In the hybrid multiple H-bridge topology of beam supply, the load change of a DC/DC full-bridge converter can greatly affect the output voltage during onsite operation. An improved sliding mode control (SMC) strategy is thus proposed in this paper, where the rate of switching control is added to the law of system equivalent control to create a law that can realize a complete sliding mode control. Considering the special operating conditions of the load can have an influence on the performance of the controller, the impact of uncertainty existing in onsite conditions is suppressed with the proposed strategy utilized. The validity of the proposed strategy, finally, is verified by simulation, which proves the outperformance of the system in both robustness and dynamics.
This paper presents a robust control technique for small-scale unmanned helicopters to track predefined trajectories (velocities and heading) in the presence of bounded external disturbances. The controller design is based on the linearized state-space model of the helicopter. The multivariable dynamics of the helicopter is divided into two subsystems, longitudinallateral and heading-heave dynamics respectively. There is no strong coupling between these two subsystems and independent controllers are designed for each subsystem. The external disturbances and model mismatch in the longitudinal-lateral subsystem are present in all (matched and mismatched) channels. This model mismatch and external disturbances are estimated as lumped disturbances using extended disturbance observer and an extended disturbance observer based sliding mode controller is designed for it to counter the effect of these disturbances. In the case of heading-heave subsystem, external disturbances and model mismatch only occur in matched channels so a second order sliding mode controller is designed for it as it is insensitive to matched uncertainties. The control performance is successfully tested in Simulink.
A new 4-D dynamical system with hyperchaos is reported in this work. It is shown that the proposed nonlinear dynamical system with hyperchaos has no equilibrium point. Hence, the new dynamical system exhibits hidden hyperchaotic attractor. An in-depth dynamic analysis of the new hyperchaotic system is carried out with bifurcation transition diagrams, multistability analysis, period-doubling bubbles and offset boosting analysis. Using Integral Sliding Mode Control (ISMC), global hyperchaos synchronization results of the new hyperchaotic system are described in detail. Furthermore, an electronic circuit realization of the new hyperchaotic system has been simulated in MultiSim software version 13.0 and the results of which are in good agreement with the numerical simulations using MATLAB.
In order to control joints of manipulators with high precision, a position tracking control strategy combining fractional calculus with iterative learning control and sliding mode control is proposed for the control of a single joint of manipulators. Considering the coupling between joints of manipulators, a fractional-order iterative sliding mode cross-coupling control strategy is proposed and the theoretical proof of its progressive stability is given. The paper takes a two-joint manipulator as the research object to verify the control strategy of a single-joint manipulator. The results show that the control strategy proposed in this paper makes the two-joint mechanical arm chatter less and the tracking more accurate. The synchronous control of the manipulator is verified by a three-joint manipulator. The results show that the angular displacement adjustment times of the three-joint manipulator are 0.11 s, 0.31 s and 0.24 s, respectively. 3.25 s > 5 s, 3.15 s of a PD cross-coupling control strategy; 2.85 s, 2.32 s, 4.22 s of a PD iterative cross-coupling control strategy; 0.14 s, 0.33 s, 0.28 s of a fractional-order sliding mode cross-coupling control strategy. The root mean square error of the position error of the designed control strategy is 6.47 × 10-6 rad, 3.69 × 10-4 rad, 6.91 × 10-3 rad, respectively. The root mean square error of the synchronization error is 3.96 × 10-4 rad, 1.36 × 10-3 rad, 7.81 × 10-3 rad, superior to the other three control strategies. The results illustrate the effectiveness of the proposed control method.
In global path planning (GPP), an autonomous underwater vehicle (AUV) tracks a predefined path. The main objective of GPP is to generate a collision free sub-optimal path with minimum path cost. The path is defined as a set of segments, passing through selected nodes known as waypoints. For smooth planar motion, the path cost is a function of the path length, the threat cost and the cost of diving. Path length is the total distance travelled from start to end point, threat cost is the penalty of collision with the obstacle and cost of diving is the energy expanse for diving deeper in ocean. This paper addresses the GPP problem for multiple AUVs in formation. Here, Grey Wolf Optimization (GWO) algorithm is used to find the suboptimal path for multiple AUVs in formation. The results obtained are compared to the results of applying Genetic Algorithm (GA) to the same problem. GA concept is simple to understand, easy to implement and supports multi-objective optimization. It is robust to local minima and have wide applications in various fields of science, engineering and commerce. Hence, GA is used for this comparative study. The performance analysis is based on computational time, length of the path generated and the total path cost. The resultant path obtained using GWO is found to be better than GA in terms of path cost and processing time. Thus, GWO is used as the GPP algorithm for three AUVs in formation. The formation follows leader-follower topography. A sliding mode controller (SMC) is developed to minimize the tracking error based on local information while maintaining formation, as mild communication exists. The stability of the sliding surface is verified by Lyapunov stability analysis. With proper path planning, the path cost can be minimized as AUVs can reach their target in less time with less energy expanses. Thus, lower path cost leads to less expensive underwater missions.
The main goal of introducing Active Suspension System in vehicles is to reduce the vehicle body motion under road obstacles which improves the ride comfort of the passenger. In this paper, the Full Car Model (FCM) with seven Degrees of Freedom is considered and simulated by MATLAB/Simulink. The Terminal Sliding Mode Controller (TSMC) and Fractional Order Terminal Sliding Mode Controller (FOTSMC) are designed to enhance the ride quality, stability and passenger comfort for FCM. The designed FOTSMC has the ability to provide higher control accuracy in a finite time. The performances of the designed controllers are evaluated by measuring the vehicle body vibration in both angular and vertical direction under bump input and ISO-8608 random input against passive suspension system. The FrequencyWeighted Root Mean Square (FWRMS) and Vibration dose value of Body Acceleration as per ISO-2631 are evaluated for FOTSMC, TSMC and PSS. The stability of the FCM is proved by Lyapunouv theory. Further analysis with sprung mass and speed variation of FCM demonstrate the robustness of proposed controller. To investigate the performances of designed controllers, comparison is made with existing Sliding Mode Controller (SMC) which proves that the designed FOTSMC performs better than existing SMC.