This article studies the formation and trajectory tracking control of multiagent systems. We present a novel multilayer graph for the multiagent system to enable extensibility of the interaction network. Based on the multilayer graph, a formation control law by using the potential function approach is developed for autonomous formation, formation maintenance, collision, and obstacle avoidance. When the desired formation is achieved, the barycentric of the formation shape is viewed as a virtual leader, and a model predictive control (MPC) scheme is applied to the virtual leader for tracking a reference trajectory; meanwhile, the agents will maintain the desired angles and distances via the formation control law. By applying the proposed schemes, the tasks of formation maintenance and trajectory tracking in a constrained space are fulfilled. Comprehensive simulation studies under different environmental constraints and trajectories confirm the effectiveness of the proposed approaches in addressing the formation and trajectory tracking problems.

In this article, an adaptive path following the controller of a multijoint snake robot (MSR) based on the improved Serpenoid curve is proposed. The proposed controller can make the MSR follow the desired path. Compared with the traditional controller, this controller can make the position error possess fast convergence speed and high stability. The swing, the controller can estimate unknown friction coefficients, which improves the adaptive path following the ability of the MSR in an environment with unknown friction coefficients. First, the dynamic model without lateral force is established. Then, the control objectives of the controller are formulated. Third, the Serpenoid gait equation is improved, and the state-dependent time-varying amplitude is obtained. Fourth, the input–output control function of the system and the tracking function of the swing amplitude compensation are designed by the adaptive control method. The stability of the motion attitude angle variable errors and uniformly ultimately bounded stability of the tracking position are verified, respectively. Finally, the effectiveness and superiority of the proposed controller are verified by experiments.

Summary: As for the obstacle avoidance and formation control for the multi-robot systems, this paper presents an obstacle-avoidance method based on the improved artificial potential field (IAPF) and PID adaptive tracking control algorithm. In order to analyze the dynamics and kinematics of the robot, the mathematical model of the robot is built. Then we construct the motion situational awareness map (MSAM), which can map the environment information around the robot on the MSAM. Based on the MSAM, the IAPF functions are established. We employ the rotating potential field to solve the local minima and oscillations. As for collisions between robots, we build the repulsive potential function and priority model among the robots. Afterwards, the PID adaptive tracking algorithm is utilized to multi-robot formation control. To demonstrate the validity of the proposed method, a series of simulation results confirm that the approaches proposed in this paper can successfully address the obstacle- and collision-avoidance problem while reaching formation.

To improve the convergence rate of path-following errors of a bionic snake robot and reduce the overshoot of kinematic errors, a path-following control method based on fuzzy line-of-sight (LOS) guidance for a bionic snake robot with unknowns is developed. This method designs the time-varying LOS forward distance and sliding mode switching gain according to fuzzy rules, offsets the external interferences, weakens the damage of chattering to robot joints, and reduces the negative impact of external interferences on the robot path-following. In addition, the uncertain friction coefficients are predicted by using the adaptive estimation, which compensates for joints’ rotating force inputs and improves environmental adaptability of the body. By establishing the appropriate Lyapunov function, the stability of the gait angle, motion position, and whole system are verified. Simulation and experiment results show the feasibility and superiority of the proposed method.

To improve the efficiency of the dual active bridge (DAB) converter working in the low and medium power ranges, this paper proposes a new triple-phase-shift (TPS) modulation scheme based on frequency domain fundamental harmonic analysis (FDFHA) with lower root mean square (RMS) current and wider zero-voltage switching (ZVS) range. The DAB converter’s Fourier decomposition expression under TPS is generated, and the FDFHA expression is created using fundamental harmonic analysis (FHA). With the RMS current as the optimization target, the operating point with the smallest RMS current is found by solving for it using the extended global optimum condition (EGOC) that applies to the FDFHA expression. Based on this, a control strategy with a simple controller structure is established, which has excellent dynamic performance. Additionally, when comparing the proposed scheme to other optimized schemes, the results show that the proposed scheme can drastically lower the RMS current in the low and medium power ranges and achieve a wider ZVS range, notably in the low power range to enable all switches to achieve ZVS. Finally, an experimental prototype with a peak efficiency of 95.95% was built to verify the effectiveness of the proposed scheme.