils down to selecting zero locations to achieve the desired output or performance based on the model for the plant. Sliding mode and PID controllers are proposed as a classical controllers and neural network based controller is used for controlling a magnetic levitation system. Backstepping and dynamic surface sliding mode control 7. Sliding mode controller is a powerful nonlinear robust controller under condition of partly uncertain dynamic parameters of system [7].

The design of the linear controller is based on the linearized converter model around an equilibrium point near which the controller gives www. The presented design techniques have also various subsequent extensions: versions 2-DOF PID structures, sliding-mode PI controllers, PI-fuzzy controllers, structures with switching control algorithms.


In this tutorial we will introduce a simple, yet versatile, feedback compensator structure: the Proportional-Integral-Derivative PID controller. So a sliding mode controller is designed based on single power rate reaching law and double power rate reaching law methods. In this letter, a new sliding-mode-based flux and speed estimation Sliding mode variable structure control SMVSC has very strong robustness, which has been widely applied in permanent magnet synchronous motor PMSM speed regulating system.

The small signal models of the buck and boost converters, obtained using standard state space averaging techniques, were utilized in the dissertation. Control output range limiting, integrator anti-windup and bumpless controller output for PID gain changes are some of the salient features of the PID VI.

In the design of sliding mode controller the first stage is a design of sliding surface while the second is forces the state to approach the sliding surface from any other region of the state space, and remains on it [1] Refer Fig. Moreover in [10, 11], sliding mode controller has been servo systems using sliding-mode control is developed in this paper. The sliding surface of the proposed controller is based on the proportional integral derivative PID dynamics.

Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems

Firstly, sliding mode controllers are designed for altitude, roll, pitch and yaw angle controls. It can be noted that if the control force then Equations 3, 4 become the equation of passive suspension system 1, 3. These methods require relativelyHence, a nonlinear control strategy based on sliding mode, which is a standard approach to tackle the parametric and modeling uncertainties of a nonlinear system, is chosen for slip control.

The design requirements are for the closed loop system to track a reference input with a rise time less than 1. The stress of the wire is a better set-point for the controller since the transformation temperatures and hence the Martensite fraction are functions of the wire's stress. The objective is to develop a control model for controlling such systems using a control action in an optimum manner without delay or overshoot and ensuring control stability.

In control systems, sliding mode control is a nonlinear control method that alters the dynamics of a nonlinear system by application of a discontinuous control signal that forces the system to "slide" along a cross-section of the system's normal behavior. Robust nonlinear control design strategies using sliding mode control SMC and integral SMC ISMC are developed, which are capable of achieving reliable and accurate tracking control for systems containing dynamic uncertainty, unmodeled disturbances, and actuator anomalies that result in an unknown and time-varying control direction.

pid based sliding mode controller design

This control scheme improves the ride comfort quality and road handling of the active suspension system for the applications on unpaved street with improvement in chattering effects in control effort. The method is proposed to design a control that guarantees both asymptotic and finite time stability given helped by bilinear The impact of these new FO integral indices based PID design on the closed loop control performance as well as the corresponding optimality of.Pandian, S. December 1, December ; 4 : — Pneumatic robot manipulators are characterized by high-order, time-variant actuator dynamics, nonlinearities due to compressibility of air, external disturbances such as static and Coulomb friction, and wide range of payload variations.

Conventional PID controllers suffer from problems of gain tuning under these conditions. In this paper, a new control algorithm is proposed for the position and trajectory control of pneumatic actuators based on the sliding mode control approach. The stability of motion is proved for the case of a linear, time-invariant switching surface.

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A disadvantage of using sliding mode control for third- and higher-order mechanical systems is the need for acceleration feedback. In this paper, to overcome this difficulty we propose the use of differential pressure. The proposed controller is simple, easy to implement, and robust to payload and parametric variations.

The effectiveness of the new scheme for position and trajectory control is illustrated by experiments on an industrial piston-driven cylindrical actuator with proportional valves.

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VolumeIssue 4. Previous Article Next Article. Technical Papers. PandianShunmugham R.

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Ritsumeikan University, Kusatsu Japan. This Site. Google Scholar. Yasuhiro HayakawaYasuhiro Hayakawa. Yoshinori KanazawaYoshinori Kanazawa.

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Yoshiyuki KamoyamaYoshiyuki Kamoyama. Sadao Kawamura Sadao Kawamura. Author and Article Information.

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Shunmugham R. Dec4 : 9 pages. Published Online: December 1, Article history Received:. Views Icon Views. Cite Icon Cite. Issue Section:. Blackburn, J. Press, Cambridge. Hamerlain, M. Robotics and Automation, Nagoyapp. Hanmandlu, M.These metrics are regularly updated to reflect usage leading up to the last few days. Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

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pid based sliding mode controller design

Find more information on the Altmetric Attention Score and how the score is calculated. Sliding mode control SMC has excellent robustness to model uncertainties and disturbances. This would make SMC an ideal scheme for process control applications where model uncertainties and disturbances are common.

The existing SMC, however, has the major drawback of control chattering; i. This makes SMC not suitable for most chemical processes where the manipulated variables are continuous and where high-frequency changes are not permitted.

The chattering is eliminated via the replacement of the discontinuous switching in the SMC by a continuous input determined by a PID scheme. An adaptive strategy is proposed to tune the PID parameters online to control the process states onto a sliding surface that characterizes the closed-loop performance.

pid based sliding mode controller design

The proposed algorithm has been shown to be effective in controlling an inverted pendulum system and a typical pH neutralization process. To whom correspondence should be addressed. View Author Information. Cite this: Ind. Article Views Altmetric. Citations Abstract Sliding mode control SMC has excellent robustness to model uncertainties and disturbances.

Cited By. This article is cited by 18 publications. Sreepriya, K. Aparna, M. Lakhekar, Laxman M. Waghmare, Prakash G. Jadhav, Rupam Gupta Roy.

IEEE Access8 Journal of the Franklin Institute15 Continuous sliding mode controllers for multi-input multi-output systems. Nonlinear Dynamics94 4 PLC based flow control system using a motor operated valve. Tracking design with single-input CMAC based sliding mode controller.Tianxiang Qi, Hao Wang. In this paper, we design a sliding mode controller named PID-SMC for active queue management in the congestion control system.

Integral Sliding Mode Controller

When the instantaneous queue length error is greater than a set-point, the PID-SMC controller employs a proportional-derivative PD switching function to reduce the queue length overshoot and achieve fast system response; otherwise, the PID-SMC controller uses a proportional-integral-derivative PID switching function to tackle the system uncertainty and ensure high control accuracy.

We also use an enhanced reaching law to improve the dynamic performance and overcome the chattering problem. We conduct simulation experiments in the Network Simulator, and the results demonstrate that our proposed PID-SMC method is robust against uncertainties and disturbances.

PID sliding mode controller design and application to active queue management. Abstract In this paper, we design a sliding mode controller named PID-SMC for active queue management in the congestion control system. Keywords active queue management Congestion control integral separation proportional-integral-derivative reaching law sliding mode control.

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Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems. A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, Kp, Ki, and Kd, are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition.

By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Duffing—Holmes chaotic system is used as an illustrative to show the effectiveness of the proposed robust adaptive PID controller.

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ROS package for online trajectory generation and tracking using nonlinear control law for ground vehicle. Control of a nonlinear liquid level system using a new artificial neural network based reinforcement learning approach. The TWIP simulator was written originally as a collection of scripts that allowed for the simulation of system from a single IC.

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